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1. Evolution of a Model System: New Insights from the Study of Anolis Lizards

   https://doi.org/10.1146/annurev-ecolsys-110421-103306  

   Muñoz, Martha M.; Frishkoff, Luke O.; Pruett, Jenna; Mahler, D. Luke (November 2023, Annual Review of Ecology, Evolution, and Systematics)

   With decades of intensive study, Anolis lizards have emerged as a biological model system. We review how new research on anoles has advanced our understanding of ecology and evolution, challenging long-standing paradigms and opening new areas of inquiry. Recent anole research reveals how changes in behavior can restructure ecological communities and can both stimulate and stymie evolution, sometimes simultaneously. Likewise, investigation of anoles as spatial or phylogenetic evolutionary experiments has documented evolutionary repeatability across spatiotemporal scales, while also illuminating its limits. Current research places anoles as an emerging model for Anthropocene biology, with recent work illustrating how species respond as humans reconfigure natural habitats, alter the climate, and create novel environments and communities through urbanization and species introduction. Combined with ongoing methodological developments in genomics, phylogenetics, and ecology, the growing foundational knowledge of Anolis positions them as a powerful model system in ecology and evolution for years to come. Expected final online publication date for the Annual Review of Ecology, Evolution, and Systematics, Volume 54 is November 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

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2. Characterizing tree trait variance over spatiotemporal scales

   https://doi.org/10.1002/ecy.4126  

   Umaña, Maria Natalia; Hulshof, Catherine M. (June 2023, Ecology)

   Abstract Beyond the study of the mean, functional ecology lacks a concise characterization of trait variance patterns across spatiotemporal scales. Traits are measured in different ways, using different metrics, and at different spatial (and rarely temporal) scales. This study expands on previous research by applying a ubiquitous and widely used empirical model—Taylor's Power Law—to functional trait variance with the goal of identifying general patterns of trait variance scaling (the behavior of trait variance across scales). We compiled data on tree seedling communities monitored over 10 years across 213 2 m²plots and functional trait data from a subtropical forest in Puerto Rico. We examined trait‐based Taylor's Power Law at nested spatial and temporal scales. The scaling of variance with the mean was idiosyncratic across traits suggesting that the drivers of variation are likely to differ across traits that may make variance scaling theory elusive. However, slopes varied more in space than through time, suggesting that spatial environmental variability may have a larger role in driving trait variance than temporal variability. Empirical models that characterize taxonomic patterns across spatiotemporal scales, like Taylor's Power Law, can provide an insight into the scaling of functional traits, a necessary next step toward a more predictive trait‐based ecology. 

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3. Characterizing biological responses to climate variability and extremes to improve biodiversity projections

   https://doi.org/10.1371/journal.pclm.0000226  

   Buckley, Lauren B.; Carrington, Emily; Dillon, Michael E.; García-Robledo, Carlos; Roberts, Steven B.; Wegrzyn, Jill L.; Urban, Mark C. (June 2023, PLOS Climate)

   Moura, Mario R. (Ed.)

   Projecting ecological and evolutionary responses to variable and changing environments is central to anticipating and managing impacts to biodiversity and ecosystems. Current modeling approaches are largely phenomenological and often fail to accurately project responses due to numerous biological processes at multiple levels of biological organization responding to environmental variation at varied spatial and temporal scales. Limited mechanistic understanding of organismal responses to environmental variability and extremes also restricts predictive capacity. We outline a strategy for identifying and modeling the key organismal mechanisms across levels of biological organization that mediate ecological and evolutionary responses to environmental variation. A central component of this strategy is quantifying timescales and magnitudes of climatic variability and how organisms experience them. We highlight recent empirical research that builds this information and suggest how to design future experiments that can produce more generalizable principles. We discuss how to create biologically informed projections in a feasible way by combining statistical and mechanistic approaches. Predictions will inform both fundamental and practical questions at the interface of ecology, evolution, and Earth science such as how organisms experience, adapt to, and respond to environmental variation at multiple hierarchical spatial and temporal scales. 

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4. Characterizing biological responses to climate variability and extremes to improve biodiversity projections

   Buckley, L.; Carrington, E.; Dillon, M.E.; Garcia-Robledo, C; Roberts, S.B; Wegrzyn, J.; Urban, M.C. (June 2023, PLOS climate)

   Projecting ecological and evolutionary responses to variable and changing environments is central to anticipating and managing impacts to biodiversity and ecosystems. Current model- ing approaches are largely phenomenological and often fail to accurately project responses due to numerous biological processes at multiple levels of biological organization responding to environmental variation at varied spatial and temporal scales. Limited mechanistic under- standing of organismal responses to environmental variability and extremes also restricts predictive capacity. We outline a strategy for identifying and modeling the key organismal mechanisms across levels of biological organization that mediate ecological and evolutionary responses to environmental variation. A central component of this strategy is quantifying timescales and magnitudes of climatic variability and how organisms experience them. We highlight recent empirical research that builds this information and suggest how to design future experiments that can produce more generalizable principles. We discuss how to create biologically informed projections in a feasible way by combining statistical and mechanistic approaches. Predictions will inform both fundamental and practical questions at the interface of ecology, evolution, and Earth science such as how organisms experience, adapt to, and respond to environmental variation at multiple hierarchical spatial and temporal scales. 

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5. Variation in the strength of local and regional determinants of herbivory across the Neotropics

   https://doi.org/10.1111/oik.10218  

   Joy Massad, Tara; Rangel Nascimento, André; Fernando Campos Moreno, Diego; Simbaña, Wilmer; Garcia Lopez, Humberto; Sulca, Lidia; Lepesqueur, Cintia; Richards, Lora A.; Forister, Matthew L.; Stireman, John O.; et al (December 2023, Oikos)

   Insect herbivory can be an important selective pressure and contribute substantially to local plant richness. As herbivory is the result of numerous ecological and evolutionary processes, such as complex insect population dynamics and evolution of plant antiherbivore defenses, it has been difficult to predict variation in herbivory across meaningful spatial scales. In the present work, we characterize patterns of herbivory on plants in a species‐rich and abundant tropical genus (Piper) across forests spanning 44° of latitude in the Neotropics. We modeled the effects of geography, climate, resource availability, andPiperspecies richness on the median, dispersion, and skew of generalist and specialist herbivory. By examining these multiple components of the distribution of herbivory, we were able to determine factors that increase biologically meaningful herbivory at the upper ends of the distribution (indicated by skew and dispersion). We observed a roughly twofold increase in median herbivory in humid relative to seasonal forests, which aligns with the hypothesis that precipitation seasonality plays a critical role in shaping interaction diversity within tropical ecosystems. Site level variables such as latitude, seasonality, and maximumPiperrichness explained the positive skew in herbivory at the local scale (plot level) better for assemblages ofPipercongeners than for a single species. Predictors that varied between local communities, such as resource availability and diversity, best explained the distribution of herbivory within sites, dampening broad patterns across latitude and climate and demonstrating why generalizations about gradients in herbivory have been elusive. The estimated population means, dispersion, and skew of herbivory responded differently to abiotic and biotic factors, illustrating the need for careful studies to explore distributions of herbivory and their effects on forest diversity. 

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