Ecography最新文献

Understanding how species' ecological partitioning functions across biomes is fundamental to macroecology and conservation biology. Here, we examine the global distribution of dietary strategies in terrestrial mammals, focusing on how biome specialization modulates trophic diversity and structure at a broad geographical scale. Using species-level data from over 3600 terrestrial mammal species, we constructed a multivariate dietary space and quantified the area, redundancy, dispersion, uniqueness, and turnover of trophic strategies across ten major biomes. Species were classified as biome specialists, moderate generalists, or extreme generalists based on their biome breadth. By analysing biome specialists and generalists separately, we show that biome specialists tend to exhibit more constrained and compositionally distinct dietary niches in less productive biomes, while generalists, particularly moderate generalists, dominate functional space occupancy in all biomes, even the harsher ones such as tundra and taiga. This highlights how environmental constraints and ecological roles shape trophic strategies at a global scale. Notably, extreme generalists tended to exhibit more carnivorous or insectivorous diets, suggesting a strategy based on mobile predation or opportunism rather than a highly diversified omnivory. Despite these general patterns, highly productive biomes supported the greatest diversity of dietary strategies, with higher functional redundancy and niche packing. Nestedness and turnover analyses revealed that biome specialists diets are often subsets of generalists diets, but with significant compositional shifts across biomes. These findings underscore the dual role of biome generalists as both functional stabilizers and potential limiters of ecological diversity, and highlight the vulnerability of specialist species to global change. Our study offers a mechanistic framework for understanding how dietary strategies interact with environmental filtering, and for identifying functional risks in changing ecosystems.

Extreme climatic events are increasing with climate change, producing changes in communities' climatic characterization. So, mismatches (climatic disequilibrium, CD) between climatic conditions inferred from species' requirements (community inferred climate, CIC) and macroclimate may undergo changes with extreme climatic events. Climatic resilience is defined as the ability to maintain or recover community climatic characteristics, regardless of species' identity, after disturbance or stress.

We evaluated the dynamics of plant community climatic characterization in Mediterranean shrublands that experienced a drought event, considering CIC and CD. CIC was calculated by averaging species' climatic niche centroids, weighted by species' relative abundances, in the multivariate environmental space obtained from the climate of the species' geographical occurrence. CD was estimated as Euclidean distance in this space between the observed historic macroclimate and CIC. Climatic resistance was inferred by the distance between pre-drought and drought CIC, climatic resilience by the distance between pre-drought and post-drought CIC, and relative climatic resilience by the same distance weighted by the climatic displacement suffered during the drought. We found a significant reduction in community CD after drought, with CIC becoming more arid, likely due to environmental filtering of those species with wetter distribution. Communities with less pre-drought CD showed higher climatic resistance but pre-drought CD did not explain climatic resilience. Communities with more arid CIC exhibited high climatic resilience regardless of drought impact (high relative climatic resilience), except for certain communities exhibiting highly arid CICs. Communities with less arid CIC showed low relative climatic resilience, as their resilience was associated with high resistance.

The study highlights community impacts by extreme droughts through filtering of species distributed in more humid climates. This produces changes in the CD of communities, whose resilience is determined by CIC, pre-drought CD, and drought impact in terms of CIC change.

Montane species utilize various habitats along elevations to adapt to seasonality, providing an ideal opportunity to study how species respond to shifting environments. This study characterizes seasonal changes in community structure and elevational distributions across multiple taxa in the Central Himalayas. We compared species richness, community co-occurrence network, and composition of mammals and birds across twelve 300-m elevational bands during the warm and cold seasons. We calculated seasonal shifts in the species elevational ranges, assessing how species traits influenced these shifts and testing the most widely accepted hypotheses for seasonal shifts in elevation distribution: the ‘food-limitation hypothesis' and the ‘climatic constraint hypothesis'. Simpler community network structures emerge during cold seasons, with distinct patterns observed across taxa. Mammals and birds exhibit a hump-shaped elevational pattern in species richness, with peak richness shifting to lower elevations in the cold season as high-elevation species moved downslope. Temporal beta diversity from warm to cold seasons were primarily caused by species losses rather than species gains in high- and middle-elevation communities for both taxa. High- and middle-elevation mammals and birds, as well as insectivorous birds, significantly shifted their upper elevational boundaries downslope in the cold season. Innovatively, we analyzed the seasonal distribution shifts of congeneric competing species to understand the interplay between abiotic and biotic factors in driving species' adaptive responses. From warm to cold season, high-elevation genera increased spatial separation while low-elevation genera decreased it, indicating that interspecies relationships adjust to environmental fluctuations and vary across contexts. This study provides empirical evidence of seasonal variations in community structure and species distributions across Himalayan taxa, highlighting how seasonality drives shift in species distributions across elevations and emphasizing the dynamic nature of elevational ranges over time. This variability underscores the need to incorporate elevational range flexibility into climate change research to understand climate-driven distribution shifts.

