Pets are family. We celebrate their arrival with the same joy as a grand homecoming, and their absence leaves a grief as deep as losing a loved one. In bonding with cats and dogs, we often attribute human abilities and emotions to them.

But beyond this affection, domestic animals still carry the instincts and genetic legacy of their wild ancestors(1, 2). My cats — Caruso, Muesli, and Plata — have been calm and loving, but they have always enjoyed a real hunt (3). When a moth comes in through a window, they seem possessed: their mouths chitter and make clicking sounds, they leap from one piece of furniture to another, and their heads snap sharply between the insect’s position and other points in the room, calculating the best spot from which to pounce on their prey. That is why when they become feral, cats and dogs integrate into food chains like any other species: they compete for ecosystem resources, hunt and are hunted, and hybridise and exchange diseases with other carnivores (4, 5).

Domestic cats are highly skilled hunters, and their predatory interactions with a wide range of prey are widely documented in social media and documentaries. Some examples include cats catching: bats and birds on the wing, butterflies, chipmunks, dragons, fishes, grasshoppers, frogs, lizards, mice, owls, rabbits, seagulls, snakes, squirrels, and wallabies. See an award-winning photo depicting wildlife with fatal injuries caused by cats recorded in 2019 at a single animal hospital in the USA, and a video showing domestic cats mimicking bird calls and some cat owners explaining that their pets reject commercial cat food after experiencing the thrill of hunting real prey. The documentary Secret Life of Cats contextualises the ecological challenges posed by free-roaming cats.

Preference for native and diverse wildlife

Isac Mella and collaborators studied the prey hunted by 120 domestic cats in the Mexican city of Xalapa (6). The research was made possible through the participation of 44 residents, who were given standardised instructions to collect the animals that their cats brought home each month. From March to August 2018, the felines killed a total of 246 prey (about 41 per month), belonging to 64 different species, with 9 out of 10 being native fauna.

In terms of numbers, reptiles (36%) and invertebrates (23%) made up more than half of the captures, with the rose-bellied lizard (Sceloporus variabilis) the most hunted species (38 individuals). Hunted birds and invertebrates topped the list in terms of diversity (17 species each), followed by reptiles (15 species), and amphibians and mammals (6-9 species). The study also found that striped cats were more successful hunters likely due to their camouflage, and that captures increased the longer the animals spent outdoors (6).

Adapted for constant hunting

Rats and cats are the most damaging predatory mammals to global biodiversity (6). Our cat companions hunt more than 2,000 species of wildlife, including 347 that are at risk of extinction and 11 that are already extinct (7). After being introduced to over 120 islands — most of them lacking natural predators — cats have caused 14% of vertebrate extinctions and currently threaten 8% of vulnerable birds, mammals, and reptiles (8). In countries like Australia (9,37), China (10) and the United States (11), cats kill millions to billions of prey animals every year (5). The problem is both pervasive and global, as the worldwide population exceeds 600 million cats (12-14) [read here and here] and 900 million dogs (4) [read here and here] — together equivalent to the human population of China!

This predatory prowess is no accident: cats are obligate carnivores (15). Unlike the more flexible diet of dogs, a cat’s metabolism is specifically adapted to process protein-rich food (16). Their sense of taste detects the amino acids in meat, but is insensitive to sweetness (17) and shows low sensitivity to saltiness [NaCl], likely due to the high sodium [Na] content in their natural diet of meat (18, 19).

The habit of domestic cats eating several small meals a day mirrors the behaviour of their wild counterparts that hunt and consume multiple small prey throughout the day. Likewise, their tendency to lose interest in repetitive meals at home reflects an innate drive to seek prey variety, likely evolved to prevent nutritional deficiencies in their natural environment.

In short, domestic cats are evolutionarily solitary and territorial animals, compelled to hunt frequently to survive (20). This evolutionary background also explains why cats are generally more independent than dogs (21): cats grant us the privilege of living with them, while dogs — descended from the highly social wolf (22, 23) — can suffer stress or depression when left alone [watch Cats vs. Dogs: Which is Best?].

Invasive in the wild

As a domesticated animal, the cat has no native distribution. Wherever these domestic mammals live in a feral state, they qualify as an exotic invasive species (24). Even when wearing a collar or carrying a microchip, a domestic cat roaming beyond the confines of a human home should be considered a non-native invasive animal.

In Australia, for example, domestic cats with outdoor access kill more wildlife than feral cats (9). However, in many countries such as Spain, domestic cats are not included in official invasive-species lists, creating a legal gap that hampers action. Control measures range from eradication campaigns and euthanasia, sometimes combined with sterilisation followed by release or placement into adoption programs (24, 25).

Strategies vary depending on factors like cat population density, their presence in protected natural areas or available funding. Ironically, although animal welfare advocates and conservationists often share common goals, the issue of domestic cats preying on endangered wildlife has created a deep divide between them.

Hawai’i exemplifies this conflict [watch]: feral cats contribute to the decline of endangered seabirds through direct predation (27), and threaten Hawaiian monk seals (Neomonachus schauinslandi) by spreading the protozoan parasite Toxoplasma gondii (26) that reproduces only in cat hosts (domestic, feral, and wild species). Despite this clear conservation threat, efforts to control feral cat populations face strong opposition from animal welfare groups, illustrating the tension between protecting native wildlife and concern for cat welfare.

Ideally, domestic cats should be kept indoors. If you share your life with cats, giving them full freedom to roam outdoors increases their range and the impact on wildlife, while also exposing them to greater health risks (27). For insights, watch cat management efforts in Canada and watch cat-tracking research.

If you do allow your cats outside, at the very least, restrict their outings to times when wildlife is less active (28). All measures require public support and an informed citizenry (29), because the initial reaction is often negative. People tend to see not the predator they live with, but the beloved family member they have adopted — and that emotion is projected uncritically onto all cats everywhere.

Ancestry of domestic cats. On the left, my cat Caruso with one of his fabric mice, which he often hunts at home as if it were real (Móstoles, Spain). On the right, a female African wildcat (Felis silvestris lybica) wearing a study radio collar in Kgalagadi Transfrontier Park (Botswana) — watch the species hunting birds, mice and termites. There are five subspecies of wildcat (genus Felis) in Africa and Eurasia (31) [watch wildcat diversity]. Genetics confirm that the domestic cat shares its closest common ancestor with the African wildcat [watch evolutionary story here and here] tamed in ancient Mesopotamia (2). The first tomb containing a cat, alongside the deceased’s belongings, dates to around 9,500 years ago at the Neolithic settlement of Shillourokambos, Cyprus (32). Cat domestication [watch archaeological story] might have begun with individuals that approached human settlements, where they only reproduced among themselves (33), while people tolerated them for their effectiveness in controlling pests like mice (34). The Egyptians already selectively bred different varieties, and their spread accelerated with Roman trade routes (34). Selective breeding became widespread after the Middle Ages, when coats other than the wildcat’s grey became common (1). Over time, domestic cats have evolved a range of adaptations tailored to facilitate living alongside humans (35). For example, they meow in a shorter, sharper tone than the wildcat to please and engage with people (36). Watch documentary Cat Tales exploring the human-cat history. Photos courtesy of Clara Inia Herrando (Caruso) and Marna Herbst (African wildcat).

Salvador Herrando-Pérez

References

1. Ottoni C et al. (2017). The palaeogenetics of cat dispersal in the ancient world. Nature Ecology & Evolution 1: 0139
2. Driscoll CA et al. (2007). The Near Eastern origin of cat domestication. Science 317: 519-523
3. Shajid Pyari M et al. (2021). Inexperienced but still interested – indoor-only cats are more inclined for predatory play than cats with outdoor access. Applied Animal Behaviour Science 241: 105373
4. Hughes J & Macdonald DW (2013). A review of the interactions between free-roaming domestic dogs and wildlife. Biological Conservation 157: 341-351. https://doi.org/10.1016/j.biocon.2012.07.005.
5. Loss SR et al. (2022). Review and synthesis of the global literature on domestic cat impacts on wildlife. Journal of Animal Ecology 91: 1361-1372
6. Mella-Méndez I et al. (2022). Predation of wildlife by domestic cats in a Neotropical city: a multi-factor issue. Biological Invasions 24: 1539-1551. https://doi.org/10.1007/s10530-022-02734-5.
7. Lepczyk CA et al. (2023). A global synthesis and assessment of free-ranging domestic cat diet. Nature Communications 14: 7809
8. Medina FM et al. (2011). A global review of the impacts of invasive cats on island endangered vertebrates. Global Change Biology 17: 3503-3510
9. Legge S et al. (2020). We need to worry about Bella and Charlie: the impacts of pet cats on Australian wildlife. Wildlife Research 47: 523-539
10. Li Yet al. (2021). Estimates of wildlife killed by free-ranging cats in China. Biological Conservation 253: 108929
11. Loss SR, Will T & Marra PP (2013). The impact of free-ranging domestic cats on wildlife of the United States. Nature Communications 4: 1396
12. Mori E et al. (2019). License to kill? Domestic cats affect a wide range of native fauna in a highly biodiverse Mediterranean country. Frontiers in Ecology and Evolution 7: 477
13. Rowan AN, Kartal T & Hadidian J (2019). Cat demographics & impact on wildlife in the USA, the UK, Australia and New Zealand: facts and values. Journal of Applied Animal Ethics Research 2: 7-37
14. Bischof R et al. (2022). Mapping the “catscape” formed by a population of pet cats with outdoor access. Scientific Reports 12: 5964
15. Bradshaw JWS et al. (1996). Food selection by the domestic cat, an obligate carnivore. Comparative Biochemistry and Physiology A 114: 205-209
16. Russell K, Murgatroyd PR & Batt RM (2002). Net protein oxidation is adapted to dietary protein intake in domestic cats (Felis silvestris catus). Journal of Nutrition 132: 456-460
17. Li X et al. (2005). Pseudogenization of a sweet-receptor gene accounts for cats’ indifference toward sugar. PLoS Genetics 1: e3
18. Bradshaw JWS (1991). Sensory and experiential factors in the design of foods for domestic dogs and cats. Proceedings of the Nutrition Society 50: 99-106
19. Li P & Wu G, in Nutrition and Metabolism of Dogs and Cats, G Wu, Ed. (Springer Nature Switzerland, Cham, 2024), pp. 55-98
20. Bradshaw JWS (2006). The evolutionary basis for the feeding behavior of domestic dogs (Canis familiaris) and cats (Felis catus). Journal of Nutrition 136: 1927S-1931S
21. Pongrácz P & Lugosi CA (2024). Predator for hire: the curious case of man’s best independent friend, the cat. Applied Animal Behaviour Science 271: 106168
22. Larson G (2021). The question of canine origins. Science 374: 541-541
23. Ollivier M et al. (2018). Dogs accompanied humans during the Neolithic expansion into Europe. Biology Letters 14: 20180286
24. Trouwborst A, McCormack PC & Martínez Camacho E (2020). Domestic cats and their impacts on biodiversity: a blind spot in the application of nature conservation law. People and Nature 2: 235-250
25. Boone JD et al. (2019). A long-term lens: cumulative impacts of free-roaming cat management strategy and intensity on preventable cat mortalities. Frontiers in Veterinary Science 6: 238
26. Robinson SJ, Amlin A & Barbieri MM (2023). Terrestrial pathogen pollutant, Toxoplasma gondii, threatens Hawaiian monk seals (Neomonachus schauinslandi) following heavy runoff events. Journal of Wildlife Diseases 59: 1-11
27. Cecchetti Met al. (2022). Spatial behavior of domestic cats and the effects of outdoor access restrictions and interventions to reduce predation of wildlife. Conservation Science and Practice 4: e597
28. Chung HJ et al. (2024). Safe or sound? Factors influencing outdoor access, cat behavior, and hunting history with implications for conservation and welfare. Applied Animal Behaviour Science 280: 106425
29. Deak BP et al. (2019). The significance of social perceptions in implementing successful feral cat management strategies: a global review. Animals 9: 617
30. Loyd KAT et al. (2013). Quantifying free-roaming domestic cat predation using animal-borne video cameras. Biological Conservation 160: 183-189
31. Steyer K et al. (2016). Large-scale genetic census of an elusive carnivore, the European wildcat (Felis s. silvestris). Conservation Genetics 17: 1183-1199
32. Vigne J-D et al. (2004). Early taming of the cat in Cyprus. Science 304: 259-259
33. Driscoll CA, Macdonald DW & O’Brien SJ (2009). From wild animals to domestic pets, an evolutionary view of domestication. Proceedings of the National Academy of Sciences of the USA 106: 9971-9978
34. Faure E & Kitchener AC (2009). An archaeological and historical review of the relationships between felids and people. Anthrozoös 22: 221-238
35. Natoli E, Litchfield C & Pontier D (2022). Coexistence between humans and ‘misunderstood’ domestic cats in the Anthropocene: exploring behavioural plasticity as a gatekeeper of evolution. Animals 12: 1717
36. Nicastro N (2004). Perceptual and acoustic evidence for species-level differences in meow vocalizations by domestic cats (Felis catus) and African wild cats (Felis silvestris lybica). Journal of Comparative Psychology 118: 287-296
37. Philippe-Lesaffre M et al. (2025). Differential ecological impacts of free-ranging cats among continents. Ecography 2025: e07169

Throughout our lives, we interact with hundreds of wildlife species without stopping to think about it. These interactions can be direct, such as encountering wild animals while hiking in the mountains or driving through rural areas — or more deliberate, as when we engage with wildlife for food, sport, or trade. As hunters, fishers, and collectors, we kill more than 15,000 species of vertebrates — one-third of known diversity — a range of prey 300 times greater than that of any other predator our size (1).

