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Wind disperses the pollen and seeds of many plants, but little is known about whether and how it shapes large-scale landscape genetic patterns. We address this question by a synthesis and reanalysis of genetic data from more than 1,900 populations of 97 tree and shrub species around the world, using a newly developed framework for modeling long-term landscape connectivity by wind currents. We show that wind shapes three independent aspects of landscape genetics in plants with wind pollination or seed dispersal: populations linked by stronger winds are more genetically similar, populations linked by directionally imbalanced winds exhibit asymmetric gene flow ratios, and downwind populations have higher genetic diversity. For each of these distinct hypotheses, partial correlations between the respective wind and genetic metrics (controlling for distance and climate) are positive for a significant majority of wind-dispersed or wind-pollinated genetic data sets and increase significantly across functional groups expected to be increasingly influenced by wind. Together, these results indicate that the geography of both wind strength and wind direction play important roles in shaping large-scale genetic patterns across the world's forests. These findings have implications for various aspects of basic plant ecology and evolution, as well as the response of biodiversity to future global change.

Quantitative knowledge of xylem physical tolerance limits to dehydration is essential to understanding plant drought tolerance but is lacking in many long-vessel angiosperms. We examine the hypothesis that a fundamental association between sustained xylem water transport and downstream tissue function should select for xylem that avoids embolism in long-vessel trees by quantifying xylem capacity to withstand air entry of western North American oaks (Quercus spp.). Optical visualization showed that 50% of embolism occurs at water potentials below -2.7 MPa in all 19 species, and -6.6 MPa in the most resistant species. By mapping the evolution of xylem vulnerability to embolism onto a fossil-dated phylogeny of the western North American oaks, we found large differences between clades (sections) while closely related species within each clade vary little in their capacity to withstand air entry. Phylogenetic conservatism in xylem physical tolerance, together with a significant correlation between species distributions along rainfall gradients and their dehydration tolerance, suggests that closely related species occupy similar climatic niches and that species' geographic ranges may have shifted along aridity gradients in accordance with their physical tolerance. Such trends, coupled with evolutionary associations between capacity to withstand xylem embolism and other hydraulic-related traits, yield wide margins of safety against embolism in oaks from diverse habitats. Evolved responses of the vascular system to aridity support the embolism avoidance hypothesis and reveal the importance of quantifying plant capacity to withstand xylem embolism for understanding function and biogeography of some of the Northern Hemisphere's most ecologically and economically important plants.

Premise of the Study:Herbarium specimens are increasingly used as records of plant flowering phenology. However, most herbarium-based studies on plant phenology focus on taxa from temperate regions. Here, we explore flowering phenologic responses to climate in the subtropical plant genus Protea (Proteaceae), an iconic group of plants that flower year-round and are endemic to subtropical Africa. Methods:We present a novel, circular sliding window approach to investigate phenological patterns developed for species with year-round flowering. We employ our method to evaluate the extent to which site-to-site and year-to-year variation in temperature and precipitation affect flowering dates using a database of 1727 herbarium records of 25 Protea species. We also explore phylogenetic conservatism in flowering phenology. Results:We show that herbarium data combined with our sliding window approach successfully captured independently reported flowering phenology patterns (r = 0.93). Both warmer sites and warmer years were associated with earlier flowering of 3-5 days/°C, whereas precipitation variation had no significant effect on flowering phenology. Although species vary widely in phenological responsiveness, responses are phylogenetically conserved, with closely related species tending to shift flowering similarly with increasing temperature. Discussion:Our results point to climate-responsive phenology for this important plant genus and indicate that the subtropical, aseasonally flowering genus Protea has temperature-driven flowering responses that are remarkably similar to those of better-studied northern temperate plant species, suggesting a generality across biomes that has not been described elsewhere.

