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Strong phenological shifts in response to changes in climatic conditions have been reported for many species, including amphibians, which are expected to breed earlier. Phenological shifts in breeding are observed in a wide number of amphibian populations, but less is known about populations living at high elevations, which are predicted to be more sensitive to climate change than lowland populations. The goal of this study is to assess the main factors determining the timing of breeding in an alpine population of the common toad (Bufo bufo) and to describe the observed shifts in its breeding phenology. We modelled the effect of environmental variables on the start and peak dates of the breeding season using 39 years of individual-based data. In addition, we investigated the effect of the lunar cycle, as well as the individual variation in breeding phenology. Finally, to assess the individual heterogeneity in the timing of breeding, we calculated the repeatability of the timing of arrival at the breeding site. Breeding advanced to earlier dates in the first years of the study but the trend continued only until the mid 1990s, and stabilised afterwards. Overall, toads are now breeding on average around 30 days earlier than at the start of the study period. High temperatures and low snow cover in winter and spring, as well as reduced spring precipitation were all associated with earlier breeding. Additionally, we found evidence of males arriving on average before females at the breeding site but no clear and strong effect of the lunar cycle. We only found weak evidence of among-individual variation in shifts in the breeding phenology, as well as a low repeatability of arrival timing. Our findings show that the observed changes in breeding phenology are strongly associated with the environmental conditions. These results contribute to filling a knowledge gap on the effects of climate change on alpine amphibian populations. Moreover, we show that changes in phenology, especially in the mountains, can be hard to predict as local microclimatic conditions do not necessarily reflect the observed global climatic trends.

Density dependent carry-over effects from one life history stage to another can affect the dynamics of populations. Here we study such carry-over effects from the tadpole to the postmetamorphic juvenile stage in an endangered amphibian, the natterjack toad (Epidalea calamita). We raised tadpoles in outdoor aquatic mesocosms at four densities and assessed juvenile performance after metamorphosis in terrestrial mesocosms. High larval density reduced mass at metamorphosis by 50 % and doubled the length of the larval period. Survival was reduced at the high densities. Larger metamorphs had higher survival in terrestrial mesocosms and remained larger than cohort members at the end of the 30-day experiment. Because juvenile survival drives amphibian population dynamics, density-dependent carry-over effects to the juvenile stage are likely to affect population viability. We discuss the implications of the results for amphibian conservation practice, both pond construction programs and surveys of amphibian populations.

Abstract The Nullarbor Plain constitutes one of the main biogeographic barriers of Australia, and it has been suggested to have played a key role in the disjunct distribution of numerous southern Australian species. Although previous research has shown that the origin of this barrier coincides with the timing of the speciation events in some plant lineages, it is not clear whether the uplift of this barrier promoted divergence events in vertebrates. We addressed the role of the Nullarbor barrier and its fringing semiarid habitats as drivers of beta diversity in bird assemblages. Specifically, we determined the effect of distance from the Nullarbor barrier, environmental conditions, and isolation by distance on the composition of local communities on both sides of the plain. We measured beta diversity using taxonomic, phylogenetic, and functional metrics of composition. The influence of precipitation, geographic distance, and distance to the Nullarbor barrier on these metrics was addressed using generalized dissimilarity models and a moving‐window approach. We also tested for differences in local extinction, dispersal and speciation rates, and lineage diversity between two regions, southeastern (SE) and southwestern (SW) Australia. Geological and orogenetic dynamics linked to the appearance of the Nullarbor Plain may have spurred speciation events in SE. However, evidence suggests that subsequent periods in which this region was wetter and forested favored dispersal, mainly from SE to SW. Accordingly, observed dissimilarity in species composition was lower than expected at random, suggesting the existence of considerable turnover between regions. Our results suggest that precipitation deficit (and the xeric vegetation that it promotes) was the most important predictor of beta diversity, whereas the distance to the barrier explained some variation in terms of phylogenetic composition. This study shows that the uplift of the Nullarbor barrier played a minor role in shaping present‐day bird diversity in southern Australia. Recent speciation events coupled with historical connectivity can explain the observed patterns.