Globally, forest disturbances caused by herbivorous insects and plant pathogens (i.e. biotic disturbances) have increased since the 1990s, a trend linked in part to climate warming. With increases in biotic disturbance activity, an emerging ecological phenomenon has been documented: biotic disturbance ‘hotspots', or areas where two or more biotic disturbance agents co-occur in space and time. Biotic disturbance hotspots may have important implications for forest resilience, particularly if they erode mechanisms of post-disturbance forest recovery. The factors leading to hotspot occurrence, however, remain poorly understood. We characterized the patterns and drivers of biotic disturbance hotspots occurring from 2000 to 2020 across three broad forested regions in the western United States (US; the Southern Rockies, Middle Rockies, and Cascades). Using Bayesian spatio-temporal models, we evaluated whether hotspots can be predicted from predisposing factors expected to increase forest susceptibility to biotic disturbance (i.e. forest composition, topography, and average climate), as well as inciting factors known to trigger individual bark beetle and pathogen outbreaks (i.e. annual weather). Biotic disturbance hotspots exhibited distinct spatio-temporal patterns and trends within each region. Forest structure and composition were the strongest and most consistent drivers of hotspots. Other factors varied in their importance by region, reflecting regional differences in biophysical context. Relative to the predictor variables included in our models, estimated spatio-temporal random effects were more closely correlated with model predictions, suggesting that dynamic factors such as outbreak spread strongly shape patterns of biotic disturbance hotspots. Our results illustrate the widespread nature of biotic disturbance hotspots across western US coniferous forests and demonstrate the importance of forest structure and regional outbreak dynamics in anticipating hotspots at regional scales. These findings provide a deeper understanding of interacting forest disturbances and have important implications for the resilience of forests during a period marked by continued increases in disturbance activity.

Pelagic-feeding seabirds deliver nutrient subsidies that enhance the productivity, biodiversity, and resilience of terrestrial and marine ecosystems, particularly in nutrient-poor tropical environments. However, the biogeophysical variables governing the fluxes of these nutrients within and among interconnected ecosystems remain poorly understood. To address this, we examined the spatial distribution of seabird-vectored nutrients in the seascape of Tetiaroa, a semi-enclosed coral atoll in French Polynesia, where seabird populations and associated nutrient cycles are recovering after recent rat eradication. We focus on the nitrogen isotope (δ¹⁵N) signatures of a dominant marine alga as evidence of seabird-vectored nutrient uptake. Integrating stable isotope analysis within a seascape ecology framework, we show that breeding seabird biomass, depth, distance to land, geographic location within the atoll, and seafloor curvature drive spatial patterns of nutrient enrichment. Specifically, our models account for up to 88% of the variation in algal δ¹⁵N signatures and reveal peak enrichment in shallow, nearshore areas where water flow slows and converges due to localised seafloor curvature. These results extend previous research by highlighting seafloor geomorphology, notably curvature, as a modulator of fine-scale nutrient delivery patterns. Although a complex model incorporating 11 high-resolution biogeophysical variables enhanced spatial predictions by revealing fine-scale variations, a simpler model using only five of these variables was comparably effective in capturing overall spatial trends. This study identifies the key seascape configuration and complexity characteristics likely to affect the spatial patterns of recovery potential following the restoration of seabird-driven nutrient cycles, offering valuable guidance for ongoing restoration efforts in this coupled island-reef system. Future investigations could assess how the effects of biogeophysical variables on nutrient delivery vary in magnitude and direction across different geographic, geological, and anthropogenic contexts.

