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  1. Responses of wildlife to climate change are typically quantified at the species level, but physiological evidence suggests significant intraspecific variation in thermal sensitivity given adaptation to local environments and plasticity required to adjust to seasonal environments. Spatial and temporal variation in thermal responses may carry important implications for climate change vulnerability; for instance, sensitivity to extreme weather may increase in specific regions or seasons. Here, we leverage high-resolution observational data from eBird to understand regional and seasonal variation in thermal sensitivity for 21 bird species. Across their ranges, most birds demonstrated regional and seasonal variation in both thermal peak and range, or the temperature and range of temperatures when observations peaked. Some birds demonstrated constant thermal peaks or ranges across their geographical distributions, while others varied according to local and current environmental conditions. Across species, birds typically demonstrated either geographical or seasonal adaptation to climate. Local adaptation and phenotypic plasticity are likely important but neglected aspects of organismal responses to climate change.

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    Free, publicly-accessible full text available November 8, 2024
  2. Free, publicly-accessible full text available May 23, 2025
  3. The cerebellum is considered a “learning machine” essential for time interval estimation underlying motor coordination and other behaviors. Theoretical work has proposed that the cerebellum’s input recipient structure, the granule cell layer (GCL), performs pattern separation of inputs that facilitates learning in Purkinje cells (P-cells). However, the relationship between input reformatting and learning has remained debated, with roles emphasized for pattern separation features from sparsification to decorrelation. We took a novel approach by training a minimalist model of the cerebellar cortex to learn complex time-series data from time-varying inputs, typical during movements. The model robustly produced temporal basis sets from these inputs, and the resultant GCL output supported better learning of temporally complex target functions than mossy fibers alone. Learning was optimized at intermediate threshold levels, supporting relatively dense granule cell activity, yet the key statistical features in GCL population activity that drove learning differed from those seen previously for classification tasks. These findings advance testable hypotheses for mechanisms of temporal basis set formation and predict that moderately dense population activity optimizes learning. NEW & NOTEWORTHY During movement, mossy fiber inputs to the cerebellum relay time-varying information with strong intrinsic relationships to ongoing movement. Are such mossy fibers signals sufficient to support Purkinje signals and learning? In a model, we show how the GCL greatly improves Purkinje learning of complex, temporally dynamic signals relative to mossy fibers alone. Learning-optimized GCL population activity was moderately dense, which retained intrinsic input variance while also performing pattern separation. 
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  4. Abstract Aim

    Species depend upon a constrained set of environmental conditions, or environmental niches, for survival and reproduction that are being increasingly perturbed or lost under rapid climatic change. Seasonal environments, which require species to withstand shifting conditions or track their niches via movement, can offer an important system to study the range of biological responses to potentially cope with climate change. Here, we develop a novel methodological framework to identify niche‐tracking strategies, including the tracking of niche position and breadth, using a uniquely well‐sampled system of 619 New World bird species.


    Western Hemisphere.

    Time period


    Major taxa studied

    Birds (Aves).


    At continental scales, we identify the tracking of both environmental niche position and breadth and assess its phylogenetic and functional underpinning. Partitioning niche position and breadth tracking can inform whether climatic means or extremes constrain seasonal niches.


    We uncover four primary niche‐tracking strategies, including the tracking of environmental niche position, niche breadth, both or neither. Species that track niche position most often also track niche breadth, but nearly 40% only track one component and 26% only track niche breadth and not position. There is only limited phylogenetic determinism to this variation, but a strong association with ecological and functional attributes that differs between niche position versus niche breadth tracking.

    Main conclusions

    The observed diversity in type and strength of environmental niche‐tracking strategies points to highly differing sensitivity to ongoing climatic change, with narrow trackers of both position and breadth particularly susceptible. The trait associations of niche tracking imply significant functional consequences for communities and ecosystems as impending climate change affects some strategies more strongly than others. Seasonal environments and their diversity of niche‐tracking strategies offer exceptionally dynamic systems for understanding the biological responses and consequences of climate change.

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  5. Thomas, Matthew B. (Ed.)
    Climate change is expected to have complex effects on infectious diseases, causing some to increase, others to decrease, and many to shift their distributions. There have been several important advances in understanding the role of climate and climate change on wildlife and human infectious disease dynamics over the past several years. This essay examines 3 major areas of advancement, which include improvements to mechanistic disease models, investigations into the importance of climate variability to disease dynamics, and understanding the consequences of thermal mismatches between host and parasites. Applying the new information derived from these advances to climate–disease models and addressing the pressing knowledge gaps that we identify should improve the capacity to predict how climate change will affect disease risk for both wildlife and humans. 
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  6. null (Ed.)
  7. null (Ed.)
    The temperature-dependence of many important mosquito-borne diseases has never been quantified. These relationships are critical for understanding current distributions and predicting future shifts from climate change. We used trait-based models to characterize temperature-dependent transmission of 10 vector–pathogen pairs of mosquitoes ( Culex pipiens , Cx. quinquefascsiatus , Cx. tarsalis , and others) and viruses (West Nile, Eastern and Western Equine Encephalitis, St. Louis Encephalitis, Sindbis, and Rift Valley Fever viruses), most with substantial transmission in temperate regions. Transmission is optimized at intermediate temperatures (23–26°C) and often has wider thermal breadths (due to cooler lower thermal limits) compared to pathogens with predominately tropical distributions (in previous studies). The incidence of human West Nile virus cases across US counties responded unimodally to average summer temperature and peaked at 24°C, matching model-predicted optima (24–25°C). Climate warming will likely shift transmission of these diseases, increasing it in cooler locations while decreasing it in warmer locations. 
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