Ecography最新文献

The availability of online biodiversity data has increased in recent decades, aiding our understanding of diversity patterns and species richness–environment relationships across temporal and spatial scales. However, even the most exhaustive databases are prone to sampling biases, which create knowledge gaps in species distributions and increase uncertainty in model predictions. Regarding marine environments, intertidal zones are globally distributed and considered early warning systems for climate change impacts and species' range shifts. Owing to their relative accessibility, intertidal records should – supposedly – be less incomplete and biased compared to open-ocean and deep-sea areas. Yet, the extent and coverage of intertidal records available in global biodiversity databases remains unknown. In this study, we used a high-resolution worldwide tidal flat map to identify intertidal records of 11 563 benthic species from the OBIS (Ocean Biodiversity Information System) portal. Following a thorough data-cleaning process, we evaluated geographic patterns in observed species richness, site accessibility, sampling effort, and inventory completeness across latitudes. We demonstrate that observed species richness has mid-latitudinal peaks while the tropics accumulate species with missing records, similar to patterns described for the entire marine realm. These patterns correlate with disproportionate mid-latitude sampling efforts and poor tropical sampling coverage. Sixty-five percent of the mapped intertidal sites are located within 3 hours of a city, but sampling records remain almost absent along African Atlantic, South American Pacific, and Indo-Pacific coasts. Thus, even for the accessible and well-studied intertidal shorelines, database records are not free from geographical biases and their associated implications for biodiversity estimates. Our results highlight the need for a better data-sharing culture, and we hope to encourage initiatives promoting more and better-distributed research efforts on intertidal biodiversity, which could improve global scale detection and prediction of climate change impacts at regional and global scales.

In migratory insects performing multigenerational migration, such as the painted lady butterfly Vanessa cardui, successive generations face a wide variety of predator communities and may be subject to different predation risks. Here, we analyze the pattern of wing damage of over 2000 butterflies to investigate, for the first time, the risk of predation of adult painted ladies across a latitudinal range of ca 3500 km extending from the northern Mediterranean through the Maghreb to sub-Saharan West Africa. Large number of butterflies showed substantial wing damage attributable to failed attacks, with birds, mantids and lizards being the most likely predators. The risk of attack increased towards the equator, even after controlling for wing wear. In addition, there was a strong effect of butterfly size on predation risk, with larger butterflies facing a higher risk compared to their smaller counterparts, and clear evidence that females suffered more attacks than males. Although size is a major factor, latitude was a stronger predictor of predation risk across the migratory system, as evidenced by greater wing damage in butterflies at lower latitudes, even though their size notably decreased. These results raise an interesting evolutionary conflict, with a tradeoff between size and predation risk, as larger butterflies are likely to be more fecund and efficient in migratory flight but, at the same time, more vulnerable to predation.

Co-occurrence networks offer insights into the complexity of microbial interactions, particularly in highly diverse environments where direct observation is challenging. However, identifying the scale at which local and non-local processes structure co-occurrence networks remains challenging because it requires simultaneously analyzing network structure within and between local networks. In this context, the rumen microbiome is an excellent model system because each cow contains a physically confined microbial community, which is imperative for the host's livelihood and productivity. Employing the rumen microbiome of 1012 cows across seven European farms as our model system, we constructed and analyzed farm-level co-occurrence networks to reveal underlying microbial interaction patterns. Within each farm, microbes tended to close triangles but some microbial families were over-represented while others under-represented in these local interactions. Using stochastic block modeling we detected a group structure that reflected functional equivalence in co-occurrence. Knowing the group composition in one farm provided significantly more information on the grouping in another farm than expected. Moreover, microbes strongly conserved co-occurrence patterns across farms (also adjusted for phylogeny). We developed a meta-co-occurrence multilayer approach, which links farm-level networks, to test scale signatures simultaneously at the farm and inter-farm levels. Consistent with the comparison between groups, the multilayer network was not partitioned into clusters. This result was consistent even when artificially disconnecting farm-level networks. Our results show a prominent signal of processes operating across farms to generate a non-random, similar (yet not identical) co-occurrence patterns. Comprehending the processes underlying rumen microbiome assembly can aid in developing strategies for its manipulation. More broadly, our results provide new evidence for the scale at which forces shape microbe co-occurrence. Finally, the hypotheses-based approach and methods we developed can be adopted in other systems to detect scale signatures in species interactions.

