Ecography最新文献

Island ecosystems are particularly susceptible to the impacts of invasive species. Many rare and endangered species that are endemic to islands are negatively affected by invasions. Past studies have shown that the establishment of non-native species on islands is related to native plant richness, habitat heterogeneity, island age, human activity, and climate. However, it is unclear whether the factors promoting establishment (i.e. the formation of self-sustaining populations) also promote subsequent invasion (i.e. spread and negative impacts). Using data from 4308 non-native plant species across 46 islands and archipelagos globally, we examined which biogeographic characteristics influence established and invasive plant richness using generalized linear models nested within piecewise structural equation models. Our results indicate that anthropogenic land use (i.e. human modification) is strongly associated with establishment but not invasion, that climate (maximum monthly temperature) is strongly associated with invasion but not establishment, and that habitat heterogeneity (represented by maximum elevation and island area) is strongly associated with both establishment and invasion. Island isolation explains native plant richness well, but is not associated with established and invasive plant richness, likely due to anthropogenic introductions. We conclude that anthropogenic land use on islands is likely to be a proxy for the number of introductions (i.e. propagule pressure), which is more important for establishment than invasion. Conversely, islands with more diverse habitats and favorable (warm) climate conditions are likely to contain more available niche space (i.e. ‘vacant niches') which create opportunities for both establishment and invasion. By evaluating multiple stages of the invasion process, we differentiate between the biogeographic characteristics that influence plant establishment (which does not necessarily lead to ecological impacts) versus those that influence subsequent plant invasion (which does lead to negative impacts).

Every night during spring and autumn, the mass movement of migratory birds redistributes bird abundances found on the ground during the day. However, the connection between the magnitude of nocturnal migration and the resulting change in diurnal abundance remains poorly quantified. If departures and landings at the same location are balanced throughout the night, we expect high bird turnover but little change in diurnal abundance (stream-like migration). Alternatively, migrants may move simultaneously in spatial pulses, with well-separated areas of departure and landing that cause significant changes in the abundance of birds on the ground during the day (wave-like migration). Here, we apply a flow model to data from weather surveillance radars (WSR) to quantify the daily fluxes of nocturnally migrating birds landing and departing from the ground, characterizing the movement and stopover of birds in a comprehensive synoptic scale framework. We corroborate our results with independent observations of the diurnal abundances of birds on the ground from eBird. Furthermore, we estimate the abundance turnover, defined as the proportion of birds replaced overnight. We find that seasonal bird migration chiefly resembles a stream where bird populations on the ground are continuously replaced by new individuals. Large areas show similar magnitudes of take-off and landing, coupled with relatively small distances flown by birds each night, resulting in little change in bird densities on the ground. We further show that WSR-inferred landing and take-off fluxes predict changes in eBird-derived abundance turnover rate and turnover in species composition. We find that the daily turnover rate of birds is 13% on average but can reach up to 50% on peak migration nights. Our results highlight that WSR networks can provide real-time information on rapidly changing bird distributions on the ground. The flow model applied to WSR data can be a valuable tool for real-time conservation and public engagement focused on migratory birds' daytime stopovers.

Key Biodiversity Areas (KBAs) represent the largest global network of sites critical to the persistence of biodiversity, which have been identified against standardised quantitative criteria. Sites that hold very high biodiversity value or potential are given specific attention on site-based conservation targets of the Kunming-Montreal Global Biodiversity Framework (GBF), and KBAs are already used in indicators for the GBF and the Sustainable Development Goals. However, most of the species that trigger KBA status are birds and to maximise benefits for biodiversity under the actions taken to fulfil the GBF, countries need to update their KBAs to represent important sites across multiple taxa. Here we introduce KBAscope, an R package to identify potential KBAs using multiple taxonomic groups. KBAscope provides flexible, user-friendly functions to edit species data (population, range maps, area of occupancy, area of habitat and localities); apply KBA criteria; and generate outputs to support the delineation and validation of KBAs. The details of the analysis – such as the spatial units tested or the KBA criteria applied – can be decided according to the scope of the analysis. We demonstrate the functionality of KBAscope by using it to identify potential KBAs in Greece based on multiple terrestrial taxonomic groups and four sizes of grid cells (4 km², 25 km², 100 km², 225 km²).