Seasonal environmental conditions shape the behavior and life history of virtually all organisms. Climate change is modifying these seasonal environmental conditions, which threatens to disrupt population dynamics. It is conceivable that climatic changes may be beneficial in one season but result in detrimental conditions in another because life-history strategies vary between these time periods. We analyzed the temporal trends in seasonal survival of yellow-bellied marmots (Marmota flaviventer) and explored the environmental drivers using a 40-y dataset from the Colorado Rocky Mountains (USA). Trends in survival revealed divergent seasonal patterns, which were similar across age-classes. Marmot survival declined during winter but generally increased during summer. Interestingly, different environmental factors appeared to drive survival trends across age-classes. Winter survival was largely driven by conditions during the preceding summer and the effect of continued climate change was likely to be mainly negative, whereas the likely outcome of continued climate change on summer survival was generally positive. This study illustrates that seasonal demographic responses need disentangling to accurately forecast the impacts of climate change on animal population dynamics.

Biological responses to climate change have been widely documented across taxa and regions, but it remains unclear whether species are maintaining a good match between phenotype and environment, i.e. whether observed trait changes are adaptive. Here we reviewed 10,090 abstracts and extracted data from 71 studies reported in 58 relevant publications, to assess quantitatively whether phenotypic trait changes associated with climate change are adaptive in animals. A meta-analysis focussing on birds, the taxon best represented in our dataset, suggests that global warming has not systematically affected morphological traits, but has advanced phenological traits. We demonstrate that these advances are adaptive for some species, but imperfect as evidenced by the observed consistent selection for earlier timing. Application of a theoretical model indicates that the evolutionary load imposed by incomplete adaptive responses to ongoing climate change may already be threatening the persistence of species.

Understanding how the natural world will be impacted by environmental change over the coming decades is one of the most pressing challenges facing humanity. Addressing this challenge is difficult because environmental change can generate both population-level plastic and evolutionary responses, with plastic responses being either adaptive or nonadaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses and that the rate of adaptive evolution to a new environment depends on whether plastic responses are adaptive or nonadaptive. Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full machinery of the evolutionarily explicit models we develop will be needed to predict responses to environmental change or whether simpler nonevolutionary models that are now widely constructed may be sufficient.

The Nullarbor Plain constitutes one of the main biogeographic barriers of Australia, and it has been suggested to have played a key role in the disjunct distribution of numerous southern Australian species. Although previous research has shown that the origin of this barrier coincides with the timing of the speciation events in some plant lineages, it is not clear whether the uplift of this barrier promoted divergence events in vertebrates. We addressed the role of the Nullarbor barrier and its fringing semiarid habitats as drivers of beta diversity in bird assemblages. Specifically, we determined the effect of distance from the Nullarbor barrier, environmental conditions, and isolation by distance on the composition of local communities on both sides of the plain. We measured beta diversity using taxonomic, phylogenetic, and functional metrics of composition. The influence of precipitation, geographic distance, and distance to the Nullarbor barrier on these metrics was addressed using generalized dissimilarity models and a moving‐window approach. We also tested for differences in local extinction, dispersal and speciation rates, and lineage diversity between two regions, southeastern (SE) and southwestern (SW) Australia. Geological and orogenetic dynamics linked to the appearance of the Nullarbor Plain may have spurred speciation events in SE. However, evidence suggests that subsequent periods in which this region was wetter and forested favored dispersal, mainly from SE to SW. Accordingly, observed dissimilarity in species composition was lower than expected at random, suggesting the existence of considerable turnover between regions. Our results suggest that precipitation deficit (and the xeric vegetation that it promotes) was the most important predictor of beta diversity, whereas the distance to the barrier explained some variation in terms of phylogenetic composition. This study shows that the uplift of the Nullarbor barrier played a minor role in shaping present‐day bird diversity in southern Australia. Recent speciation events coupled with historical connectivity can explain the observed patterns. [ABSTRACT FROM AUTHOR]

