Predicting biodiversity responses to climate change remains a difficult challenge, especially in climatically complex regions where precipitation is a limiting factor. Though statistical climatic envelope models are frequently used to project future scenarios for species distributions under climate change, these models are rarely tested using empirical data. We used long-term data on bird distributions and abundance covering five states in the western US and in the Canadian province of British Columbia to test the capacity of statistical models to predict temporal changes in bird populations over a 32-year period. Using boosted regression trees, we built presence-absence and abundance models that related the presence and abundance of 132 bird species to spatial variation in climatic conditions. Presence/ absence models built using 1970-1974 data forecast the distributions of the majority of species in the later time period, 1998-2002 (mean AUC = 0.79 AE 0.01). Hindcast models performed equivalently (mean AUC = 0.82 AE 0.01). Correlations between observed and predicted abundances were also statistically significant for most species (forecast mean Spearman 0 s q = 0.34 AE 0.02, hindcast = 0.39 AE 0.02). The most stringent test is to test predicted changes in geographic patterns through time. Observed changes in abundance patterns were significantly positively correlated with those predicted for 59% of species (mean Spearman 0 s q = 0.28 AE 0.02, across all species). Three precipitation variables (for the wettest month, breeding season, and driest month) and minimum temperature of the coldest month were the most important predictors of bird distributions and abundances in this region, and hence of abundance changes through time. Our results suggest that models describing associations between climatic variables and abundance patterns can predict changes through time for some species, and that changes in precipitation and winter temperature appear to have already driven shifts in the geographic patterns of abundance of bird populations in western North America.

The structure and function of the soil microbiome of urban greenspaces remain largely undetermined. We conducted a global field survey in urban greenspaces and neighboring natural ecosystems across 56 cities from six continents, and found that urban soils are important hotspots for soil bacterial, protist and functional gene diversity, but support highly homogenized microbial communities worldwide. Urban greenspaces had a greater proportion of fast-growing bacteria, algae, amoebae, and fungal pathogens, but a lower proportion of ectomycorrhizal fungi than natural ecosystems. These urban ecosystems also showed higher proportions of genes associated with human pathogens, greenhouse gas emissions, faster nutrient cycling, and more intense abiotic stress than natural environments. City affluence, management practices, and climate were fundamental drivers of urban soil communities. Our work paves the way toward a more comprehensive global-scale perspective on urban greenspaces, which is integral to managing the health of these ecosystems and the well-being of human populations.

The Asian giant hornet (Vespa mandarinia) was recently detected in western British Columbia, Canada and Washington State, United States. V. mandarinia are an invasion concern due to their ability to kill honey bees and affect humans. Here, we used habitat suitability models and dispersal simulations to assess potential invasive spread of V. mandarinia. We show V. mandarinia are most likely to establish in areas with warm to cool annual mean temperature, high precipitation, and high human activity. The realized niche of introduced populations is small compared to native populations, suggesting introduced populations could spread into habitats across a broader range of environmental conditions. Dispersal simulations also show that V. mandarinia could rapidly spread throughout western North America without containment. Given its potential negative impacts and capacity for spread, extensive monitoring and eradication efforts throughout western North America are warranted.

1. Impacts of global change on the distribution, abundance, and phenology of species have been widely documented. In particular, recent climate change has led to widespread changes in animal and plant seasonality, leading to debate about its potential to cause phenological mismatches among interacting taxa. 2. In mountainous regions, populations of many species show pronounced phenological gradients over short geographic distances, presenting the opportunity to test for effects of climate on phenology, independent of variation in confounding factors such as photoperiod. 3. Here we show for 32 butterfly species sampled for five years over a 1700 m gradient (560–2260 m) in a Mediterranean mountain range that, on average, annual flight period is delayed with elevation by 15–22 days per kilometre. Species mainly occurring at low elevations in the region, and to some extent those flying earlier in the year, showed phenological delays of 23–36 days per kilometre, whereas the flight periods of species that occupy high elevations, or fly in late summer, were consistently more synchronised over the elevation gradient. 4. Elevational patterns in phenology appear to reflect a narrowing phenological window of opportunity for larval and adult butterfly activity of high elevation and late‐flying species. 5. Here, we speculate as to the causes of these patterns, and the consequences for our ability to predict species responses to climate change. Our results raise questions about the use of space–time substitutions in predicting phenological responses to climate change, since traits relating to flight period and environmental associations may influence the capacity of species to adapt to changing climates.

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Aim Models relating species distributions to climate or habitat are widely used to predict the effects of global change on biodiversity. Most such approaches assume that climate governs coarse-scale species ranges, whereas habitat limits fine-scale distributions. We tested the influence of topoclimate and land cover on butterfly distributions and abundance in a mountain range, where climate may vary as markedly at a fine scale as land cover. Location Sierra de Guadarrama (Spain, southern Europe)Methods We sampled the butterfly fauna of 180 locations (89 in 2004, 91 in 2005) in a 10,800 km 2 region, and derived generalized linear models (GLMs) for species occurrence and abundance based on topoclimatic (elevation and insolation) or habitat (land cover, geology and hydrology) variables sampled at 100-m resolution using GIS. Models for each year were tested against independent data from the alternate year, using the area under the receiver operating characteristic curve (AUC) (distribution) or Spearman's rank correlation coefficient (rs) (abundance). ResultsIn independent model tests, 74% of occurrence models achieved AUCs of > 0.7, and 85% of abundance models were significantly related to observed abundance. Topoclimatic models outperformed models based purely on land cover in 72% of occurrence models and 66% of abundance models. Including both types of variables often explained most variation in model calibration, but did not significantly improve model cross-validation relative to topoclimatic models. Hierarchical partitioning analysis confirmed the overriding effect of topoclimatic factors on species distributions, with the exception of several species for which the importance of land cover was confirmed.Main conclusions Topoclimatic factors may dominate fine-resolution species distributions in mountain ranges where climate conditions vary markedly over short distances and large areas of natural habitat remain. Climate change is likely to be a key driver of species distributions in such systems and could have important effects on biodiversity. However, continued habitat protection may be vital to facilitate range shifts in response to climate change.

While the contribution of biodiversity to supporting multiple ecosystem functions is well-established in natural ecosystems, the relationship of the above and belowground diversity with ecosystem multifunctionality remains virtually unknown in urban greenspaces. Here, we conducted a standardized survey of urban greenspaces from 56 municipalities across six continents, aiming to investigate the relationships of plant and soil biodiversity (diversity of bacteria, fungi, protists, and invertebrates, and metagenomics-based functional diversity) with 18 surrogates of ecosystem functions from nine ecosystem services. We found that soil biodiversity across biomes was significantly and positively correlated with multiple dimensions of ecosystem functions, and contributed to key ecosystem services such as microbial-driven carbon pools, organic matter decomposition, plant productivity, nutrient cycling, water regulation, plant-soil mutualism, plant pathogen control, and antibiotic resistance regulation. Plant diversity only indirectly influenced multifunctionality in urban greenspaces via changes in soil conditions that were associated with soil biodiversity. These findings were maintained after controlling for climate, spatial context, soil properties, vegetation, and management practices. This study provides solid evidence that conserving soil biodiversity in urban greenspaces is key to support multiple dimensions of ecosystem functioning, which is critical for the sustainability of urban ecosystems and human wellbeing.