Biodiversity is often described as having multiple facets, including species richness, functional diversity and phylogenetic diversity. In this paper, we argue that phylogenetic diversity itself has three distinct facets-lineage diversification, character divergence and survival time-that can be quantified using distinct branch length metrics on an evolutionary tree. Each dimension is related to different processes of macroevolution, has different spatial patterns and is tied to distinct goals for conserving biodiversity and protecting its future resilience and evolutionary potential. We compared the landscapes identified as top conservation priorities by each of these three metrics in a conservation gap analysis for California, a world biodiversity hotspot, using herbarium data on the biogeography and evolutionary relationships of more than 5000 native plant species. Our analysis incorporated a novel continuous metric of current land protection status, fine-scale data on landscape intactness and an optimization algorithm used to identify complementary priority sites containing concentrations of taxa that are evolutionarily unique, vulnerable due to small range size and/or poorly protected across their ranges. Top conservation priorities included pockets of coastal and northern California that ranked highly for all three phylodiversity dimensions and for species richness, as well as sites uniquely identified by each metric whose value may depend on whether properties such as genetic divergence, high net diversification or independent survival experience are most desirable in an Anthropocene flora.This article is part of the theme issue 'Biological collections for understanding biodiversity in the Anthropocene'.

Fine‐scale spatial climate variation fosters biodiversity and buffers it from climate change, but ecological studies are constrained by the limited accessibility of relevant fine‐scale climate data. In this paper we introduce a novel form of species distribution model that uses species occurrences to predict high‐resolution climate variation. This new category of 'bioclimate' data, representing micro‐scale climate as experienced by one or more species of interest, is a useful complement to microclimate data from existing approaches. The modeling method, called BISHOP for 'bioclimate inference from species' high‐resolution occurrence patterns,' uses data on species occurrences, coarse‐scale climate, and fine‐scale physiography (e.g. terrain, soil, vegetation) to triangulate fine‐scale bioclimate patterns. It works by pairing a climate‐downscaling function predicting a latent bioclimate variable, with a niche function predicting species occurrences from bioclimate. BISHOP infers how physiography affects bioclimate, estimates how these effects vary geographically, and produces high‐resolution (10 m) maps of bioclimate over large regions. It also predicts species distributions. After introducing this approach, we apply it in an empirical study focused on topography and trees. Using data on 216 North American tree species, we document the biogeographic patterns that enable BISHOP, estimate how four terrain variables (northness, eastness, windward exposure, and elevational position) each influence three climate variables, and use these results to produce downscaled maps of tree‐specific bioclimate. Model validation demonstrates that inferred bioclimate outperforms macroclimate in predicting distributions of separate species not used during inference, confirming its ecological relevance. Our results show that nearby bioclimates can differ by 5°C in temperature and twofold in moisture, with equator‐facing, east‐facing, windward‐facing, and locally elevated sites exhibiting hotter, drier bioclimates on average. But these effects vary greatly across climate zones, revealing that topographically similar landscapes can differ strongly in their bioclimate variation. These results have important implications for micrometeorology, biodiversity, and climate resilience. [ABSTRACT FROM AUTHOR]

Biodiversity is often described as having multiple facets, including species richness, functional diversity and phylogenetic diversity. In this paper, we argue that phylogenetic diversity itself has three distinct facets-lineage diversification, character divergence and survival time-that can be quantified using distinct branch length metrics on an evolutionary tree. Each dimension is related to different processes of macroevolution, has different spatial patterns and is tied to distinct goals for conserving biodiversity and protecting its future resilience and evolutionary potential. We compared the landscapes identified as top conservation priorities by each of these three metrics in a conservation gap analysis for California, a world biodiversity hotspot, using herbarium data on the biogeography and evolutionary relationships of more than 5000 native plant species. Our analysis incorporated a novel continuous metric of current land protection status, fine-scale data on landscape intactness and an optimization algorithm used to identify complementary priority sites containing concentrations of taxa that are evolutionarily unique, vulnerable due to small range size and/or poorly protected across their ranges. Top conservation priorities included pockets of coastal and northern California that ranked highly for all three phylodiversity dimensions and for species richness, as well as sites uniquely identified by each metric whose value may depend on whether properties such as genetic divergence, high net diversification or independent survival experience are most desirable in an Anthropocene flora.This article is part of the theme issue 'Biological collections for understanding biodiversity in the Anthropocene'.