Now, let’s look at it from the other side. Anyone who has survived an attack or a fatal accident, they understand that the experience is remembered for a lifetime. Likewise, animals store information about threatening or harmful encounters with humans (2). For them, adjusting their behaviour in response to human presence has implications for their survival and reproduction (3, 4), which are passed down from generation to generation (5). This ability to adapt, for example, determines which individuals, populations and species coexist with us in urbanised environments (6).

Response to dangerous sounds

Liana Zanette and her team measured the flight responses of wild mammals in the Greater Kruger National Park (South Africa) when exposed to sounds that signal danger (7) [video-summary]. To do this, Zanette recorded videos of more than 4,000 visits to 21 waterholes by 18 mammal species. During each visit, a speaker attached to a tree randomly played one of five playback sounds: hunting dogs barking, gunshots, lion growls, human conversations in a calm tone and, as a control, the songs of harmless birds.

Overall, animals fled in one out of every three recorded scenes. The four dangerous sounds caused them to flee before and more frequently than the bird songs. Notably, animals fled twice as often and 40% earlier upon hearing human voices compared to lion growls. The average time to abandon a waterhole varied by sound: 14 seconds (humans), 23 seconds (dogs, gunshots, lions), and 32 (birds) seconds. Response times (medians) also varied by species: from 2 seconds (African wild dog Lycaon pictus) to 100 seconds (African elephant Loxodonta africana).

Weighing up to 200 kg, the lion (Panthera leo) is Africa’s largest feline and the continent’s apex predator, capable of hunting virtually any animal, including young elephants (8) — see lion facts and documentary list on this big cat. Since the Pleistocene, lions and humans have shared territories, both employing highly effective group-hunting strategies (9).

However, only our species can be considered an ‘unsustainable superpredator’ (10). Unlike other carnivores, (i) humans are overpopulating the Earth, and (ii) our ability to kill has no natural limits: it is not solely dependent on physical skill, but also on advanced technologies that are regulated to some extent by cultural factors such as resource-exploitation laws.

Research like Zanette’s (7) suggests that wildlife has learned to fear us: they definitely know how we roll. Importantly, if animals avoid humans in protected areas where activities are regulated to varying degrees, this avoidance, and its impact on species’ life histories, is likely to be even more pronounced outside these zones, depending on the type and intensity of human activities.

Fear as part of the landscape

The concept of the “landscape of fear” refers to how animals perceive the risk of being attacked depending on where they are within their habitat (11) — related to the concepts of ecology of fear (12) and nonconsumptive effects (13). A lower presence of wildlife in an area frequented by a predator, whether human or animal, does not necessarily mean the predator has wiped them out; rather, their prey might have simply moved elsewhere (14).

Thus, in the African savannah, large herbivores tend to avoid waterholes that lions frequent, especially at night when the king of the jungle is out hunting (15). The landscape of fear intensifies with the mere presence of humans, and its effects ripple through the food web. A clear example is the mountain lion (Puma concolor) in North America. These carnivores avoid urbanised areas or take longer to return to them after encountering people (16). As a result, deer populations increase in these areas, leading to more intense browsing of vegetation and a shift toward shrub-dominated landscapes (17).

Human presence shapes the behaviour and movement of wild animals, even if they remain unseen and even in protected areas. This cause-and-effect relationship is difficult to measure and has been studied more in conspicuous bird species (18). Zanette argues that many species react negatively to human voices in a systematic way (7). Guided by fear, they flee without pausing to assess whether a person is harmless (e.g., walking or taking photographs) or dangerous (e.g., armed with rifles). This justifies setting visitor quotas for parks and reserves, a practice already in place in Western countries.

Nevertheless, in Africa many protected areas rely on tourism for funding, making it inadequate to restrict visitor numbers (19). Alternative strategies might be needed to help animals become accustomed to human presence, as has been done with gorilla and great ape tourism (20) — see TED talk and expert discussion.

However, these measures are controversial (21). Familiarisation with humans could lead to behaviours resembling domestication, potentially making prey more vulnerable to their natural predators (22). Ultimately, understanding and mitigating the pervasive “landscape of fear” caused by human presence is crucial, not only for conserving wildlife populations, but also for preserving the delicate balance of ecosystems on which our own survival depends.

Salvador Herrando-Pérez

References

1. Darimont CT et al. 2023. Humanity’s diverse predatory niche and its ecological consequences. Communications Biology 6: 609 https://doi.org/10.1038/s42003-023-04940-w
2. Zanette LY & Clinchy, M 2020. Ecology and neurobiology of fear in free-living wildlife. Annual Review of Ecology, Evolution, and Systematics 51: 297-318 https://doi.org/10.1146/annurev-ecolsys-011720-124613
3. Goumas M et al. 2020. The role of animal cognition in human-wildlife interactions. Frontiers in Psychology 11: 589978 https://doi.org/10.3389/fpsyg.2020.589978
4. Whittaker D & Knight, RL 1998. Understanding wildlife responses to humans. Wildlife Society Bulletin 26: 312-317 https://www.jstor.org/stable/3784056
5. Allen MC, Clinchy, M & Zanette, LY 2022. Fear of predators in free-living wildlife reduces population growth over generations. Proceedings of the National Academy of Sciences 119: e2112404119 https://doi.org/10.1073/pnas.2112404119
6. Caspi T et al. 2022. Behavioral plasticity can facilitate evolution in urban environments. Trends in Ecology & Evolution 37: 1092-1103 https://doi.org/10.1016/j.tree.2022.08.002
7. Zanette LY et al. 2023. Fear of the human “super predator” pervades the South African savanna. Current Biology 33: 4689-4696 https://doi.org/10.1016/j.cub.2023.08.089
8. Périquet S, Fritz, H & Revilla, E 2015. The Lion King and the Hyaena Queen: large carnivore interactions and coexistence. Biological Reviews 90: 1197-1214 https://doi.org/10.1111/brv.12152
9. Somerville K 2019, in Humans and lions: conflict, conservation and coexistence. (Taylor & Francis, London, UK), pp. 6-28 https://doi.org/10.4324/9781315151182
10. Darimont CT et al. 2015. The unique ecology of human predators. Science 349: 858-860 https://doi.org/10.1126/science.aac4249
11. Laundre J, Hernández, L & Ripple, W 2010. The landscape of fear: ecological implications of being afraid. The Open Ecology Journal 3: 1-7 https://doi.org/10.2174/1874213001003030001
12. Brown JS 2019, in Encyclopedia of Animal Behavior (Second Edition), JC Choe, Ed. (Academic Press, Oxford), pp. 196-202 https://doi.org/10.1016/B978-0-12-809633-8.20870-4
13. Preisser EL & Bolnick, DI 2008. When predators don’t eat their prey: Nonconsumptive predator effects on prey dynamics. Ecology 89: 2414-2415. https://doi.org/10.1890/08-0522.1
14. Brown JS, Laundré, JW & Gurung, M 1999. The ecology of fear: optimal foraging, game theory, and trophic interactions. Journal of Mammalogy 80: 385-399 https://doi.org/10.2307/1383287
15. Valeix M et al. 2009. Does the risk of encountering lions influence African herbivore behaviour at waterholes? Behavioral Ecology and Sociobiology 63: 1483-1494 https://doi.org/10.1007/s00265-009-0760-3
16. Smith JA et al. 2017. Fear of the human ‘super predator’ reduces feeding time in large carnivores. Proceedings of the Royal Society B 284: 20170433. https://doi.org/10.1098/rspb.2017.043310.1098/rspb.2017.0433
17. Yovovich V, Thomsen, M & Wilmers, CC 2021. Pumas’ fear of humans precipitates changes in plant architecture. Ecosphere 12: e03309 https://doi.org/10.1002/ecs2.3309
18. Green RJ & Higginbottom, K 2000. The effects of non-consumptive wildlife tourism on free-ranging wildlife: a review. Pacific Conservation Biology 6: 183-197 https://doi.org/10.1071/PC000183
19. World Travel & Tourism Council 2019. The economic impact of global wildlife tourism – Travel and tourism as an economic tool for the protection of wildlife. 29 p, London, UK. https://researchhub.wttc.org/product/economic-impact-of-global-wildlife-tourism
20. Stronza AL, Hunt, CA & Fitzgerald, LA 2019. Ecotourism for conservation? Annual Review of Environment and Resources 44: 229-253 https://doi.org/10.1146/annurev-environ-101718-033046
21. Macfie EJ & Williamson, EA 2010. Best practice guidelines for great ape tourism. IUCN Species Survival Commission 38: 1-77. Disponible en https://iucn.org/resources/publication/best-practice-guidelines-great-ape-tourism. https://doi.org/10.1017/CBO9781139087407.022.
22. Geffroy B et al. 2015. How nature-based tourism might increase prey vulnerability to predators. Trends in Ecology & Evolution 30: 755-765 https://doi.org/10.1016/j.tree.2015.09.010

Humans rarely live longer than 100 years. But many other animals and plants can live for several centuries or even millennia, particularly in the ocean.

In the Arctic, there are whales that have survived since the time of Napoleon’s Empire; in the Atlantic, there are molluscs that were contemporary with Christopher Columbus’ voyages; and in Antarctica, there are sponges born before the Holocene when humans were still an insignificant species of hunter-gatherers (see video on lifespan variation in wildlife).

Long-lived species grow slowly and reproduce at later ages (1, 2). As a result, these animals require a long time to form abundant populations and to recover from fishing-related mortality.

Among cartilaginous fish (chimaeras, rays, sharks, and skates), the risk of extinction due to overfishing is twice as high for deep-sea species compared to coastal species, because the former have longer and slower life cycles (3).

Of course, to assess the relationship between extinction risk and species longevity, it is first necessary to measure lifespan, which presents a methodological challenge in deep-sea sharks (4).

Dating eyes

In a study that bridges biology, chemistry and geochronology, Danish researcher Julius Nielsen and his colleagues estimated the longevity of the Greenland shark (Somniosus microcephalus) by analysing 25 females accidentally caught by the country’s fishing fleet between 2010 and 2013 (5) (study featured here and here).

These sharks move from the ocean surface down to depths of around 2000 m (6, 7) (see here for submarine footage along with life-history notes of the species). What’s particularly interesting is that the proteins forming their eye lenses are synthesised during the embryonic stage, while the offspring are still inside their mothers. This means that the chemical composition of an eye lens reflects the mother’s diet and can be used to estimate the newborn’s birthdate.

Nielsen measured the concentration of radiocarbon to determine the age of the sharks’ eyes (5) (see video on estimating the age of sharks).

