Phylogenetic relatedness is often used as a proxy for ecological similarity in community and macroecological analyses. Yet whether phylogeny is informative about similarity in measured traits can vary among traits and species pools, while incomplete trait data may further affect the resulting inference. We developed ‘PNC', an R package that links trait data preparation and coverage assessment with phylogenetic signal analysis within focal species pools and across multiple communities. The package includes curated quantitative trait datasets for plants, birds, mammals, reptiles, amphibians, and fishes, and uses paired simulations to assess how observed missing data patterns influence Pagel's λ estimates and significance classifications for individual traits. Applications to the Barro Colorado Island (BCI) plant species pool and Himalayan bird communities showed that phylogenetic signal varied among traits, taxonomic levels, and local species pools. In both applications, significance classifications for the individual traits were generally stable under the observed missing data patterns. ‘PNC' therefore provides an integrated workflow for evaluating whether phylogeny is an informative proxy for measured trait similarity in the assemblage under study and how sensitive that inference is to incomplete trait data.
The theory of island biogeography (TIB) explains species richness patterns, yet its extension to compositional dissimilarity (β diversity), particularly from multidimensional perspectives, remains limited. Using butterfly assemblages across 44 land‐bridge islands in the Zhoushan Archipelago, China, we applied an integrative framework to unravel how island geography and species traits shape multi‐faceted β diversity. We partitioned taxonomic, phylogenetic, and functional β diversity into turnover and nestedness components, quantified species and site contributions, and distinguished roles of widespread versus restricted species. Key findings reveal: 1) dimensionality‐specific geographic drivers: inter‐island isolation differences primarily influenced nestedness in taxonomic and phylogenetic dimensions, suggesting its role as a filter for ordered species loss. In contrast, island area differences consistently affected both turnover and nestedness across all dimensions, underscoring its role as a master filter of resources and habitat. Island geographic attributes (e.g. isolation) only explained local community uniqueness in the taxonomic dimension. 2) A trait‐mediated mechanism: species with weaker dispersal capacity (smaller thorax area) contributed more to β diversity (higher species contribution), providing direct trait‐based evidence for dispersal limitation. 3) Internal metacommunity structure: nestedness was predominantly structured by widespread species, whereas turnover was driven mainly by the idiosyncratic distributions of restricted species. Our study demonstrates that island community assembly emerges from deterministic filtering (area and isolation shaping the widespread species backbone) interacting with stochastic processes (governing restricted species). This integrates TIB with β diversity by showing that TIB's core predictors (area and isolation) differentially shape the components of β diversity and offers a multidimensional, mechanistic framework for island conservation that emphasizes protecting island networks, source islands, and unique species and habitats.
Global warming is rapidly restructuring biological communities, yet terrestrial ecosystems often appear to lack the systematic climate‐driven signatures observed in marine realms. We hypothesise that this apparent idiosyncrasy arises from neglecting the geographic structure of climate. Using 1161 terrestrial community time series, we transitioned from geographic grids to a multidimensional climate space defined by temperature and precipitation. This framework allows climatic associations to be evaluated while accounting for climate‐space geometry by quantifying two key components: climate area and climate isolation. Using Bayesian hierarchical models, we evaluated how baseline climate and climate‐space geometry jointly shape temporal trends in richness, abundance, and evenness. While the average effect of warming on biodiversity appeared non‐significant, we found that terrestrial biodiversity responses varied systematically with baseline climate and climate‐space geometry. Species richness increased with warming in cooler climates but declined in the warmest regions. Furthermore, richness responses to warming became more positive in climatic regimes occupying larger areas, while the evenness response to warming depended on the interaction between climate area and isolation. Our findings identify the geography of climate as a critical link for understanding terrestrial biodiversity shifts. By treating climate as both an environmental condition and a spatial structure, we reveal coherent community responses to warming that were previously obscured in geographic space. These results suggest that conservation strategies benefit from looking beyond local temperature rates to consider the extent and connectivity of the climatic regimes being reshaped by climate change.
Elephants and other megaherbivores can strongly modify woody vegetation, yet their influence across heterogeneous landscapes and spatial scales remains poorly resolved. Here, we combined remotely sensed time series of vegetation height (2000–2022) and woody cover (2015–2025) with elephant population counts from 34 reserves across eight southern African countries to investigate the relationship between elephants and woody vegetation dynamics at local and landscape scales. To represent uneven within‐reserve use, we further used movement data from 315 GPS‐collared elephants to model habitat selection and estimate spatially explicit local densities in 15 reserves. Across reserves, vegetation height generally decreased whereas woody cover generally increased. Both trends varied nonlinearly with reserve‐average elephant density: reserves with 1–2 elephants km −2 experienced the fastest declines in height and increases in cover, whereas increases in woody cover were weak or absent at the highest observed densities (approximately three elephants km −2 ), although uncertainty was substantial. At the local scale (1 km 2 ), vegetation dynamics were most strongly linked to fire frequency and changes in rainfall, yet higher estimated elephant density was associated with faster declines in vegetation height and progressively weaker gains in woody cover; the fitted woody‐cover trend became negative at the highest local densities (≥ 4 elephants km −2 ). These results indicate that elephants, at sufficient densities, can slow down increases in woody cover and promote shifts toward shorter vegetation locally, but have less pronounced effects at the reserve scale. The latter may reflect low population densities or a balance between positive (seed dispersal, resprouting) and negative (browsing, stem breakage) impacts on woody vegetation. Overall, our findings show that elephants can maintain open savanna structure where densities, or local concentrations of landscape use, are sufficiently high, emphasizing the importance of protecting and restoring viable populations.
What determines the vast differences in species' abundance and distribution is a central question in ecology. Behavioural plasticity, the capacity to adjust behaviour to local conditions, is hypothesised to help species thrive, yet its role in shaping large‐scale patterns of ecological prosperity remains unclear. Using a phylogenetic comparative analysis of over 7000 bird species, we tested whether behavioural innovation, measured from literature reports of novel feeding behaviours, predicts two axes of prosperity, global population density and geographic range size. After accounting for phylogeny and a suite of life‐history and ecological traits, most innovation metrics were positively associated with both density and range size, whether innovation was scored as presence/absence or as a research‐effort‐corrected rate. Phylogenetic path analyses leaned towards innovation promoting prosperity rather than the reverse, strongly for the binary metric but only weakly for the innovation rate. Overall, our results identify behavioural plasticity as a predictor of avian macroecological patterns, operating alongside classic life‐history and ecological constraints. Recognising cognitive capacity as part of a species' ecological strategy offers insight into which species may be best equipped to persist on a rapidly changing planet.
