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The genetics model system Arabidopsis thaliana (L.) Heynh. lives across a vast geographic range with contrasting climates, in response to which it has evolved diverse life histories and phenotypic adaptations. In the last decade, the cataloging of worldwide populations, DNA sequencing of whole genomes, and conducting of outdoor field experiments have transformed it into a powerful evolutionary ecology system to understand the genomic basis of adaptation. Here, we summarize new insights on Arabidopsis following the coordinated efforts of the 1001 Genomes Project, the latest reconstruction of biogeographic and demographic history, and the systematic genomic mapping of trait natural variation through 15 years of genome-wide association studies. We then put this in the context of local adaptation across climates by summarizing insights from 73 Arabidopsis outdoor common garden experiments conducted to date. We conclude by highlighting how molecular and genomic knowledge of adaptation can help us to understand species’ (mal)adaptation under ongoing climate change. 

Herbaceous plant species have been the focus of extensive, long-term research into climate change responses, but there has been little effort to synthesize results and predicted outlooks from different model species. We summarize research on climate change responses for eight intensively-studied herbaceous plant species. We establish generalities across species, examine limitations, interrogate biases, and propose a path forward. All six forb species exhibit reduced fitness, maladaptation, and/or population declines in at least part of the range. Plasticity alone is likely not sufficient to allow adjustment to shifting climates. Most model species also have spatially-restricted dispersal that may limit genetic and evolutionary rescue. These results are surprising, given that these species are widespread, span large elevation ranges, and generally have substantial levels of genetic and phenotypic variation. The focal species have diverse life histories, reproductive strategies, and habitats, but most are native to North America. Thus, these species may poorly represent rare species, habitat specialists, or species endemic to other parts of the world. We encourage researchers to design demographic and field experiments that evaluate plant traits and fitness in contemporary and potential future conditions across the full life cycle, and that consider the effects of climate change on biotic interactions. 

Anthropogenic habitat destruction and climate change are reshaping the geographic distribution of plants worldwide. However, we are still unable to map species shifts at high spatial, temporal, and taxonomic resolution. Here, we develop a deep learning model trained using remote sensing images from California paired with half a million citizen science observations that can map the distribution of over 2,000 plant species. Our model—Deepbiosphere—not only outperforms many common species distribution modeling approaches (AUC 0.95 vs. 0.88) but can map species at up to a few meters resolution and finely delineate plant communities with high accuracy, including the pristine and clear-cut forests of Redwood National Park. These fine-scale predictions can further be used to map the intensity of habitat fragmentation and sharp ecosystem transitions across human-altered landscapes. In addition, from frequent collections of remote sensing data,Deepbiospherecan detect the rapid effects of severe wildfire on plant community composition across a 2-y time period. These findings demonstrate that integrating public earth observations and citizen science with deep learning can pave the way toward automated systems for monitoring biodiversity change in real-time worldwide. 

Summary Herbaceous plant species have been the focus of extensive, long‐term research into climate change responses, but there has been little effort to synthesize results and predicted outlooks. This primer summarizes research on climate change responses for eight intensively studied herbaceous plant species. We establish generalities across species, examine limitations, and propose a path forward. Climate change has reduced fitness, caused maladaptation, and/or led to population declines in at least part of the range of all six forb species. Plasticity alone is likely not sufficient to allow adjustment to shifting climates. Most model species also have spatially restricted dispersal that may limit genetic and evolutionary rescue. These results are surprising, given that these species are generally widespread, span large elevation ranges, and have substantial genetic and phenotypic variation. The focal species have diverse life histories, reproductive strategies, and habitats, and most are native to North America. Thus, species that are rare, habitat specialists, or endemic to other parts of the world are poorly represented in this review. We encourage researchers to design demographic and field experiments that evaluate plant traits and fitness in contemporary and potential future conditions across the full life cycle, and that consider biotic interactions in climate change responses. 

Signals of local adaptation have been found in many plants and animals, highlighting the heterogeneity in the distribution of adaptive genetic variation throughout species ranges. In the coming decades, global climate change is expected to induce shifts in the selective pressures that shape this adaptive variation. These changes in selective pressures will likely result in varying degrees of local climate maladaptation and spatial reshuffling of the underlying distributions of adaptive alleles. There is a growing interest in using population genomic data to help predict future disruptions to locally adaptive gene-environment associations. One motivation behind such work is to better understand how the effects of changing climate on populations’ short-term fitness could vary spatially across species ranges. Here we review the current use of genomic data to predict the disruption of local adaptation across current and future climates. After assessing goals and motivations underlying the approach, we review the main steps and associated statistical methods currently in use and explore our current understanding of the limits and future potential of using genomics to predict climate change (mal)adaptation. Expected final online publication date for the Annual Review of Ecology, Evolution, and Systematics, Volume 51 is November 2, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

The potential for adaptive evolution to enable species persistence under a changing climate is one of the most important questions for understanding impacts of future climate change. Climate adaptation may be particularly likely for short-lived ectotherms, including many pest, pathogen, and vector species. For these taxa, estimating climate adaptive potential is critical for accurate predictive modeling and public health preparedness. Here, we demonstrate how a simple theoretical framework used in conservation biology—evolutionary rescue models—can be used to investigate the potential for climate adaptation in these taxa, using mosquito thermal adaptation as a focal case. Synthesizing current evidence, we find that short mosquito generation times, high population growth rates, and strong temperature-imposed selection favor thermal adaptation. However, knowledge gaps about the extent of phenotypic and genotypic variation in thermal tolerance within mosquito populations, the environmental sensitivity of selection, and the role of phenotypic plasticity constrain our ability to make more precise estimates. We describe how common garden and selection experiments can be used to fill these data gaps. Lastly, we investigate the consequences of mosquito climate adaptation on disease transmission using Aedes aegypti -transmitted dengue virus in Northern Brazil as a case study. The approach outlined here can be applied to any disease vector or pest species and type of environmental change. 

With growing populations and pressing environmental problems, future economies will be increasingly plant-based. Now is the time to reimagine plant science as a critical component of fundamental science, agriculture, environmental stewardship, energy, technology and healthcare. This effort requires a conceptual and technological framework to identify and map all cell types, and to comprehensively annotate the localization and organization of molecules at cellular and tissue levels. This framework, called the Plant Cell Atlas (PCA), will be critical for understanding and engineering plant development, physiology and environmental responses. A workshop was convened to discuss the purpose and utility of such an initiative, resulting in a roadmap that acknowledges the current knowledge gaps and technical challenges, and underscores how the PCA initiative can help to overcome them.