Radiocarbon, or carbon 14, is present in small, constant amounts throughout an organism’s life (including ours), but after death, its quantity decreases by half every ~ 5700 years (8, 9). By knowing this decay rate, the amount of radiocarbon in inert, organic materials — such as proteins in a fossilised mammoth bone or a shark’s eye lens — can indicate age (see video on radiocarbon dating and my previous blogs here and here).

Using radiocarbon dating, Nielsen found that the studied females were born between 71 and 392 years ago, reaching sexual maturity only after living for at least 150 years. This makes the Greenland shark the longest-living vertebrate known to date, surpassing the bowhead whale (Balaena mysticetus) and the Floreana giant tortoise (Chelonoidis niger) from the Galápagos Islands by more than a century.

Spatial but also vertical protection

With the global decline of coastal fisheries (highlighted in documentaries Seaspiracy and The End of the Line), deep-sea ecosystems have become a new target for exploitation, both for fisheries, which are seen as a partial solution to food insecurity for a growing population of 8+ billion people (10), and for mining (see documentaries here and here).

Cartilaginous fish are clear examples of overfishing in the world’s seas and oceans (11) (watch Sharkwater and its sequel Sharkwater Extinction). One-third of threatened deep-sea shark species are already part of industrial fisheries, with half of them classified as endangered. They are exploited not only for their meat and fins, but also for the oil extracted from their livers (12).

However, the longevity and low reproductive rate of deep-sea sharks make them a finite resource — akin to mining coal (13). Fishing fleets can deplete a population that takes centuries to recover before moving on to another, much like mining companies that traverse mountains and countries in search of new coal reserves after exhausting previous ones. 

On land, the extent of natural protected areas is measured by horizontal space across the landscape. In the ocean, however, effective fishery management requires additional vertical regulation — for example, setting limits on the maximum depth at which fishing is allowed (12).

This challenge is further complicated by the fact that deep-sea waters often lie in international zones, beyond national jurisdictions (14). From a scientific perspective, we must understand the life cycles of these remarkable species to inform governments about which ones can be fished and how to do so sustainably (15).

Let’s always keep in mind that the ocean is the heart of the Earth, and its health reflects the overall well-being of all living creatures.

Salvador Herrando-Pérez

References

1. Metcalfe NB, Monaghan, P 2003. Growth versus lifespan: perspectives from evolutionary ecology. Experimental Gerontology 38: 935-940
2. de Magalhães JP, Costa, J., Church, GM 2007. An analysis of the relationship between metabolism, developmental schedules, and longevity using phylogenetic independent contrasts. The Journals of Gerontology A 62: 149-160
3. García VB, Lucifora, LO, Myers, RA 2008. The importance of habitat and life history to extinction risk in sharks, skates, rays and chimaeras. Proceedings of the Royal Society B 275: 83-89
4. Zhang Y et al. 2024. Methodology advances in vertebrate age estimation. Animals 14: 343
5. Nielsen J et al. 2016. Eye lens radiocarbon reveals centuries of longevity in the Greenland shark (Somniosus microcephalus). Science 353: 702-704
6. Nielsen J et al. 2020. Assessing the reproductive biology of the Greenland shark (Somniosus microcephalus). PLoS One 15: e0238986
7. Orlov AM, Rusyaev, SM, Orlova, SY 2022. in Imperiled: The Encyclopedia of Conservation, DA DellaSala & MI Goldstein, Eds. (Elsevier), pp. 794-800
8. Herrando-Pérez S 2021. Bone need not remain an elephant in the room for radiocarbon dating. Royal Society Open Science 8: 201351
9. Hajdas I et al. 2021. Radiocarbon dating. Nature Reviews Methods Primers 1: 62
10. Gatto A et al. 2023. Deep-sea fisheries as resilient bioeconomic systems for food and nutrition security and sustainable development. Resources, Conservation and Recycling 197: 106907
11. Dulvy NK et al. 2021. Overfishing drives over one-third of all sharks and rays toward a global extinction crisis. Current Biology 31: 4773-4787
12. Finucci B et al. 2024. Fishing for oil and meat drives irreversible defaunation of deepwater sharks and rays. Science 383: 1135-1141
13. Norse EA et al. 2012. Sustainability of deep-sea fisheries. Marine Policy 36: 307-320
14. Oanta GA 2018. International organizations and deep-sea fisheries: current status and future prospects. Marine Policy 87: 51-59
15. Priede IG 2017. Deep-Sea Fishes: Biology, Diversity, Ecology and Fisheries (Cambridge University Press), pp. 504
16. Walter RP et al. 2017. Origins of the Greenland shark (Somniosus microcephalus): impacts of ice-olation and introgression. Ecology and Evolution 7: 8113-8125
17. Grant SM, Sullivan, R, Hedges, KJ 2018. Greenland shark (Somniosus microcephalus) feeding behavior on static fishing gear, effect of SMART (Selective Magnetic and Repellent-Treated) hook deterrent technology, and factors influencing entanglement in bottom longlines. PeerJ 6: e4751
18. Lydersen C, Fisk, AT, Kovacs, KM 2016. A review of Greenland shark (Somniosus microcephalus) studies in the Kongsfjorden area, Svalbard Norway. Polar Biology 39: 2169-2178
19. Fields RD 2007. The shark’s electric sense. Scientific American 297: 74-81

While we all inherit potentially harmful mutations from our parents, the effects of these mutations are often partially or completed masked if we possess two alternative variants of a gene — one from each parent. However, the children of closely related parents are more likely to inherit the same copies of harmful mutations. This is known as ‘inbreeding depression’. 

But inbreeding depression can happen in any species, with the risk increasing as populations become smaller. Because many species are rapidly declining in abundance and becoming isolated from one another predominantly due to habitat destruction, invasive species, and climate change, the chances of inbreeding are also increasing.

Not only are such populations more susceptible to random disturbances, they are also victim of reduced population growth rates arising from inbreeding depression. This produces what is generally known as the ‘extinction vortex‘ — the smaller your population, the more you inbreed and produce sub-optimal offspring, leading to even more population decline and eventually extinction.

One emergency intervention that can ‘rescue’ such inbred populations from extinction (at least in the short term) is to introduce unrelated individuals from other populations in an attempt to increase genetic diversity, and therefore, the rate of population growth. While somewhat controversial because some fear introducing diseases or eroding local-area specialisation (so-called ‘outbreeding depression’), the risk-benefit ratio of this ‘genetic rescue’ is now widely considered to be worth it. 

Australia has the worst record of mammal extinction of any nation, with 110 marsupial species (~ 65% of extant species) listed as threatened under the Environment Protection and Biodiversity Conservation Act 1999. Many of these species now only occur in small (< 1000 individuals) and isolated populations occupying < 10% of their former geographic ranges. The effect of inbreeding depression on extinction risk is now recognised as immediate threat to endangered marsupials (and other species), now making the prospect of genetic rescue a serious management consideration.

Nature plays dice

Populations in need of genetic rescue are not only at risk from overly close familial relations. The problems facing small populations include many interacting threats that arise due to chance events. The discrete and binary nature of birth and death (an individual is born, or not; is alive, or not) introduces randomness into the number of individuals in a population — we call this ‘demographic stochasticity’, and the number of different gene variants in the gene pool — we call this ‘genetic drift’.

Due to the strong influence of randomness in small populations, population size can suddenly collapse in the absence of further degradation of their habitat, and harmful mutations can accumulate before they are purged by natural selection. And to make matters worse, the mutual reinforcement of stochastic demographic and genetic processes that prevail in small populations creates a positive feedback loop (demo-genetic feedback) that heightens extinction risk as populations decline — a phenomenon referred to as the ‘extinction vortex’. 

While genetic rescue can immediately improve fitness, these gains might be short-lived if the risks of demographic instability and genetic drift remain, counteracting the benefits of genetic intervention, and drawing the population back into the extinction vortex. Maximising the effectiveness of genetic-rescue interventions therefore requires understanding ‘demo-genetic feedback’ and its role in shaping the outcomes of genetic rescue.

In our recent paper published in Evolutionary Applications (which we’re also pleased to report made the journal’s ‘Editor Pick‘), we highlight the relevance of demo-genetic feedback to genetic rescue and suggest an approach for building simulation models that can be applied to evaluate different scenarios of genetic rescue.

Our paper is aimed at conservation practitioners and applied ecologists seeking to do genetic rescue in populations of threatened species.

Theory into practice

Rapid advances in computational power, sequencing technology, and modelling software are facilitating the sophisticated simulation models built and validated with more data or based on more-realistic assumptions than was previously possible. These enable genetically explicit, individual-based models needed to make more accurate predictions of the dynamics of wildlife populations under proposed management interventions such as genetic rescue.

Open-source software capable of simulating the influence of demo-genetic feedback on the outcome of genetic rescue includes SLiM, quantiNemo, CDMetaPOP, RangeShifter, and HexSim (not an exhaustive list, but the main ones).

We compared the capabilities of these five software programs for incorporating demo-genetic feedback into simulations of genetic rescue. We contend that the implementation of genetic rescue in conservation should be guided by models that replicate the mutual reinforcement of demographic stochasticity, genetic drift, and inbreeding. Building such models is aimed at helping decision-makers to choose optimally among a set of competing potential interventions. 

To demonstrate our approach, we developed simulations of a heuristic model using SLiM to show how demo-genetic feedback influences extinction dynamics and the outcomes of genetic rescue of small populations.

We give the model details in the paper, but in summary, we calculated probability of extinction at an arbitrary time horizon of 1500 years in a no-intervention scenario and four alternative genetic-rescue scenarios. Genetic-rescue scenarios differed in two main ways: the number of individuals translocated into the target population (50 or 100 individuals), and the number of translocation events (once, or three times).

Compared to the no-intervention scenario, we found that genetic rescue decreased the probability of extinction by 3–9 %, with the largest effect in the scenario where 100 individuals were translocated three times.

The goal of the modelling exercise is not to predict specific outcomes of genetic rescue or proscribe details of its implementation. Rather, forward-projection models can be used to rank the relative success of virtual genetic-rescue scenarios and prioritise real-world strategies based on the relative probability of reducing inbreeding depression.

Our heuristic model was purposefully simple in terms of the variables we examined. Alternative scenarios facing decision-makers might differ for a range of variables, for example: population abundance of the target and source populations, or degree of genetic differentiation of the target and source populations, as well as many other potentially important things (some of which we list in our paper). 

Big data for hungry models

Rapid advances in sequencing technology and bioinformatics have increased the feasibility of obtaining high-resolution (and lower-cost) genomic data for threatened species. These genomic data, as well as the many studies based on microsatellite DNA, can be leveraged to develop and apply simulation models of genetic rescue.

We focussed on Australian threatened marsupials to demonstrate the types of genetic data that are available and suggest a set of modelling strategies and how data can be used to develop and apply them. Of the 21 species for which we found published genetic data, all had microsatellite data, 13 species had mitochondrial DNA (mtDNA), 9 species had genome-wide single-nucleotide polymorphisms (SNPs), and 2 species had whole-genome sequences — koala (Phascolarctos cinereus) and Tasmanian devil (Sarcophilus harrisii). There was also one species in which ancient DNA had been sequenced.

Most species (15) were represented by one or two types of sequence data, while fewer (6) had three or more data types. Species with the most genetic data included woylie (Bettongia penicillata), northern quoll (Dasyurus hallucatus), western barred bandicoot (Perameles bougainville), Leadbeater’s possum (Gymnobelideus leadbeateri), koala, and Tasmanian devil.

Genetic data can be used at different stages of model development and can be applied at one or all stages of model building, calibration, and/or validation. Most populations needing genetic rescue are unlikely to have the necessary data to estimate all mechanistic parameters, such as mutation rates, so estimates can be used from (in order of preference) other populations of the same species, related species, or unrelated species to fill the gap.

For example, a mutation rate for koalas has recently been estimated, which should supersede estimates for Drosophila or humans if simulating genetic rescue of a marsupial population. Parameters for which there are no data can be estimated from allometric relationships, or based on other reasonable assumptions informed by theoretical predictions, with cautious interpretation of model outputs guided by global sensitivity analyses to quantify and highlight uncertainty.

