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Global change imposes multiple challenges on species and, thus, a reliable prediction of current and future vulnerability of species must consider multiple stressors and intrinsic traits of species. Climate, physiology, and forest cover, for example, are required to evaluate threat to thermolabile forest-dependent species, such as sloths (Bradypus spp.; Mammalia: Xenarthra). Here, we estimated future changes in the distribution of three sloth species using a metabolic-hybrid model focused on climate (climatic only, i.e., CO approach) and adding forest cover constraints to distribution of species (climate plus land cover, i.e., CL approach). We used an innovative method to generate estimates of physiological parameters for endotherms, validated with field data. The CF approach predicted a future net expansion of distribution of B. torquatus and B. variegatus, and a future net contraction of distribution of B. tridactylus. The inclusion of forest cover constraints, however, reversed the predictions for B. torquatus, with a predicted net distribution contraction. It also reduced expansion of B. variegatus, although still showing a large net expansion. Thus, B. variegatus is not predicted to be threatened in the future; B. tridactylus emerges as the species most vulnerable to climate change, but with no considerable forest losses, while B. torquatus shows the opposite pattern. Our study highlights the importance of incorporating multiple stressors in predictive models in general. To increase resilience of species to climate change, it is key to control deforestation in the Amazon for B. tridactylus, and to promote reforestation in the Atlantic Forest for B. torquatus.

 

Caudal autotomy is a striking adaptation used by many lizard species to evade predators. Most studies to date indicate that caudal autotomy impairs lizard locomotor performance. Surprisingly, some species bearing the longest tails show negligible impacts of caudal autotomy on sprint speed. Part of this variation has been attributed to lineage effects. For the first time, we model the effects of caudal autotomy on the locomotor performance of a gymnophthalmid lizard, Micrablepharus atticolus, which has a long and bright blue tail. To improve model accuracy, we incorporated the effects of several covariates. We found that body temperature, pregnancy, mass, collection site, and the length of the regenerated portion of the tail were the most important predictors of locomotor performance. However, sprint speed was unaffected by tail loss. Apparently, the long tail of M. atticolus is more useful when using undulation amidst the leaf litter and not when using quadrupedal locomotion on a flat surface. Our findings highlight the intricate relationships among physiological, morphological, and behavioral traits. We suggest that future studies about the impacts of caudal autotomy among long-tailed lizards should consider the role of different microhabitats/substrates on locomotor performance, using laboratory conditions that closely mimic their natural environments. 

Models predicting the distribution of savannas worldwide have identified rainfall and fire as their primary determinants. However, most of them have relied upon adult traits, while juvenile traits, at the bottleneck of the plant's life cycle, have been largely overlooked. We developed a novel mechanistic model based on the effects of temperature and fire on germination traits to predict the distribution of Cerrado, i.e., the largest neotropical savanna.

Cerrado and neighboring biomes.

We compiled data on the germination of seeds subjected to temperature and heat shock treatments and used generalized additive mixed models to predict germination potential as a function of temperature, species, physiognomy (forest/savanna), habits (herbs/shrubs/trees), and fire frequency.

The best model showed that seasonal temperatures set the germination limits for seeds of both savanna and forest physiognomies. Forest seeds presented a higher germinability in the optimum temperature range, but savanna seeds had higher survival rates after heat shocks. The model revealed that the southern limit of Cerrado is determined by low winter temperatures, while the western and eastern boundaries are set by high summer temperatures. The model also predicted an area of high germination potential that coincides with high biodiversity and climate stability in the Cerrado.

Germination traits are highly valuable to predict vegetation responses to climate. Seasonal temperatures are primary determinants of the Cerrado’s extent, while fire favors the recruitment of savanna species over the Cerrado–Amazonia ecotone. Global warming may significantly impact the germination potential of native species.