A large number of published ecological studies fail to include basic information about the climate data used. In the interest of reproducibility and transparency, we offer recommendations for best practices that we urge Editors, authors, and reviewers to adopt in future publications.

BackgroundCalifornia is a world floristic biodiversity hotspot where the terms neo- and paleo-endemism were first applied. Using spatial phylogenetics, it is now possible to evaluate biodiversity from an evolutionary standpoint, including discovering significant areas of neo- and paleo-endemism, by combining spatial information from museum collections and DNA-based phylogenies. Here we used a distributional dataset of 1.39 million herbarium specimens, a phylogeny of 1083 operational taxonomic units (OTUs) and 9 genes, and a spatial randomization test to identify regions of significant phylogenetic diversity, relative phylogenetic diversity, and phylogenetic endemism (PE), as well as to conduct a categorical analysis of neo- and paleo-endemism (CANAPE).ResultsWe found (1) extensive phylogenetic clustering in the South Coast Ranges, southern Great Valley, and deserts of California; (2) significant concentrations of short branches in the Mojave and Great Basin Deserts and the South Coast Ranges and long branches in the northern Great Valley, Sierra Nevada foothills, and the northwestern and southwestern parts of the state; (3) significant concentrations of paleo-endemism in Northwestern California, the northern Great Valley, and western Sonoran Desert, and neo-endemism in the White-Inyo Range, northern Mojave Desert, and southern Channel Islands. Multiple analyses were run to observe the effects on significance patterns of using different phylogenetic tree topologies (uncalibrated trees versus time-calibrated ultrametric trees) and using different representations of OTU ranges (herbarium specimen locations versus species distribution models).ConclusionsThese analyses showed that examining the geographic distributions of branch lengths in a statistical framework adds a new dimension to California floristics that, in comparison with climatic data, helps to illuminate causes of endemism. In particular, the concentration of significant PE in more arid regions of California extends previous ideas about aridity as an evolutionary stimulus. The patterns seen are largely robust to phylogenetic uncertainty and time calibration but are sensitive to the use of occurrence data versus modeled ranges, indicating that special attention toward improving geographic distributional data should be top priority in the future for advancing understanding of spatial patterns of biodiversity.

Premise of the studyCalifornia's vascular flora is the most diverse and threatened in temperate North America. Previous studies of spatial patterns of Californian plant diversity have been limited by traditional metrics, non-uniform geographic units, and distributional data derived from floristic descriptions for only a subset of species.MethodsWe revisited patterns of sampling intensity, species richness, and relative endemism in California based on equal-area spatial units, the full vascular flora, and specimen-based distributional data. We estimated richness, weighted endemism (inverse range-weighting of species), and corrected weighted endemism (weighted endemism corrected for richness), and performed a randomization test for significantly high endemism.Key resultsPossible biases in herbarium data do not obscure patterns of high richness and endemism at the spatial resolution studied. High species richness was sometimes associated with significantly high endemism (e.g., Klamath Ranges) but often not. In Stebbins and Major's (1965) main endemism hotspot, Southwestern California, species richness is high across much of the Peninsular and Transverse ranges but significantly high endemism is mostly localized to the Santa Rosa and San Bernardino mountains. In contrast, species richness is low in the Channel Islands, where endemism is significantly high, as also found for much of the Death Valley region.ConclusionsMeasures of taxonomic richness, even with greater weighting of range-restricted taxa, are insufficient for identifying areas of significantly high endemism that warrant conservation attention. Differences between our findings and those in previous studies appear to mostly reflect the source and scale of distributional data, and recent analytical refinements.