More commonly available data for target populations include sequence-based estimates of genetic diversity and inbreeding (e.g., allelic richness, heterozygosity/homozygosity, inbreeding or relatedness coefficients), and less commonly, genetic load. Such information could be used to calibrate (and ideally, validate) the mechanistic parameters in the model that give rise to virtual sequence variation.

Known as ‘pattern-oriented modelling’, this approach is widely used to calibrate and validate individual-based models. Once the genetic mechanisms that give rise to virtual sequence variation are calibrated, users could then run simulations of genetic rescue and compare them based on how much they affect virtual genetic diversity, inbreeding, or genetic load.

Another strategy involves simulating genetic rescue of populations in which allele frequencies have been initialised from sequence (marker) data (‘empirical alleles’). Here, sequence data from the target population can be imported into the simulated populations at a user-defined time based on when the data were collected.

Why it’s important

We are in the midst of an extinction crisis that is no longer solely a moral challenge to humanity, but also an existential one. The plants, animals and other organisms on Earth today are a living repository of millions of years of evolution and diversification — encoded genetically — that has produced the living forms and functions that underpin the integrity of the biosphere.

Due to global declines in species abundance and distribution, the loss of genetic and functional diversity already far exceed safe limits within which humanity can continue to develop and thrive for generations to come. In an attempt to stem the bleeding, so to speak, genetic rescue is not only necessary, but must be applied efficiently and effectively.

We simply do not have the time (or money) to waste. 

Julian Beaman

I regularly hear stories from editors handling my papers, as well as accounts from colleagues, about the ridiculous number of review requests they send with no response. It isn’t uncommon to hear that editors ask more than 50 people for a review (yes, you read that correctly), to no avail. Even when the submitting authors provide a list of potential reviewers, it doesn’t seem to help.

The ensuing delays in time to publication are really starting to hurt people, and the most common victims are early career researchers needing to build up their publication track records to secure grants and jobs. And the underhanded, dickhead tactic to reset the submission clock by calling a ‘major review’ a ‘rejection with opportunity to resubmit’ doesn’t fucking fool anyone. The ‘average time from submission to publication’ claimed by most journals is a boldface lie because of their surreptitious manipulation of handling statistics.

The most obese pachyderm in the room is, of course, the extortionary prices (and it is nothing short of extortion) charged for publishing in most academic journals these days. For example, I had to spend more than AU$17,000.00 to publish a single open-access paper in Nature Geoscience last year. That was just for one paper. Never again.

Anyone with even a vestigial understanding of economics feels utterly exploited when asked to review a paper for nothing. As far as I am aware, there isn’t a reputable journal out there that pays for peer reviews. As a whole, academics are up-to-fucking-here with this arrangement, so it should come as no surprise that editors are struggling to find reviewers.

The fact too that the number of submissions keeps rising because of our institutional obsession with publication frequency means that we are being asked more and more to do a lot of work for free.

How can we possibly reverse this trend and get back to a more realistic and fair model of publication?

There is no shortage of proposed alternatives, but I fear most of these will never come to pass, mainly because journals have us firmly by the short and curlies.

Why? The reason we can’t seem to break out of the vice is because we are compelled to publish in the highest-impact journals as much as possible, to the exclusion of almost all else. So, with such a huge demand to get published, the journals can charge whatever they want because there is a guaranteed supply of punters willing to fork over the cash. Capitalist free-market dynamics 101: high demand = insane prices.

Something has to give, and I’m not sure what that will look like. In the meantime, however, there are a few things I can suggest journals could do to alleviate the challenge of finding reviewers. I also provide a list of things individual authors can do to reduce the probability that reviewer ‘shortages’ don’t bite too hard.

What journals can do

1. Drop your prices

The most important, yet least likely change needed is for journals to stop charging so much to publish papers in their journals. The now common practice is a vile and repugnant act of pure extortion. All major scientific publishing companies are publicly listed profit monsters that don’t give a shit about academic quality or fair treatment — they care only how much profit they make. I have no illusion that my little blog post is going to change any company policies, but there are things we can do to hit these profiteering bastards where it hurts (see below).

2. Pay reviewers

Another most likely unrealistic pipe dream is that journals pay their reviewers. There are many proposed models for how such a system could work that would be fair, maintain some profits (cringe), and ensure objectivity. But until someone actually tries the approach, there’s no way the reviewer crisis will suddenly disappear.

3. Quicker turnaround

Do not take weeks, or sometimes even months, to make a decision not to send a manuscript to review. If you have no intention of reviewing a manuscript, tell the authors immediately, and don’t just string them along. This decision should be made in days (ideally, less than 24 hours) following submission.

4. Actually edit

This might sound intuitive, but apparently it’s not obvious to many editors: editors must actually edit. ‘Editing’ does not mean collecting reviews and defaulting to the decision of the worst reviewer. Editing means the editor has to read the paper, weigh up the diverse viewpoints, and decide what are the most important components required to get the manuscript up to a minimum standard imposed by the journal. Having already made the decision to review the paper, the editor’s job is to do everything possible to find ways to accept the manuscript, not dump it.

5. Pay editors

Most editors do the onerous job of editing hundreds of manuscripts for no monetary recompense whatsoever (just like the reviewers they’re struggling to commission). The expression ‘you get what you pay for’ is most apt here. See previous recommendation.

6. Kill the transfer insult

Again, this is probably a pipe dream, but do not suggest I transfer my manuscript to a lower-impact, pay-only journal in your profiteering ‘family of journals’. It’s just insulting.

7. Stop lying about handling times

Stop the bullshit handling-time manipulation. The time from submission to publication is the time from first submission until publication, full stop.

8. Publish immediately

Once a paper is accepted, publish the damn thing immediately, not in 2, 6, or 16 weeks. It’s an insult to authors that they have to wait not only for the lengthy review, but also a completely unjustified delay after acceptance. I don’t give a flying fuck if the paper isn’t in its final form — at least publish the accepted version with a working digital object identifier (DOI) as soon as you send us that lovely e-mail starting with “It is our pleasure to inform you that your paper … has been accepted for publication in … “.

9. Accept pre-prints

I know there aren’t many journals left who refuse to accept manuscripts if there is an accompanying pre-print, but there are some (in fact, I only recently had a paper rejected at the doorstep because of a journal’s anachronistic, fuckwit policy not to play the pre-print game). To you, I say, ‘just fuck off’. Not only are you bucking the widely accepted trend, you are deliberately making it difficult for those papers to see the publication light of day (even in non-peer-reviewed form).

What submitting authors can do

You probably think that as a submitting author, you have almost no power to change the system. I agree. But you do at least wield a little influence.

10. Demand regular updates

Try to avoid the hopelessness and impotence about not knowing why a journal is taking so long to move your manuscript from ‘under consideration’ to some other vague, but at least progressive, next stage. It is absolutely within your rights to demand editors provide regular updates on your manuscript, and the reasons for any undue delays. If the reason is ‘we can’t find reviewers’ as is now becoming a stock response, offer to help (see next items).

11. Provide a long, well-supported reviewer shopping list

I do this now almost for every submission as a matter of course. Whether it’s via a journal’s online submission system, in my cover letter, or both, I now provide a long list of potential reviewers that I deem suitable to review my work. But don’t abuse this opportunity by just recommending your mates (editors can see right through that puerile ruse at just a glance). Only choose people who are independent (with whom you have never, or least not within the last 5 years, published), properly qualified (don’t suggest your sister-in-law, unless she’s the uncontested top expert in the field, and even then, reconsider), and not from your same institution, for obvious reasons.

I’m also tending to go a step farther now by contacting potential reviewers beforehand and warning them that I’d like to put forward their names, and “pretty please would you mind terribly if you could take some time to review my paper, thank-you-from-the-bottom-of-my-heart?”

Finally, once you accumulate your list of names, make a backup ‘plan B’ list of other people.

12. Avoid the worst journals

If a journal has a history of being a bad player, then avoid submitting to them. This could be journals that charge the most, journals who are notoriously slow, journals known to employ ‘gatekeeper‘ editors, journals from societies that make stupid decisions (e.g., journals of the Royal Society, who refuses to remove a neonazi from its fellowship). The latter example notwithstanding, many are suggesting that society journals generally offer the best combination of attributes.

13. Don’t play their bait-and-switch game

See item 6 above. If a journal helpfully suggests transferring your article to one of its pay-only sister journals, tell them politely to fuck right off. This is a blatant attempt to suck cash out of you.

14. Appeal

If the journal’s ‘final’ decision is ‘no, bugger off’, don’t just take it sitting down (read more on dealing with rejection). I have written an entire post on this subject, but in brief, the higher the journal’s reputation, the better the chance a well-reasoned appeal will be successful.

15. Be historically honest

If you have had a bad experience during a review process, sometimes it’s not worth the appeal. Instead, submit elsewhere, but do not fear explaining to the new journal’s editor a little about your paper’s history and why you think you were treated unfairly (e.g., one reviewer was horrible, and the editor didn’t actually edit). Being honest about your paper’s history, warts and all, can often provide needed context for a new editor instead of starting from scratch.

Be warned though — if it wasn’t clear to someone at first submission why your article was sound, the onus on you is to submit a better version, or another reviewer is likely to raise the same issues. What’s that saying? — If you keep doing the same thing over and over expecting a different result, then you are …

16. Refuse to enable the worst offenders

In addition to avoiding submissions to evil journals, you can also refuse to review for them when requested (I know, this will only exacerbate the reviewer crisis, but something has to give). I have personally boycotted reviewing for many journals now because of their behaviour, and I’ve made my reasons for refusal clear when responding to their requests, so they get the message that their behaviour (or at least, the behaviour of their parent company) is unacceptable.

You can also wield your power as an academic by refusing to cite papers in your own work, no matter how good or on-point they are, if they are published in badly behaving journals. There are ALWAYS alternative papers to cite. Journal reputations are built on citations, which leads some to abuse that reputation by charging outlandish fees. Hit them where it hurts.

17. Always pre-print

See item nine above. Make it a habit to publish pre-prints before submitting the manuscript itself to a journal. At least the paper is out there and can be cited (with a DOI). Preprints have other advantages too.

There is no silver bullet to this mess, but I encourage academics to stand up for themselves and not just bow down to the bloated publishing gods every time they make another stupid demand.

But I might be jaded.

CJA Bradshaw

Throughout the year, we wear different clothing to protect ourselves from the cold or heat and for aesthetic reasons depending on the occasion. Likewise, many animals change the colour, thickness and structure of their fur and feathers in tune with the seasons.

However, as the climate changes, springs arrive earlier, winters are delayed, and the frequency and intensity of precipitation have become highly variable. All of this makes it harder for species to adjust their wardrobe to temperature changes (1).

In this context, body colour is a critical factor for birds and mammals that undergo an annual moult (2). In 21 species from the cold latitudes of the Northern Hemisphere, some individuals are brown in summer, but turn white in winter, while others remain brown year round (3). This phenomenon includes weasels, rodents, ptarmigans, foxes, rabbits and hares.

If these vertebrates moult to white when there is no snow, they stick out like dog’s bollocks against forest habitats dominated by greens and browns (leaves, soil, tree trunks) (4). In turn, if snowfall decreases due to climate change, predators are expected to capture non-camouflaged prey more easily, thereby reducing prey population abundance.

White and brown coats

Joanie Kennah and collaborators studied the combined effect of coat colour and ambient temperature on the snowshoe hare (Lepus americanus) in the Yukon (Canada) (5). This species inhabits temperate and boreal forests of North America, where the Canada lynx (Lynx canadensis) is its primary predator (6). Hares change their coats during Spring and Autumn. This moult is genetically regulated (7) and synchronised with the photoperiod (hours of daylight) and the duration of the snow-covered landscape (8).

Using a capture-recapture method, Kennah monitored the colour (white or brown) of 347 adult hares equipped with radio-transmitter collars over three consecutive autumns (Sep–Dec) and four springs (Mar–May) from 2015 to 2018. In total, 75 hares died during the study, and 14% of the recaptures were white animals in a snowless landscape.

Contrary to expectations, these white, non-camouflaged hares had higher survival rates than camouflaged individuals in autumn. This relationship was driven by their feeding habits. The studied populations spent 11–12 hours/day feeding. As temperatures dropped in autumn, white hares spent less time feeding (on grasses and shrubs) and more time being vigilant in a snowless habitat (9). This seems to have reduced attacks by their natural predators and compensated for their higher visibility (5). Kennah did not observe these relationships in the spring.