The snow leopard (Panthera uncia) is one of the world's most elusive felids. In Bhutan, which is one of the 12 countries where the species still persists, reliable information on its distribution and habitat suitability is lacking, thus impeding effective conservation planning for the species. To fill this knowledge gap, we created a country-wide species distribution model using “presence-only” data from 420 snow leopard occurrences (345 from a sign survey and 77 from a camera-trapping survey) and 12 environmental covariates consisting of biophysical and anthropogenic factors. We analyzed the data in an ensemble model framework which combines the outputs from several species distribution models. To assess the adequacy of Bhutan's network of protected areas and their potential contribution toward the conservation of the species, we overlaid the output of the ensemble model on the spatial layers of protected areas and biological corridors. The ensemble model identified 7,206 km2 of Bhutan as suitable for the snow leopard: 3,647 km2 as highly suitable, 2,681 km2 as moderately suitable, and 878 km2 as marginally suitable. Forty percent of the total suitable habitat consisted of protected areas and a further 8% of biological corridors. These suitable habitats were characterized by a mean livestock density of 1.3 individuals per hectare, and a mean slope of 25°; they closely match the distribution of the snow leopard's main wild prey, the bharal (Pseudois nayaur). Our study shows that Bhutan's northern protected areas are a centre for snow leopard conservation both at the national and regional scale.

Abstract Background Animal-borne data loggers today often house several sensors recording simultaneously at high frequency. This offers opportunities to gain fine-scale insights into behaviour from individual-sensor as well as integrated multi-sensor data. In the context of behaviour recognition, even though accelerometers have been used extensively, magnetometers have recently been shown to detect specific behaviours that accelerometers miss. The prevalent constraint of limited training data necessitates the importance of identifying behaviours with high robustness to data from new individuals, and may require fusing data from both these sensors. However, no study yet has developed an end-to-end approach to recognise common animal behaviours such as foraging, locomotion, and resting from magnetometer data in a common classification framework capable of accommodating and comparing data from both sensors. Methods We address this by first leveraging magnetometers’ similarity to accelerometers to develop biomechanical descriptors of movement: we use the static component given by sensor tilt with respect to Earth’s local magnetic field to estimate posture, and the dynamic component given by change in sensor tilt with time to characterise movement intensity and periodicity. We use these descriptors within an existing hybrid scheme that combines biomechanics and machine learning to recognise behaviour. We showcase the utility of our method on triaxial magnetometer data collected on ten wild Kalahari meerkats (Suricata suricatta), with annotated video recordings of each individual serving as groundtruth. Finally, we compare our results with accelerometer-based behaviour recognition. Results The overall recognition accuracy of > 94% obtained with magnetometer data was found to be comparable to that achieved using accelerometer data. Interestingly, higher robustness to inter-individual variability in dynamic behaviour was achieved with the magnetometer, while the accelerometer was better at estimating posture. Conclusions Magnetometers were found to accurately identify common behaviours, and were particularly robust to dynamic behaviour recognition. The use of biomechanical considerations to summarise magnetometer data makes the hybrid scheme capable of accommodating data from either or both sensors within the same framework according to each sensor’s strengths. This provides future studies with a method to assess the added benefit of using magnetometers for behaviour recognition.

It is unclear whether species’ responses to climate change tend to be adaptive or sufficient to keep up with climate change. Here, Radchuk et al. perform a meta-analysis showing that in birds phenology has advanced adaptively in some species, though not all the way to the new optima.

Abstract One of the largest causes of fluctuations in the size and structure of populations is changes in the environment. In nature, these changes are often temporally autocorrelated and the strength and direction of the autocorrelation can affect population dynamics. These effects are mediated by complex, simultaneously occurring ecological and evolutionary processes, such as phenotypic plasticity and selection. Determining how these processes interact to affect responses of different life histories to autocorrelated environmental fluctuations is of paramount importance to infer which taxa are likely to go extinct or become invasive under global change. Here, we assessed the effect of autocorrelation in environmental states on the trait and population dynamics of different life histories using an evolutionary explicit individual‐based modeling approach. We found that, in general, higher positive temporal autocorrelation caused more variation in population size. Fast life histories were more affected than slow ones as they were able to adapt more quickly to varying environmental optima and therefore experienced larger initial decreases in population size when optima changed. Including adaptive phenotypic plasticity buffered the effects of autocorrelation on population dynamics while nonadaptive plasticity amplified them, especially for slow life histories, which recovered less from maladaptation. This study highlights that integration of phenotypic plasticity, selection, and population dynamics is important to improve our understanding of how different life histories deal with autocorrelated climate variability.

Predicting population collapse by monitoring key early warning signals in time-series data may highlight when interventions are needed. Here, the authors show that including information on phenotypic traits like body size can more accurately predict critical transitions than abundance data alone.