The core–periphery hypothesis (CPH) predicts that genetic diversity is greatest at the centre and lowest at the edges of a species' distribution because genetic diversity is a function of a species' abundance, which is also expected to be greatest at the centre and lowest at the edges of the distribution. Variants of the CPH include the ‘Ramped North' (greatest variation in the north), the ‘Ramped South' (greatest in the south), and the ‘Abundant Edge' (greatest at the distributional edges). Here, we present the first standardised multi-phylum analysis of the CPH using nine indices of genetic diversity for New Zealand's marine biota, covering 52 species. Based on 80 studies across eight phyla, spatial variation in the genetic indices was tested against four models (Normal (N), Ramped North (RN), Ramped South (RS), Abundant Edge (AE)). Only 22.7% of all individual taxon-specific tests were statistically significant: Ramped North (10.5%), Ramped South (7.4%), Abundant Edge (2.6%) and Normal (2.2%). Nonetheless, amongst the Chordata (Ramped North and Ramped South), Arthropoda (Ramped South) and Mollusca (Ramped North), a reasonably consistent pattern of genetic variation was observed within each phylum. Spatially-explicit genetic diversity of the remaining taxa fitted different models but without any obvious pattern across the phyla. Generalised binomial testing of observed p-values for each genetic index across all studies revealed that 10 of 29 tests were significant (5 RN, 2 N, 2 RS, 1 AE). Overall, our meta-analysis revealed no real support for the CPH and only limited support for a Ramped model (either Ramped North or Ramped South) of spatially-explicit genetic diversity. For New Zealand coastal marine taxa, we conclude that consistently strong patterns of genetic variation across multiple taxa do not exist and the CPH requires extensive testing from multiple other regions before we can say that such patterns exist, let alone explain them.

Determining population status to inform mitigation of anthropogenic threats requires statistical approaches that investigate spatial and temporal variation. In the face of climate change it is increasingly important to differentiate between changes in population size and redistributions of populations. This is especially true for wide-ranging species such as the blue whale. Abundance of eastern North Pacific blue whales has previously been estimated using (non-spatial) closed capture–recapture and distance sampling methods, but the estimates show opposite and diverging trends over the last 30 years. Evidence that the distribution has been expanding could explain the apparent disparity, due to the confounding effects of spatial variation in sampling and the changing distribution. To investigate this, we apply, for the first time, spatial capture–recapture (SCR) methods to blue whale photo-identification data from small boat surveys to estimate abundance. The study area was defined as the length of the continental USA coastline, extending approximately 100 km offshore. Average annual effort from 1991 to 2023 was 97 days, resulting in 7358 sightings of 1488 unique individuals. We find significant support for non-linear spatiotemporal variation. In all years, there were higher densities at lower latitudes but there were notable decadal cyclical fluctuations in the number of animals using the study area. This large variation in the numbers of animals using these waters motivates further study into the relationship with environmental changes. Our results are an important step in spatially explicit modelling of observational blue whale data, which highlight the value of including spatial and temporal data and are relevant to any marine mammal species monitored using photo-identification.

The high biodiversity in mountains is attributed to species accumulation from dispersal, high habitat heterogeneity and local speciation. Landscape connectivity thereby influences colonization and speciation processes, making its net effect on biodiversity challenging to understand. This is especially true for complex and biologically diverse mountain systems, such as the Hengduan Mountains (HDM), with their remarkably high levels of endemism. Here, we mapped the distributions of 3165 endemic plant species (25% of the region's total richness) in the HDM and studied the complex interplay between landscape connectivity and climate as drivers of endemic richness, as well as endemic compositional turnover. We found that endemic richness peaks at elevations of 3000 to 4000 m a.s.l., about 1000 m higher than that of overall richness. Mean temperature of the warmest quarter, climate change velocity since the Last Glacial Maximum, and connectivity together explain patterns of both α- and β-diversity of endemism. Our models show strong explanatory power along the elevation gradient and across the landscape. Our findings point to a distinct, context-dependent role of landscape connectivity in shaping biodiversity. In the endemic hotspot of the central-western HDM, particularly within the Three-Parallel-Rivers Region, endemic diversity indices are negatively associated with landscape connectivity. In contrast, we found a positive association between endemic richness and connectivity in the northern and southern HDM, which have overall lower endemism levels. This context-dependent effect of the connectivity–richness relationship highlights the complex influences of geomorphological processes on endemic patterns at a regional spatial scale.