Camouflage or thermoregulation

Modifying body colour for camouflage against changing backgrounds is a logical prediction (10), but it also affects thermoregulation. Dark colours absorb more radiation than light colours, which is why people tend to wear light (and cool) clothing in summer and dark (and warm) clothing in winter.

However, the shape and composition of a feather or hair confer different optical and insulation properties. For example, the amount of heat transmitted from the air to the skin by black and white plumage converges as wind speed increases (11, 12). The winter fur of hares — whether white or brown — is longer and denser than their summer fur, allowing them to spend less energy (and require less food) to maintain body temperature in the cold (13).

Over the course of the year, a coat colour that contrasts with the habitat increases hare mortality (14, 15). However, for individuals that moult from brown to white and live in extremely cold environments, survival should be highest if they turn white when there is no snow, but when the autumn cold has already set in (5), and then take advantage of the white camouflage to evade predators during the snowy conditions of winter (15).

With both added advantages, these mammals might be less vulnerable to the progressively shorter snow seasons widely documented in the Northern Hemisphere. However, the underlying issue is that the reduction in snow (both in amount and duration) appears to be causing hares to become gradually less white, as the value of their winter white camouflage diminishes (15).

Genes and environmental changes

With 32 extant species [see short videos here and here], the evolutionary history of hares includes frequent hybridisation events between species (16). All species that moult from brown to white have interbred, sharing genetic variation related to coat-colour change and thermoregulation. This genetic diversity is essential for adapting to seasonal ecosystems.

The so-called agouti gene promotes lighter colours and inhibits pigment production in mammals. This gene drives the seasonal colour variation exhibited by snowshoe hares across their range (17). To keep these evolutionary processes active, the genetic diversity regulating colour must be preserved within each species (18).

Unfortunately, the global network of protected areas fails to capture the genetic diversity associated with the colouration of vertebrates that turn white in winter (3). Any expansion of protected areas should consider including populations of different colours as a straightforward criterion to preserve species’ adaptability to a changing climate.

Salvador Herrando-Pérez and Reagan Early

References

1. Visser ME & Gienapp, P (2019). Evolutionary and demographic consequences of phenological mismatches. Nature Ecology & Evolution 3: 879-885
2. Zimova M et al. (2018). Function and underlying mechanisms of seasonal colour moulting in mammals and birds: what keeps them changing in a warming world? Biological Reviews 93: 1478-1498
3. Mills LS et al. (2018). Winter colour polymorphisms identify global hot spots for evolutionary rescue from climate change. Science 359: 1033-1036
4. Otte PJ et al. (2024). Snow cover-related camouflage mismatch increases detection by predators. Journal of Experimental Zoology A 341: 327-337
5. Kennah JL et al. (2023). Coat colour mismatch improves survival of a keystone boreal herbivore: energetic advantages exceed lost camouflage. Ecology 104: e3882
6. Krebs CJ, Boonstra, R & Boutin, S (2018). Using experimentation to understand the 10-year snowshoe hare cycle in the boreal forest of North America. Journal of Animal Ecology 87: 87-100
7. Ferreira MS et al. (2017). The transcriptional landscape of seasonal coat colour moult in the snowshoe hare. Molecular Ecology26: 4173-4185
8. Mills LS et al. (2013). Camouflage mismatch in seasonal coat colour due to decreased snow duration. Proceedings of the National Academy of Sciences of the USA 110: 7360-7365
9. Shiratsuru S & Pauli, JN (2024). Food-safety trade-offs drive dynamic behavioural antipredator responses among snowshoe hares. Journal of Animal Ecology 93: 1710-1721
10. Duarte RC, Flores, AAV & Stevens, M (2017). Camouflage through colour change: mechanisms, adaptive value and ecological significance. Philosophical Transactions of the Royal Society B 372: 20160342
11. Walsberg GE, Campbell, GS & King, JR (1978). Animal coat colour and radiative heat gain: a re-evaluation. Journal of Comparative Physiology 126: 211-222
12. Rogalla S, Shawkey, MD & D’Alba, L (2022). Thermal effects of plumage colouration. Ibis 164: 933-948
13. Sheriff MJ et al. (2009). Seasonal metabolic acclimatization in a northern population of free-ranging snowshoe hares, Lepus americanus. Journal of Mammalogy 90: 761-767
14. Zimova M, Mills, LS & Nowak, JJ (2016). High fitness costs of climate change-induced camouflage mismatch. Ecology Letters 19: 299-307
15. Oli MK et al. (2023). Does coat colour influence survival? A test in a cyclic population of snowshoe hares. Proceedings of the Royal Society B 290: 20221421
16. Ferreira MS et al. (2020). The legacy of recurrent introgression during the radiation of hares. Systematic Biology 70: 593-607
17. Jones MR et al. (2018). Adaptive introgression underlies polymorphic seasonal camouflage in snowshoe hares. Science 360: 1355-1358
18. Jamie GA & Meier, JI (2020). The persistence of polymorphisms across species radiations. Trends in Ecology & Evolution 35: 795-808
19. Grange WB (1932). The pelages and colour changes of the snowshoe hare, Lepus americanus phaeonotus, Allen. Journal of Mammalogy 13: 99-116
20. Jones MR et al. (2020). Convergent evolution of seasonal camouflage in response to reduced snow cover across the snowshoe hare range. Evolution 74: 2033-2045
21. Boonstra R et al. (2016). Why do the boreal forest ecosystems of Northwestern Europe differ from those of Western North America? BioScience 66: 722-734

Corey J. A. Bradshaw, Flinders University; Clelia Mulà, The University of Western Australia, and Giovanni Strona, University of Helsinki

Coral reefs are much more than just a pretty place to visit. They are among the world’s richest ecosystems, hosting about a third of all marine species.

These reefs also directly benefit more than a billion people, providing livelihoods and food security, as well as protection from storms and coastal erosion.

Without coral reefs, the world would be a much poorer place. So when corals die or become damaged, many people try to restore them. But the enormity of the task is growing as the climate keeps warming.

In our new research, we examined the full extent of existing coral restoration projects worldwide. We looked at what drives their success or failure, and how much it would actually cost to restore what’s already been lost. Restoring the reefs we’ve already lost around the world could cost up to A$26 trillion.

Global losses

Sadly, coral reefs are suffering all over the world. Global warming and marine heatwaves are the main culprits. But overfishing and pollution make matters worse.

When sea temperatures climb above the seasonal average for sustained periods, corals can become bleached. They lose colour as they expel their symbiotic algae when stressed, revealing the white skeleton underneath. Severe bleaching can kill coral.

Coral bleaching and mass coral deaths are now commonplace. Last month, a massive warm-water plume bleached large areas of Ningaloo Reef on Australia’s northwest coast just as large sections of the northern Great Barrier Reef were bleaching on the northeast coast.

Since early 2023, mass coral bleaching has occurred in throughout the tropics and parts of the Indian Ocean.

Over the past 40 years, the extent of coral reefs has halved. As climate change continues, bleaching events and coral deaths will become more common. More than 90% of coral reefs are at risk of long-term degradation by the end of the century.

Direct intervention

Coral reef restoration can take many forms, including removing coral-eating species such as parrot fish, transferring coral spawn, or even manipulating the local community of microbes to improve coral survival.

But by far the most common type of restoration is “coral gardening”, where coral fragments grown in nurseries are transplanted back to the reef.

The problem is scale. Coral restoration can only be done successfully at a small scale. Most projects only operate over several hundred or a few thousand square metres. Compare that with nearly 12,000 square km of loss and degradation between 2009 and 2018. Restoration projects come nowhere near the scale needed to offset losses from climate change and other threats.

Sky-high costs

Coral restoration is expensive, ranging from around $10,000 to $226 million per hectare. The wide range reflects the variable costs of different techniques used, ease of access, and cost of labour. For example, coral gardening (coral fragments grown in nurseries transplanted back to the reef) is relatively cheap (median cost $558,000 per hectare) compared with seeding coral larvae (median $830,000 per hectare). Building artificial reefs can cost up to $226 million per hectare.

We estimated it would cost more than $1.6 billion to restore just 10% of degraded coral areas globally. This is using the lowest cost per hectare and assuming all restoration projects are successful.

Even our conservative estimate is four times more than the total investment in coral restoration over the past decade ($410 million).

But it’s reasonable to use the highest cost per hectare, given high failure rates, the need to use several techniques at the same site, and the great expense of working on remote reefs. Restoring 10% of degraded coral areas globally, at $226 million a hectare, would cost more than $26 trillion – almost ten times Australia’s annual GDP.

It is therefore financially impossible to tackle the ongoing loss of coral reefs with restoration, even if local projects can still provide some benefits.

Location, location, location

Our research also looked at what drives the choice of restoration sites. We found it depends mostly on how close a reef is to human settlements.

By itself, this isn’t necessarily a bad thing. But we also found restoration actions were more likely to occur in reefs already degraded by human activity and with fewer coral species.

This means we’re not necessarily targeting sites where restoration is most likely to succeed, or of greatest ecological importance.

Another limitation is coral gardening normally involves only a few coral species – the easiest to rear and transplant. While this can still increase coral cover, it does not restore coral diversity to the extent necessary for healthy, resilient ecosystems.

Measuring ‘success’

Another sad reality is that more than a third of all coral restoration efforts fail. The reasons why can include poor planning, unproven technologies, insufficient monitoring, and subsequent heatwaves.

Unfortunately, there’s no standard way to collect data or report on restoration projects. This makes it difficult – or impossible – to identify conditions leading to success, and reduces the pace of improvement.

Succeed now, fail later

Most coral transplants are monitored for less than 18 months. Even if they survive that period, there’s no guarantee they will last longer. The long-term success rate is unknown.

When we examined the likelihood of extreme heat events immediately following restoration and in coming decades, we found most restored sites had already experienced severe bleaching shortly after restoration. It will be difficult to find locations that will be spared from future global warming.

No substitute for climate action

Coral restoration has the potential to be a valuable tool in certain circumstances: when it promotes community engagement and addresses local needs. But it is not yet – and might never be – feasible to scale up sufficiently to have meaningful long-term positive effects on coral reef ecosystems.

This reality check should stimulate constructive debate about when and where restoration is worthwhile. Without stemming the pace and magnitude of climate change, we have little power to save coral reefs from massive losses over the coming century and beyond.

Other conservation approaches such as establishing, maintaining and enforcing marine protected areas, and improving water quality, could improve the chance a coral restoration project will work. These efforts could also support local human communities with incentives for conservation.

Reinforcing complementary strategies could therefore bolster ecosystem resilience, extending the reach and success of coral restoration projects.

Corey J. A. Bradshaw, Matthew Flinders Professor of Global Ecology and Node Leader in the ARC Centre of Excellence for Indigenous and Environmental Histories and Futures, Flinders University; Clelia Mulà, PhD student in Marine Ecology, The University of Western Australia, and Giovanni Strona, Doctoral program supervisor, University of Helsinki

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Urban development has created a network of illuminated infrastructure that allows our society to function day and night without interruption. It is no surprise that with so much artificial light, we increasingly have to move farther away from towns and cities to see a sky full of stars.

Light pollution poses a challenge for nocturnal species that have adapted to living in the dimness of night (1, 2) — see documentaries about the impacts of artificial light on wildlife and insects, and a related scientific talk. This problem might be one of the causes of the global decline in insects (3, 4), in turn negatively affecting their role in maintaining agricultural systems through pest control, pollination, and soil quality (5). These concepts are featured by the documentaries The Insect Apocalypse and The Great Death of Insects.

When flying, nocturnal insects orient their backs toward the sky, using the light of the moon and stars as a reference (6) (explained here and here). However, when they encounter artificial lights, they can no longer distinguish up from down, and so they can become disoriented, flying erratically, like a moth circling a streetlight.

It is estimated that a third of the insects attracted to artificial light die from collisions, burn injuries, exhaustion, and/or predation (7). In the tropics, finding countless dead insects at the base of urban lights is a common scene. Equally important is that artificial light also hinders migration, foraging, and the search for mates in many nocturnal species (1, 8, 9).