Habitat selection models frequently use data collected from a small geographic area over a short window of time to extrapolate patterns of relative abundance into unobserved areas or periods of time. However, such models often poorly predict the distribution of animal space-use intensity beyond the place and time of data collection, presumably because space-use behaviors vary between individuals and environmental contexts. Similarly, ecological inference based on habitat selection models could be muddied or biased due to unaccounted individual and context dependencies. Here, we present a modeling workflow designed to allow transparent variance-decomposition of habitat-selection patterns, and consequently improved inferential and predictive capacities. Using global positioning system (GPS) data collected from 238 individual pronghorn, Antilocapra americana, across three years in Utah, USA, we combine individual-year-season-specific exponential habitat-selection models with weighted mixed-effects regressions to both draw inference about the drivers of habitat selection and predict space-use in areas/times where/when pronghorn were not monitored. We found a tremendous amount of variation in both the magnitude and direction of habitat selection behavior across seasons, but also across individuals, geographic regions, and years. We were able to attribute portions of this variation to season, movement strategy, sex, and regional variability in resources, conditions, and risks. We were also able to partition residual variation into inter- and intra-individual components. We then used the results to predict population-level, spatially and temporally dynamic, habitat-selection coefficients across Utah, resulting in a temporally dynamic map of pronghorn distribution at a 30 × 30 m resolution but an extent of 220 000 km². We believe our transferable workflow can provide managers and researchers alike a way to turn limitations of traditional habitat selection models – variability in habitat selection – into a tool to understand and predict species-habitat associations across space and time.

Animal movement and population connectivity are key areas of uncertainty in efforts to understand and predict the spread of infectious disease. The emergence of highly pathogenic avian influenza (HPAI) in South America poses a significant threat to globally significant populations of colonial breeding marine predators in the South Atlantic. Yet, there is a poor understanding of which species or migratory pathways may facilitate disease spread. Compiling one of the largest available animal tracking datasets in the South Atlantic, we examine connectivity and inter-population mixing for colonial breeding marine predators tagged at the Falkland Islands. We reveal extensive connectivity for three regionally dominant and gregarious species over the Patagonian Shelf. Black-browed albatrosses (BBA), South American fur seals (SAFS) and Magellanic penguins (MAG) used coastal waters along the Atlantic coast of South America (Argentina and Uruguay). These behaviours were recorded at or in close proximity to breeding colonies and haul-out areas with dense aggregations of marine predators. Transit times to and from the Falkland Islands to the continental coast ranged from 0.2–70 days, with 84% of animals making this transit within 4 days - a conservative estimate for HPAI infectious period. Our findings demonstrate BBA, SAFS and MAG connectivity between the Falkland Islands and mainland South America over an expansive spatial network and numerous pathways, which has implications for infectious disease persistence, transmission and spread. This information is vital in supporting HPAI disease surveillance, risk assessment and marine management efforts across the region.

Feedbacks are the basic linkages of living systems. In organisms, they regulate the processes of growth and homeostasis, as well as their interactions with their world. Feedback, which Judson (1980) called ‘one of the chief themes of scientific understanding,' is equally important in ecological systems. The ecological literature is rich in papers dealing with the role of feedback in various phenomena. However, we know of no comprehensive synthesis of feedbacks in ecology. Pichon et al. (2024) accomplish this, and for the first time show that ecological feedbacks can be categorized in terms of a small number of fundamental attributes. The paper brings the array of different types of feedbacks into a manageable order, providing not only the relevant theoretical framework but also guidance on methods for applying understanding to practical issues.

Evidence of large-scale biodiversity degradation in marine ecosystems has been reported worldwide, yet most research has focused on few species of interest or on limited spatiotemporal scales. Here we assessed the spatial and temporal changes in the taxonomic and functional composition of fish communities in European seas over the last 25 years (1994–2019). We then explored how these community changes were linked to environmental gradients and fishing pressure. We show that the spatial variation in fish species composition is more than two times higher than the temporal variation, with a marked spatial continuum in taxonomic composition and a more homogenous pattern in functional composition. The regions warming the fastest are experiencing an increasing dominance and total abundance of r-strategy fish species (lower age of maturity). Conversely, regions warming more slowly show an increasing dominance and total abundance of K-strategy species (high trophic level and late reproduction). Among the considered environmental variables, sea surface temperature, surface salinity and chlorophyll-a most consistently influenced communities' spatial patterns, while bottom temperature and oxygen had the most consistent influence on temporal patterns. Changes in communities' functional composition were more closely related to environmental conditions than taxonomic changes. Our study demonstrates the importance of integrating community-level species traits across multi-decadal scales and across a large region to better capture and understand ecosystem-wide responses and provides a different lens on community dynamics that could be used to support sustainable fisheries management.

The proportion of people living in urban areas is growing globally. Understanding how to manage urban biodiversity, ecosystem functions, and ecosystem services is becoming more important. Biodiversity can increase ecosystem functioning in non-urban systems. However, few studies have reviewed the relationship between biodiversity and ecosystem functioning in urban areas, which differ in species compositions, abiotic environments, food webs, and turnover rates. We reviewed evidence of biodiversity–ecosystem functioning relationships in urban environments and assessed factors that influence the relationship direction. Based on 70 studies, relationships between biodiversity and ecosystem functioning were more positive than negative in urban areas, especially for pollination and nutrient cycling and retention. Surprisingly, positive and negative relationships between biodiversity and biomass production and storage were equally not statistically different, perhaps due to extensive plant management in urban areas. The number of studies and geographic coverage of our review was still insufficient to provide a general predictive framework for when biodiversity positively impacts ecosystem functioning. We identify gaps and opportunities to improve urban biodiversity–ecosystem functioning research and discuss how our findings can improve urban green space management.