Climate change is predicted to cause population collapse in a cooperative breeder.

It has been suggested that animals may have evolved cooperative breeding strategies in response to extreme climatic conditions. Climate change, however, may push species beyond their ability to cope with extreme climates, and reduce the group sizes in cooperatively breeding species to a point where populations are no longer viable. Predicting the impact of future climates on these species is challenging as modelling the impact of climate change on their population dynamics requires information on both group- and individual-level responses to climatic conditions. Using a single-sex individual-based model incorporating demographic responses to ambient temperature in an endangered species, the African wild dog Lycaon pictus, we show that there is a threshold temperature above which populations of the species are predicted to collapse. For simulated populations with carrying capacities equivalent to the median size of real-world populations (nine packs), extinction risk increases once temperatures exceed those predicted in the best-case climate warming scenario (Representative Concentration Pathway [RCP] 2.6). The threshold is higher (between RCP 4.5 and RCP 6.0) for larger simulated populations (30 packs), but 84% of real-world populations number <30 packs. Simulated populations collapsed because, at high ambient temperatures, juvenile survival was so low that packs were no longer recruiting enough individuals to persist, leading them to die out. This work highlights the importance of social dynamics in determining impacts of climatic variables on social species, and the critical role that recruitment can play in driving population-level impacts of climate change. Population models parameterised on long-term data are essential for predicting future population viability under climate change.

Optimizing the automated recognition of individual animals to support population monitoring.

Reliable estimates of population size and demographic rates are central to assessing the status of threatened species. However, obtaining individual-based demographic rates requires long-term data, which is often costly and difficult to collect. Photographic data offer an inexpensive, noninvasive method for individual-based monitoring of species with unique markings, and could therefore increase available demographic data for many species. However, selecting suitable images and identifying individuals from photographic catalogs is prohibitively time-consuming. Automated identification software can significantly speed up this process. Nevertheless, automated methods for selecting suitable images are lacking, as are studies comparing the performance of the most prominent identification software packages. In this study, we develop a framework that automatically selects images suitable for individual identification, and compare the performance of three commonly used identification software packages; Hotspotter, I3S-Pattern, and WildID. As a case study, we consider the African wild dog, Lycaon pictus, a species whose conservation is limited by a lack of cost-effective large-scale monitoring. To evaluate intraspecific variation in the performance of software packages, we compare identification accuracy between two populations (in Kenya and Zimbabwe) that have markedly different coat coloration patterns. The process of selecting suitable images was automated using convolutional neural networks that crop individuals from images, filter out unsuitable images, separate left and right flanks, and remove image backgrounds. Hotspotter had the highest image-matching accuracy for both populations. However, the accuracy was significantly lower for the Kenyan population (62%), compared to the Zimbabwean population (88%). Our automated image preprocessing has immediate application for expanding monitoring based on image matching. However, the difference in accuracy between populations highlights that population-specific detection rates are likely and may influence certainty in derived statistics. For species such as the African wild dog, where monitoring is both challenging and expensive, automated individual recognition could greatly expand and expedite conservation efforts.

High temperatures and human pressures interact to influence mortality in an African carnivore.

The impacts of high ambient temperatures on mortality in humans and domestic animals are well-understood. However much less is known about how hot weather affects mortality in wild animals. High ambient temperatures have been associated with African wild dog Lycaon pictus pup mortality, suggesting that high temperatures might also be linked to high adult mortality.We analyzed mortality patterns in African wild dogs radio-collared in Kenya (0°N), Botswana (20°S), and Zimbabwe (20°S), to examine whether ambient temperature was associated with adult mortality.We found that high ambient temperatures were associated with increased adult wild dog mortality at the Kenya site, and there was some evidence for temperature associations with mortality at the Botswana and Zimbabwe sites.At the Kenya study site, which had the highest human impact, high ambient temperatures were associated with increased risks of wild dogs being killed by people, and by domestic dog diseases. In contrast, temperature was not associated with the risk of snare-related mortality at the Zimbabwe site, which had the second-highest human impact. Causes of death varied markedly between sites.Pack size was positively associated with survival at all three sites.These findings suggest that while climate change may not lead to new causes of mortality, rising temperatures may exacerbate existing anthropogenic threats to this endangered species, with implications for conservation. This evidence suggests that temperature-related mortality, including interactions between temperature and other anthropogenic threats, should be investigated in a greater number of species to understand and mitigate likely impacts of climate change. ​.

Within- and between-group dynamics in an obligate cooperative breeder.

Cooperative behaviour can have profound effects on demography. In many cooperative species, components of fitness (e.g. survival, reproductive success) are diminished in smaller social groups. These effects (termed group-level component Allee effects) may lead smaller groups to grow relatively slowly or fail to persist (termed group-level demographic Allee effects). If these group-level effects were to propagate to the population level, small populations would grow slowly or decline to extinction (termed population-level demographic Allee effects). However, empirical studies have revealed little evidence of such population-level effects. Theoretical studies suggest that dispersal behaviour could either cause or prevent the propagation of group-level Allee effects to the population level. We therefore characterized within- and between-pack dynamics in a population of African wild dogs (Lycaon pictus) to test these contrasting model predictions. Larger wild dog packs produced more pups, and their members experienced higher survival than those in smaller packs. Nevertheless, larger packs grew more slowly than smaller packs, because natal adults dispersed away from them. Most packs either died out in whole-pack death events or broke up when their founders died, irrespective of pack size. Overall, packs showed negative density dependence rather than group-level demographic Allee effects. Larger packs produced more, but not larger, dispersal groups and hence generated more, but not larger, new packs. Larger packs thus contributed more than smaller packs to the number of packs in the population, but their large size did not propagate to their daughter packs. This pattern helps to explain the absence of population-level Allee effects in this species. Dispersal behaviour, itself driven by natural selection on individual reproductive strategies, played a pivotal role in population dynamics, leading to the formation of new packs and limiting the size of established packs. Understanding dispersal processes is likely to be important to understanding the population dynamics of other cooperatively breeding species.