Nocturnal jewels

Camacho and collaborators evaluated the effect of artificial lighting at night on the Chocó golden scarab (Chrysina argenteola) (10). This species inhabits the tropical rainforests of the Western Andes from Ecuador to Colombia, and is a member of the group known as ‘jewel scarabs‘ due to their metallic body coloration (11). Because of its nocturnal habits and the larvae’s dependence on wood for food (12), the golden scarab has been increasingly affected by the loss of native forest in combination with light pollution from rural and urban expansion.

In the last two centuries approximately two-thirds of the native forest, which serve as habitat for this scarab, have been lost in Ecuador. However, the conservation status of the species is poorly understood, and little is known of its natural history while its populations are difficult to monitor using established entomological survey methods.

As an alternative to studying the golden scarab directly, Camacho relied on local ecological knowledge (13). In 2014, he did interviews with 395 locals, gathering 362 reports of golden scarab sightings, including their latitude and longitude. Most sightings consisted of individuals in flight and spanned a region encompassing 45 towns. Ninety-six per cent of sightings occurred in cultivated or urban areas, with 78% involving individuals flying around artificial lights. Comacho and his team cross-referenced the geographical coordinates of each sighting with satellite images (also compiled in 2014) to assess forest cover and the intensity of artificial light at each scarab sighting.

Camacho’s team found that in areas with more forest cover, sightings of the beetles were more likely in places with higher artificial light. However, in regions with less forest, sightings were more likely in dimly lit areas. The probability of encountering the beetles was highest in forests that were both abundant and more fragmented by illuminated roads and pathways (10).

Dazzling aerial landscapes

Over 80% of humanity (99% in Europe and the USA) lives under skies polluted by artificial light (14) — see animation of the world atlas of artificial night-sky brightness. Its effects on wildlife interact with other impacts through climate change, noise pollution, and habitat loss (9).

Such is the case for the Chocó golden scarab. Understanding their response to light pollution requires considering the state of the forest. In healthy forests with abundant resources for many individuals, reproduction can offset the mortality caused by light pollution. However, in areas where the forest is more degraded, the losses are not replenished, putting the beetle at high risk of local extinction. In other words, Camacho’s team’s findings (10) do not support the hypothesis that insects are more frequently trapped by artificial lights near mature forests. Rather, these arthropods are more abundant in such areas, making it more likely to observe them disoriented there compared to degraded forests or urban areas, where their populations have already waned due to low habitat quality.

The aerial zone immediately above the ground is part of the living space for species that fly. The study of this zone has given birth to the discipline of aeroecology (15) — a paradigm for cross-disciplinary research through biology, chemistry, ecology, genetics and physics.

If we perceive the land-air interface as a true ecosystem, artificial light (as much as airplane routes or the physical presence of buildings) fragments the aerial habitat of flying species at night. It is as though the animals were flying over a ‘minefield’ of urban lights that intercept them (1).

This fragmentation of the air mirrors how the construction of roads or the clearing of forests fragments the habitat of non-flying animals. Within that rationale, there is an urgent need to assess how environmental policies aimed at preventing fragmentation of terrestrial habitats can also be applied to aerial habitats and to what extent innovative actions are required when light pollution is the dominant mechanism causing habitat fragmentation (8).

Salvador Herrando-Pérez and Luis F. Camacho

References

1. Gaston KJ et al. 2021. Pervasiveness of biological impacts of artificial light at night. Integrative and Comparative Biology 61: 1098-1110
2. Kehoe R, Sanders, D & van Veen, FJF. 2022. Towards a mechanistic understanding of the effects of artificial light at night on insect populations and communities. Current Opinion in Insect Science 53: 100950
3. Owens ACS et al. 2020. Light pollution is a driver of insect declines. Biological Conservation 241: 108259
4. Kalinkat G et al. 2021. Assessing long-term effects of artificial light at night on insects: what is missing and how to get there. Insect Conservation and Diversity 14: 260-270
5. Grubisic M et al. 2018. Insect declines and agroecosystems: does light pollution matter? Annals of Applied Biology 173: 180-189
6. Fabian ST et al. 2024. Why flying insects gather at artificial light. Nature Communications 15: 689
7. Eisenbeis G & Hänel, A, 2009. in Ecology of Cities and Towns: A Comparative Approach, MJ McDonnell, AK Hahs & JH Breuste, Eds. (Cambridge University Press), pp. 243-263
8. Davy CM, Ford, AT & Fraser, KC. 2017. Aeroconservation for the fragmented skies. Conservation Letters 10: 773-780
9. Desouhant E et al. 2019. Mechanistic, ecological, and evolutionary consequences of artificial light at night for insects: review and prospective. Entomologia Experimentalis et Applicata 167: 37-58
10. Camacho LF, Barragán, G & Espinosa, S. 2021. Local ecological knowledge reveals combined landscape effects of light pollution, habitat loss, and fragmentation on insect populations. Biological Conservation 262: 109311
11. Thomas DB, Seago, A & Robacker, DC. 2007. Reflections on golden scarabs. American Entomologist 53: 224-230
12. Hawks DC. 2002. Jewel scarabs. Museum Notes (University of Nebraska State Museum) 112: 1-4
13. Joa B, Winkel, G & Primmer, E. 2018. The unknown known – a review of local ecological knowledge in relation to forest biodiversity conservation. Land Use Policy 79: 520-530
14. Falchi F et al. 2016. The new world atlas of artificial night sky brightness. Science Advances 2: e1600377
15. Kunz TH et al. 2008. Aeroecology: probing and modeling the aerosphere. Integrative and Comparative Biology 48: 1-11
16. Fernández del Río L, Arwin, H & Järrendahl, K. 2016. Polarizing properties and structure of the cuticle of scarab beetles from the Chrysina genus. Physical Review E 94: 012409
17. Kjernsmo K et al. 2020. Iridescence as camouflage. Current Biology 30: 551-555
18. Makarova AA et al. 2022. Scaling of the sense organs of insects. 1. Introduction. Compound eyes. Entomological Review 102: 161-181
19. Warrant EJ. 2017. The remarkable visual capacities of nocturnal insects: vision at the limits with small eyes and tiny brains. Philosophical Transactions of the Royal Society B 372: 20160063

Corey J. A. Bradshaw, Flinders University

US President Donald Trump’s latest war on the climate includes withdrawing support for any research that mentions the word.

He has also launched a purge on government websites hosting climate data, in an apparent attempt to make the evidence disappear.

Yes, it’s bad, especially for US-based scientists. It also affects scientists in Australia and the rest of the world. But there are ways to get around the problem. There might even be a silver lining to this dark cloud.

Trump cannot stop global climate action, although he might slow it. Nor can he hide the truth by restricting access to data. Climate research will continue despite Trump’s best efforts to hamstring scientists and research institutions.

No strength in ignorance

Last year was the warmest on record, a fact that yet again confirms our worst-case predictions. The world has already surpassed the (arbitrary) 1.5°C threshold increase relative to pre-industrial temperatures — a threshold that only a few years ago we didn’t think we would cross until 2030 at the earliest.

We’re now on track to be living in a world that’s 3°C hotter or more by the end of the century.

This is despite more than 30 years of global commitments that have largely failed to bend the warming trend.

But ignoring climate change won’t make it go away. Like the Ministry of Truth in George Orwell’s classic dystopian novel, 1984, Trump seems to believe “ignorance is strength”. He’s trying to erase facts about the climate crisis, perhaps to keep people ignorant and subdued.

What this means for Australian climate science

Many Australian scientists (including me) collaborate regularly with US colleagues, share funding, and publish results together. Knowledge sharing and open-access data are the foundation of advances in science, so Trump’s assault will inevitably slow progress here.

For example, Australian and US scientists regularly collaborate in big-ticket research and policy development related to climate change, such as the Intergovernmental Panel on Climate Change’s Physical Science Basis reports. But even with fewer US scientists in the mix, the research and reporting will continue.

Students involved in climate research will also be negatively affected, with fewer opportunities for scholarships and exchanges between our two countries.

It’s worth remembering the US is not the only country with global data sets that measure the magnitude of the climate calamity. Australia’s own Bureau of Meteorology, CSIRO, Terrestrial Ecosystem Research Network, Integrated Marine Observing System, and Geoscience Australia are just some of examples of Commonwealth government-backed data custodians that are immune to the US purge.

Other reputable climate-data repositories around the world include the European Union’s Climate Data Store, the University of East Anglia’s Climate Research Unit, the Netherlands Meteorological Institute’s Climate Explorer, and the independent WorldClim, to name a few.

While restricting access to US-based websites is inconvenient, we can readily get around the problem. Many of my colleagues have also been downloading data prior to the purge mandate to maintain access.

Consequences for the US

Over the past month I have been inundated with horror stories from many US-based colleagues in academia and the public service, who have lost their jobs and/or research funding. In addition to these very real personal tragedies, the bigger picture is even bleaker.

The loss of scientific and technical expertise these mass sackings entail weakens the capability of the US workforce to discover and develop solutions to climate change. Just when we need good scientific and engineering innovations more than ever, a massive capacity is being erased before our eyes.

Trump’s fear and hatred of all things “climate” also foreshadows even more greenhouse gas emissions from the US. He has issued various strong-arm orders to “unleash American energy” by fast-tracking fossil-fuel exploitation, blocking offshore wind-power development, and revoking targets for electric vehicles, for example.

More emissions mean more climate change, especially when you’re already one of the biggest contributors to the global problem. The US is the second-highest greenhouse emitter in the world, behind only China.

Trump claims his actions will improve economic prosperity. The reality is they will instead retard the green manufacturing boom. Curtailing anything with even the faintest whiff of “climate” will in fact reduce economic prosperity and increase unemployment.

Costs to the rest of the world

On his first day as president, Trump withdrew the US from the Paris climate agreement. This effectively removes his country from all binding limits on actions that contribute to climate change.

Weakening international treaties is a two-edged sword, because it not only lets the US off the leash, it also potentially discourages other nations from acting responsibly. Analogous to the “unresponsive bystander effect”, many nations may now be more hesitant to commit to reductions because one of the biggest emitters refuses to do anything about it.

Trump has also slashed US international aid, which will slow climate action in countries that need the most assistance.

Overall, faster rates of warming will inevitably put more strain on natural resources and agricultural production. This could increase the probability of international warfare over water, food and other essential natural resources. Because autocratic countries cope worse with food shortages than democratic ones, climate emergencies will penalise nations led by despots more heavily.

Finding a silver lining

Trump’s foolhardy anti-climate campaign is enough to make many people despair. But there are a few faint glimmers of hope on the horizon.

As the US shirks its domestic and international responsibilities, other countries might resolve to do more. Not relying on the US could force capacity-building elsewhere. Some even suggest without the US at the table slowing progress, stronger climate action might result.

Americans have their own daunting fight on their hands. But the rest of the world will have to take up the slack if we have any chance of limiting the health, wealth, equality, human rights and biodiversity calamities now unfolding because of climate change.

Corey J. A. Bradshaw, Matthew Flinders Professor of Global Ecology and Node Leader in the ARC Centre of Excellence for Indigenous and Environmental Histories and Futures, Flinders University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

This is a fixed-term position for up to 3 years, and we are especially targeting Indigenous candidates.

The successful candidate will use existing code and develop new approaches to analyse complex data derived from lake, lagoon, river, and wetland cores measuring various aspects of dated vegetation composition, fire regime, and climate fluctuation. Additionally, the successful candidate will design simulation models to evaluate how different proxies behave under various environmental conditions, aiding in the interpretation of outputs from time-series models.

As a position under CIEHF, the position requires co-designing projects with Indigenous Partner Organisations, as well as extensive travel to the other Nodes within CIEHF to collaborate with palaeo-ecologists, climatologists, archaeologists, and other relevant specialists.

For more information and details on the application process, visit this link.

Applications close 22:00 16 March 2025.

Good luck!

Before the internet irrupted, I was living in Spain and frequently travelled from my hometown to universities in Valencia and Barcelona to access scientific journals. Back then, these journals were only available in print or on compact discs. Today, I can do the same thing from home with an internet connection.