The impacts of climate change have re‐energized interest in understanding the role of climate in setting species geographic range edges. Despite the strong focus on species' distributions in ecology and evolution, defining a species range edge is theoretically and empirically difficult. The challenge of determining a range edge and its relationship to climate is in part driven by the nested nature of geography and the multidimensionality of climate, which together generate complex patterns of both climate and biotic distributions across landscapes. Because range‐limiting processes occur in both geographic and climate space, the relationship between these two spaces plays a critical role in setting range limits. With both conceptual and empirical support, we argue that three factors—climate heterogeneity, collinearity among climate variables, and spatial scale—interact to shape the spatial structure of range edges along climate gradients, and we discuss several ways that these factors influence the stability of species range edges with a changing climate. We demonstrate that geographic and climate edges are often not concordant across species ranges. Furthermore, high climate heterogeneity and low climate collinearity across landscapes increase the spectrum of possible relationships between geographic and climatic space, suggesting that geographic range edges and climatic niche limits correspond less frequently than we may expect. More empirical explorations of how the complexity of real landscapes shapes the ecological and evolutionary processes that determine species range edges will advance the development of range limit theory and its applications to biodiversity conservation in the context of changing climate. [ABSTRACT FROM AUTHOR]

Crop switching, in which farmers grow a crop that is novel to a given field, can help agricultural systems adapt to changing environmental, cultural, and market forces. Yet while regional crop production trends receive significant attention, relatively little is known about the local-scale crop switching that underlies these macrotrends. We characterized local crop-switching patterns across the United States using the US Department of Agriculture (USDA) Cropland Data Layer, an annual time series of high resolution (30 m pixel size) remote-sensed cropland data from 2008 to 2022. We found that at multiple spatial scales, crop switching was most common in sparsely cultivated landscapes and in landscapes with high crop diversity, whereas it was low in homogeneous, highly agricultural areas such as the Midwestern corn belt, suggesting a number of potential social and economic mechanisms influencing farmers' crop choices. Crop-switching rates were high overall, occurring on more than 6% of all US cropland in the average year. Applying a framework that classified crop switches based on their temporal novelty (crop introduction versus discontinuation), spatial novelty (locally divergent versus convergent switching), and categorical novelty (transformative versus incremental switching), we found distinct spatial patterns for these three novelty dimensions, indicating a dynamic and multifaceted set of cropping changes across US farms. Collectively, these results suggest that innovation through crop switching is playing out very differently in various parts of the country, with potentially significant implications for the resilience of agricultural systems to changes in climate and other systemic trends., Competing Interests: Competing interests statement:The authors declare no competing interest.

Stochastic diffusion is the noisy and uncertain process through which dynamics like epidemics, or agents like animal species, disperse over a larger area. Understanding these processes is becoming increasingly important as we attempt to better prepare for potential pandemics and as species ranges shift in response to climate change. Unfortunately, modeling of stochastic diffusion is mostly done through inaccurate deterministic tools that fail to capture the random nature of dispersal or else through expensive computational simulations. In particular, standard tools fail to fully capture the heterogeneity of the area over which this diffusion occurs. Rural areas with low population density require different epidemic models than urban areas; likewise, the edges of a species range require us to explicitly track low integer numbers of individuals rather than vague averages. In this work, we introduce a series of new tools called "mean-FLAME" models that track stochastic dispersion using approximate master equations that explicitly follow the probability distribution of an area of interest over all of its possible states, up to states that are active enough to be approximated using a mean-field model. In one limit, this approach is locally exact if we explicitly track enough states, and in the other limit collapses back to traditional deterministic models if we track no state explicitly. Applying this approach, we show how deterministic tools fail to capture the uncertainty around the speed of nonlinear dynamical processes. This is especially true for marginal areas that are close to unsuitable for diffusion, like the edge of a species range or epidemics in small populations. Capturing the uncertainty in such areas is key to producing accurate forecasts and guiding potential interventions.