 The emergence of public internet since the 1990s has globalised information and represents a data source for many areas of science (1, 2). When applied to nature, the term iEcology (internet Ecology) refers to the use of online documentation to study the natural history of plants and animals, their distributions, and the effects of humans on them (3). In fact, the internet highlights and promotes certain research topics. For example, bird species that are more frequently mentioned on social networks tend to be described taxonomically earlier, and are also the ones that interact most (positively or negatively) with human activity (4).

In search of the phenomenon

By exploring internet platforms Alamy, Flickr, Google, YouTube, and iNaturalist, Zuzanna Jagiello and her collaborators collected nearly 30 thousand photographs of hermit crabs to study the use of rubbish by these crustaceans (5). Hermit crabs are known for their peculiar habit of using empty snail shells to house their unprotected abdomens, carrying them around like someone travelling with their house on their back (6) — David Attenborough narrates here a funny swapping of shells among crabs of different size. The researchers aimed to assess the extent of the phenomenon of hermit crabs replacing natural shells with artificial materials as mobile homes (see video capturing the scene).

They focused on terrestrial species (genus Coenobita), which are distributed along the tropical coasts of the Atlantic, Indian, and Pacific Oceans. In total, Jagiello et al. found 386 images of crabs that had chosen artificial shelters. About 85% of the observations involved plastic objects, while the remaining 15% were divided among metal, glass, or combinations of both such as the base of a broken lightbulb. The sample represented 10 species out of the 17 known Coenobita species (7), spanning the three ocean basins.

Using the internet as a planetary observatory was justified in this case because Jagiello et al. (5) found only four examples of hermit crab-plastic interactions in scientific publications, which documented cases in the Maldives, and along the coasts of Belize, Brazil, and the Philippines (8-11).

Benefit of the artificial

Plastic pollution is a global threat to biodiversity, largely because many of its impacts are irreversible (12). Each species is affected in a particular way, depending on its lifestyle and habitat (13). In crustaceans, the primary effects are physiological — when animals ingest or breathe in fragments of this material — and across ecosystems — when the problem transfers between species along the food chain (14).

Each year the equivalent of 2,000 Eiffel Towers’ weight (about 20 million tonnes) of plastic waste enters the sea, dispersing everywhere (15). There is already talk of a “plastisphere” as a community of microorganisms living on plastic (16, 17) [see video summary]. However, this concept can extend functionally to any species capable of using this synthetic compound that we only invented in the early 20^th Century.

How does taking shelter in a plastic burrow benefit a hermit crab compared to using a snail shell? Several mechanisms might explain (5). On the one hand, there has been a widespread decline in mollusc abundance and diversity since the 16^th Century due to human exploitation and climate change (18, 19). As a result, in some regions, hermit crabs might have more artificial than natural shells available for housing. So much so that due to the increasing use of artificial materials by these animals and the scarcity of empty natural shells compared to the number of crabs, authorities at Mu Ko Surin National Park in Thailand have organised campaigns to donate natural snail shells. These campaigns encourage people who have shells in their collections or from other sources to contribute them, then the shells are dispersed across the habitat of hermit crabs for their use as homes.

It is also possible that the unusual appearance of a plastic shell makes it unattractive or a deterrent to predators, reducing the mortality of these crabs — analogous to how predators and prey might not recognise each other when one is an invader from a different biogeographical region (20). Additionally, it cannot be ruled out that an individual might prefer a crab mate with an innovative appearance, where a gorgeous detergent bottle cap guarantees mating success, akin to birds choosing partners with the most spectacular plumage.

Finally, terrestrial hermit crabs select smaller mollusc shells from those available in their habitat because carrying (literally, dragging) a lighter home requires less energy for movement (21) For this reason, these crabs might prefer a synthetic polymer home, which at the same size, should be lighter than a natural calcium-carbonate shell. In contrast, hermit crabs living in the ocean will take other factors into consideration for the selection of shells as homes (22); for instance, they might prefer larger and heavier shells where seabed currents are strong (23).

Clearly, as harmful as plastic is to biodiversity, once it enters the environment, many living beings will perceive it as a potential resource and will try to exploit it with varying degrees of success.

Salvador Herrando-Pérez

References

1. Kouzes RT, Myers JD, Wulf WA. 1996. Collaboratories: doing science on the internet. Computer 29: 40-46
2. Rzepa HS. 1996. Science and the internet: the world-wide web. Science Progress 79: 97-117
3. Jarić I et al. 2020. iEcology: harnessing large online resources to generate ecological insights. Trends in Ecology & Evolution 35: 630-639
4. Ladle RJ et al. 2019. A culturomics approach to quantifying the salience of species on the global internet. People and Nature 1: 524-532
5. Jagiello Z, Dylewski Ł, Szulkin M. 2024. The plastic homes of hermit crabs in the Anthropocene. Science of The Total Environment 913: 168959
6. Elwood RW. 2022. Hermit crabs, shells, and sentience. Animal Cognition 25: 1241-1257
7. Fornshell JA. 2024. The morphology and potential function of mechanoreceptors found on members of the family Coenobitidae. Arthropods 13: 7-14
8. Barreiros JP, Luiz OJ. 2009. Use of plastic debris as shelter by an unidentified species of hermit crab from the Maldives. Marine Biodiversity Records 2: e33
9. de Carvalho-Souza GF et al. 2018. Marine litter disrupts ecological processes in reef systems. Marine Pollution Bulletin 133: 464-471
10. Sasazuka M, Hamasaki K, Dan S. 2019. Shell utilization and shell-shedding behaviour by the land hermit crab Coenobita spinosus. Ethology Ecology & Evolution 31: 544-556
11. Sharma K. 2018. Hazardous hermit crab homes. Frontiers in Ecology and the Environment 16: 287-287
12. MacLeod M et al. 2021. The global threat from plastic pollution. Science 373: 61-65
13. Thushari GGN, Senevirathna JDM. 2020. Plastic pollution in the marine environment. Heliyon 6: e04709
14. Pisani XG et al. 2022. Plastics in scene: a review of the effect of plastics in aquatic crustaceans. Environmental Research 212: 113484
15. Tekman MB et al. 2022. Impacts of plastic pollution in the oceans on marine species, biodiversity and ecosystems. World Wildlife Fund (Germany)
16. Amaral-Zettler LA, Zettler ER, Mincer TJ. 2020. Ecology of the Plastisphere. Nature Reviews Microbiology 18: 139-151
17. Wright RJ, Langille MGI, Walker TR. 2021. Food or just a free ride? A meta-analysis reveals the global diversity of the Plastisphere. The ISME Journal 15: 789-806
18. Gazeau F et al. 2013. Impacts of ocean acidification on marine shelled molluscs. Marine Biology 160: 2207-2245
19. Régnier C et al. 2017. Measuring the Sixth Extinction: what do mollusks tell us? The Nautilus: 1-54
20. Carthey AJR, Banks PB. 2014. Naïveté in novel ecological interactions: lessons from theory and experimental evidence. Biological Reviews 89: 932-949
21. Contreras-Garduño J, Osorno JL, Macías-Garcia C. 2009. Weight difference threshold during shell selection relates to growth rate in the semi-terrestrial hermit crab Coenobita compressus. Behaviour 146: 1601-1614
22. Hazlett BA. 1981. The behavioral ecology of hermit crabs. Annual Review of Ecology, Evolution, and Systematics 12: 1-22
23. Alcaraz G, Toledo B, Burciaga LM. 2020. The energetic costs of living in the surf and impacts on zonation of shells occupied by hermit crabs. Journal of Experimental Biology 223: jeb222703
24. Briffa M, Arnott G, Hardege JD. 2024. Hermit crabs as model species for investigating the behavioural responses to pollution. Science of the Total Environment 906: 167360
25. Laidre ME. 2019. Private parts for private property: evolution of penis size with more valuable, easily stolen shells. Royal Society Open Science 6: 181760

But sometimes my loops take some time to finish, so I often add a rolling text update during the simulation to know how far it has progressed. But of course, I have to look at the R console to see how far things have come. Being a bit away from the central tendency of the spectrum, I can get absorbed in doing other things, so I often miss when the simulation is complete.

In a fit of excess geekiness, I’ve recently discovered voice prompts in MacOS that I can now code directly into my R simulations to give verbal updates on their progress. I find these immensely useful. I’ve therefore decided to share the basic code, because I know some other geeks out there might also appreciate the tool. Apologies — I haven’t investigated how to do this in a PC environment, so the following examples are MacOS-specific.

First, go to your Accessibility settings in System Settings in your Mac. Click on System Voice to see what voices you have access to, and which voices you wish to download to your machine. There are many languages supported.

When you construct a loop in R, add the following code within and before the loop content (this example is in English):

iter <- 1000 # number of iterations
itdiv <- iter/100 # iteration divisor 1
itdiv2 <- iter/10 # iteration divisor 2
st.time <- Sys.time() # time at start of simulation

# loop from 1 to iter
for (i in 1:iter) {
    
    # pause execution for 0.05 seconds (this would normally be the guts of your loop functions)
    Sys.sleep(0.05)
    
    # loop updaters with voice (English)
    if (i %% itdiv==0) print(paste("iter = ", i, sep=""))
    
    if (i %% itdiv2==0 & i < iter) system2("say", c("-v", "Fiona", paste(round(100*(i/iter), 0), 
                                            "per cent complete"))) # updates every 10% complete
    if (i == 0.95*iter) system2("say", c("-v", "Fiona", paste(round(100*(i/iter), 0), 
                                 "per cent complete"))) # announce at 95% complete
    if (i == 0.99*iter) system2("say", c("-v", "Fiona", paste(round(100*(i/iter), 0),
                                 "per cent complete"))) # announce at 99% complete
      
    if (i == iter) system2("say", c("-v", "Lee", "simulation complete"))
    if (i == iter) system2("say", c("-v", "Lee", paste(round(as.numeric(Sys.time() - st.time,
                            units = "mins"), 2), "minutes elapsed")))
}

Here I’ve used the female Scottish voice ‘Fiona’ and the male Australian voice ‘Lee’.

Here’s an example in French:

iter <- 1000 # nombre d'iterations
itdiv <- iter/100 # diviseur 1
itdiv2 <- iter/10 # diviseur 2
st.time <- Sys.time() # heure du commencement de la simulation

# boucle
for (i in 1:iter) {
    
    # pauser l'éxécution pendant 0,05 secondes (emplacement typique des fonctions dans la boucle)
    Sys.sleep(0.05)
    
    # mise à jour avec les voix
    if (i %% itdiv==0) print(paste("iter = ", i, sep=""))
    
    if (i %% itdiv2==0 & i < iter) system2("say", c("-v", "Aurélie", paste(round(100*(i/iter), 0),
                                           "% terminé")))
    if (i == 0.95*iter) system2("say", c("-v", "Aurélie", paste(round(100*(i/iter), 0), "% terminé")))
    if (i == 0.99*iter) system2("say", c("-v", "Aurélie", paste(round(100*(i/iter), 0), "% terminé")))
      
    if (i == iter) system2("say", c("-v", "Aurélie", "simulation terminée"))
    if (i == iter) system2("say", c("-v", "Aurélie", paste(round(as.numeric(Sys.time() - st.time, 
                           units = "mins"), 2), "minutes se sont écoulées")))
}

And an example in Italian:

iter <- 1000 # numero di iterazioni
itdiv <- iter/100 # divisore 1
itdiv2 <- iter/10 # divisore 2
st.time <- Sys.time() # tempo all'inizio della simulazione

# ciclo
for (i in 1:iter) {
    
    # mettere in pausa l'esecuzione per 0,05 secondi (inserisci qui le tue funzioni di simulazione tipiche)
    Sys.sleep(0.05)
    
    # aggiornamenti vocali
    if (i %% itdiv==0) print(paste("iter = ", i, sep=""))
    
    if (i %% itdiv2==0 & i < iter) system2("say", c("-v", "Alice", paste("completato al", 
                                           round(100*(i/iter), 0), "%")))
    #if (i == 0.95*iter) system2("say", c("-v", "Alice", paste("completato al", round(100*(i/iter), 0),
                                          "%")))
    #if (i == 0.99*iter) system2("say", c("-v", "Alice", paste("completato al", round(100*(i/iter), 0),
                                          "%"))) 

    if (i == iter) system2("say", c("-v", "Alice", "simulazione completa"))
    #if (i == iter) system2("say", c("-v", "Alice", paste("sono passati", round(as.numeric(Sys.time() 
                                     - st.time, units = "mins"), 2), "minuti")))
}

There you have it. Enjoy geeking out!

CJA Bradshaw

Quite a bit late this year, but I’ve finally put together the 2023 conservation / ecology / sustainability journal ranks based on my (published) journal-ranking method (as I’ve done every year since 2008).

After 16 years of doing this exercise, I can’t help but notice that most journals don’t do much differently from year to year. They mostly tend to publish the same number of papers, get the same number of total publications, and therefore, remain approximately in the same rank relative to others.

Some things to note: Clarivate continues to modify its algorithm, meaning that most journal Impact Factors have gone down yet again. This is somewhat irrelevant from the perspective of relative ranking, but it might piss off a few journals.

I therefore present the new 2023 ranks for: (i) 111 ecology, conservation and multidisciplinary journals, (ii) 29 open-access (i.e., you have to pay) journals from the previous category, (iii) 68 ‘ecology’ journals, (iv) 33 ‘conservation’ journals, (v) 44 ‘sustainability’ journals (with general and energy-focussed journals included), and (vi) 21 ‘marine & freshwater’ journals.

Here are the results:

(i) ecology, conservation and multidisciplinary

Here’s a more focussed list of the top-20 journals from above:

Not a lot of change from last year, but Global Change Biology has jumped forward a few positions.

From the full sample above, here is the ranking for the 28 journals that are open-access, if you fancy paying several thousands (if not tens of thousands) of dollars/euros/pounds for the privilege:

(ii) ecology journals

Not many changes for the ecology journals, but Trends in Ecology and Evolution has taken first place from Nature Ecology and Evolution. One Earth continues its upward trend.

Here’s a closer look at the top-20 from that last list:

(iii) conservation journals

Here is the most relevant list for ConservationBytes.com readers:

There are no really major changes here either. Frontiers in Conservation Science has finally made it into the list (albeit, in last place).

(iv) sustainability journals

In the ‘sustainability’ journals (including some general-category ones too), not much has changed since last year:

(v) marine and freshwater journals

Not much change here, except that Coral Reefs has moved up a few spots:

It’s all a bit boring and predictable, despite the continued downward trend in Impact Factors. And I remained disgusted by the gross exploitation of academic publishing companies.

See also the previous years’ rankings (2022, 2021, 2020, 2019, 2018, 2017, 2016, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008).

CJA Bradshaw

However, one big bonus for the environment’s recovery is the likely eradication of feral pigs (Sus scrofa). Invasive feral pigs cause a wide range of environmental, economic and social damages. In Australia, feral pigs occupy about 40% of the mainland and offshore islands, with a total, yet highly uncertain, population size estimated in the millions. 

Feral pigs are recognised as a key threatening process under the Environment Protection and Biodiversity Conservation Act 1999, with impacts on at least 148 nationally threatened species and eight threatened ecological communities. They are a declared invasive species and the subject to control programs in all Australian jurisdictions.

In a new article published in Ecosphere, a collaboration between PIRSA Biosecurity and the Global Ecology Laboratory at Flinders University analysed optimal strategies for culling feral pigs. 

Lead author Peter Hamnett states that this could be helpful in Australia and elsewhere where feral pigs are a major environmental problem. 

Globally, feral pigs cause extensive damage to biodiversity and agricultural land and infrastructure, so successes like this one are extremely important. 

As well as likely having eradicated pigs entirely, the success of the program was even more astounding when you consider its rough terrain and large size — Kangaroo Island is Australia’s third-largest island at 4430 km².

Invasive species cost Australia around $25 billion/year in terms of management and economic losses, with reduction and eradication campaigns often ad hoc. 

First introduced to the island in 1803, the feral pig population grew exponentially, mainly on the western end of the island where native flora and fauna attract tourists from around the world. Despite sporadic eradication efforts, the annual cost of feral pigs to farming and the economy on the island has run around $1 million. 

The model gives important results, particularly when many attempt eradications of invasive species are prone to fail. It also was well-timed after the fires on Kangaroo Island already reduced the pig population by about 90%.

The program managed to kill 900 pigs in total, using the most advanced technology including trapping and thermal imaging from helicopters. Follow-up monitoring is checking whether any pigs remain. 

Major investment from State, Commonwealth and other partners, totalling about $7 million, was another reason the Kangaroo Island program has been successful.

The paper assesses the costs and techniques that led to success, which will help land managers to select the most cost-effective control methods in the future.

The methods we applied will support decision-making in future feral animal eradication programs, allowing pest managers to identify the best control methods and estimate expenditure to achieve eradication in a realistic timeframe. 

More effective eradication strategies will give project investors, partners and local communities more confidence and, in turn, attract more support and help.

The eradication program was funded by the State and Commonwealth governments, Kangaroo Island Landscape Board, and the South Australian livestock industry.  

The modelling article included collaborations with the Kangaroo Island Landscape Board, National Parks and Wildlife Service, Livestock South Australia, AgKI, Kangaroo Island Land for Wildlife, landholders, and tourism stakeholders. 

Acknowledgements: Thanks to PIRSA’s Biosecurity Division, Invasive Species Unit for data access and support. We acknowledge the continued connection of Kaurna, Ngarrindjeri, and Narungga people to Karta (Kangaroo Island) and that we did this work on the unceded lands of the Kaurna.

Imagine growing up beside the eastern Mediterranean Sea 14,000 years ago. You’re an accomplished sailor of the small watercraft you and your fellow villagers make, and you live off both the sea and the land.

But times have been difficult — there just isn’t the same amount of game or fish around as when you were a child. Maybe it’s time to look elsewhere for food.

Now imagine going farther than ever before in your little boat, accompanied maybe by a few others, when suddenly you spot something on the horizon. Is that an island?

An island of tiny elephants and hippos

Welcome to Cyprus as the world emerges from the last ice age. You are the first human to set your eyes on this huge, heavily forested island teeming with food.

When you beach your boat to have a look around, you can’t believe what you’re seeing — tiny boar-sized hippos and horse-sized elephants that look like babies to your eyes. There are so many of them, and you’re hungry after the long journey.

The diminutive beasts don’t seem to show any fear. You easily kill a few and preserve the meat as best you can for the long journey back.

When you get home, you are excited to let everyone in the village know what you’ve found. Soon enough, you organise a major expedition back to the island.

Of course, we’ll never know if this kind of scenario took place, but it’s a plausible story of how and when the first humans managed to get to Cyprus. It also illustrates how they might have quickly brought about the demise of the tiny hippopotamus Phanourios minor, as well as the dwarf elephant Palaeoloxodon cypriotes.

Dwarf ‘giants’

Cyprus wasn’t the only Mediterranean island with dwarf wildlife. In fact, Crete, Malta, Sicily, Sardinia and many other islands had their own dwarf elephants and hippos.

Island dwarfism — the process in which a once large, mainland species evolves to become smaller in response to fewer resources and predators — is in fact quite common. Unfortunately, the process also makes such species more vulnerable to rapid environmental change, including the arrival of new predators such as humans.

The Cypriot dwarf hippopotamus was the smallest dwarf hippo in the Mediterranean region. Genetic data suggest it diverged from the common hippopotamus (Hippopotamus amphibius) roughly 1.5 million years ago.

The Cypriot dwarf elephant was less than 10% of the size of its mainland ancestor, the straight-tusked elephant (Palaeoloxodon antiquus) that inhabited Europe and Western Asia during the Middle and Late Pleistocene.

An extinction controversy

For a long time, many archaeologists and palaeontologists didn’t believe humans had anything to do with the extinction of these two “megafauna” species on Cyprus.

The doubters assumed that either people arrived well after the extinctions, or the earliest humans were too few to be able to kill off entire species.

Earlier this year we showed that people came to Cyprus between 14,000 and 13,000 years ago, well before hippos and elephants went extinct. We also showed that the human population likely grew to several thousand within a few hundred years of arrival. But we didn’t know whether this human population was large enough to drive the dwarf hippos and elephants to extinction.

Our new research published today answers this question with a combination of several different types of mathematical models.

Could a small human population cause extinction?

Even though these animals are long extinct, we can draw some conclusions about their likely population because we can estimate their weights from palaeontological information. The dwarf hippo weighed around 130kg, and the dwarf elephant came in at just over 500kg.

We also know how to translate weights to estimates of population size, longevity, survival and fertility. We can even use data collected from related species still living today, such as the pygmy hippo and the African elephant, to estimate how fast they would have grown.

With this information, we built computer models of what would have happened to the two mini-megafauna species on Cyprus when human hunters arrived. We estimated how efficient human hunters would be, how long it would take them to process each carcass, and how much energy hunter-gatherers need to survive.

We also estimated how much of the human diet included these species, and how this proportion might have changed as the dwarf hippo and elephant numbers dwindled.

We found that even a small human population, numbering between 3,000 and 7,000, could have easily driven first dwarf hippos, and then dwarf elephants, to extinction. Our model showed the process would have taken less than 1,000 years. This prediction matches the sequence of extinction inferred from the palaeontological record.

Our results provide strong evidence that palaeolithic peoples in Cyprus were at least partially, if not entirely, responsible for megafauna extinctions during the Late Pleistocene and early Holocene.

Cyprus was the perfect place to test our models because the island offers an ideal set of conditions to examine whether the arrival of humans ultimately led to the extinction of its megafauna. This is because Cyprus was a relatively simple test case – a small island of around 11,000 square kilometres at the time, with only two species of megafauna.

Our research therefore improves our understanding of how even small human populations can disrupt ecosystems and cause major extinctions, particularly in times of rapid environmental change.

Corey J. A. Bradshaw, Matthew Flinders Professor of Global Ecology and Node Leader in the ARC Centre of Excellence for Indigenous and Environmental Histories and Futures, Flinders University; Christian Reepmeyer, Deputy Director – Oceania, Deutsches Archäologisches Institut – German Archaeological Institute, and Theodora Moutsiou, Special Scientist, University of Cyprus

This article is republished from The Conversation under a Creative Commons license. Read the original article.

In a recent episode of The Great Simplification podcast, Nate Hagens was joined by global ecologist Corey Bradshaw to discuss his recent research on the rapid decline in biodiversity, how population and demographics will change in the coming decades, and what both of these will mean for complex global economies currently reliant on a stable environment.

How might the current rate of species loss result in a domino effect of widespread and severe impacts on the health of the biosphere? What are the key factors driving changes in population growth, and how do these vary across different countries and cultures? Could we stabilize these trends and achieve a sustainable balance between biodiversity and human population through targeted policies and initiatives — and how much time is left to act?

Over the last few decades, invasive species have incurred an average cost of at least US$26.8 billion per year globally, and are predicted to continue increasing. Investing in early management to control their potential damage and spread is widely recognised as more cost-effective than waiting until an invasive species demonstrates clear impacts. 

However, there is limited information available demonstrating whether a country’s capacity to manage its invasive species is effective at limiting future damage.

Our new study published in the journal Ecological Economics found that while more affluent countries with higher economic activity are vulnerable to more damage from invasive species, they also have the highest potential to limit damages incurred by investing more in management. Consequently, a nation’s economic capability partially determines the efficacy of investing in the control and prevention of invasive species.

The study is the first global-scale investigation of the cost-effectiveness of management and intervention of invasive species.

Based on the data compiled in the InvaCost database, our analyses show that the most affluent nations with sufficient economic capacity to invest in controlling their invasive species reap the biggest rewards by reducing damages in the long term.

Lower-income nations often struggle to allocate enough resources to manage their invasive species, so they suffer relatively more damage as a result.

Our study indicates that lower-income countries possess a clear disadvantage in mitigating the substantial economic losses caused by invasive species.

Importantly, our results show that it is prudent for wealthier nations to invest in controlling invasive species within less-capable neighbouring countries, because wealthy nations are also vulnerable to more invasions originating from potentially their less-prepared neighbours.

Such a form of international assistance serves all affected nations, and could ultimately reduce the impact of invasive species across the entire world.