Unraveling the spatiotemporal dynamics of communities is critical to understand how biodiversity responds to global changes. However, this task is not trivial, as these dynamics are quite complex, and most studies are limited to few taxa at small local and temporal scales. Tropical mountains are ideal indicators of biodiversity response since these endangered and complex ecosystems include many distinct habitats within small geographical areas, harboring a megadiverse fauna, especially insects. Indeed, while insects are particularly sensitive to environmental and climatic changes, the extent of the impact of climate variability on mountain tropical insect diversity remains poorly understood. Here we present time-series data from a decade of studying the spatiotemporal dynamics of ants, butterflies and dung beetles. We assessed patterns of species richness change along the elevational gradient for each taxonomic group per sampling year and cumulatively over years. We then quantified community changes over time by measuring the variation in species richness across sampling years (temporal trends in α-diversity), and the temporal variation in species composition (temporal β-diversity) evaluating species gains and losses over time. We also evaluated the variation of air temperature and humidity through meteorological stations within the sampling years. We detected a classical pattern of species richness decline with elevation, albeit with a noticeable increase in species richness variation with increasing elevation. The temporal β-diversity exhibited considerable variability across elevations, taxa, and time. Only dung beetles presented a positive relationship with humidity variation over the years. Critically, both rare and common species drove extirpations and colonizations, and we found no trend of temporal decline of insect species at local and regional scales. Our study shows that insect metacommunity responses to elevation and global changes are rather complex, and stresses the importance of long-term studies that incorporate multiple sampling periods and different groups of organisms in tropical mountains.

Reptiles make up one-third of tetrapods, however they are often omitted from global conservation analyses. Understanding the determinants of reptile distribution is the foundation for reptile conservation research. We assembled a dataset on the distribution of 231 reptile species (nearly 50% of recorded species in China). We then investigated the association of species range filling (the proportion of observed ranges compared to species potential climate distributions) with climate, range size, topography and human activity, using three regression methods. At the species level, we found the most primary factors influencing the recent distribution pattern of reptiles across China were the mean annual precipitation (MAP) and the mean annual temperature (MAT). In contrast, human activity came in last. Similarly, at a spatial level, MAP and MAT were still the most important factors. Geographically, the south and east of China support the highest reptile diversity, partially due to high precipitation. Contrary to the prevailing notion that reptile distributions are primarily shaped by human activities, our study re-emphasizes the importance of climate in determining reptile distribution. It accentuates the necessity of integrating climate variables into future animal conservation strategies in China. Our findings also offer valuable insights for informing conservation practices, including the site planning of natural reserves and national parks, as well as monitoring of environmental factors in protected areas.

Georeferencing is a key process in the digitization of natural history collections as it assigns spatial coordinates to preserved specimen collecting locations, facilitating their use in ecological, evolutionary and conservation research. Georeference data in public repositories such as GBIF is often missing or incomplete, jeopardising their use in research and limiting the return on investment made by public institutions. Despite the existence of guidelines for best practices for georeferencing and widely accepted standards for biodiversity data, there is a lack of a simple yet effective software tool that offers the implementation of both concepts. We present GeoPick with the aim to offer the collections community a standards-compliant tool that eases the georeferencing process, making it more cost-effective, and which, by applying best practices, contributes to the betterment of the occurrence data in public repositories. GeoPick also offers the possibility of collaboration between users and institutions through the sharing of georeferences. The tool is hosted by GBIF at https://geopick.gbif.org, and is open source. Its code is available at a public GitHub repository (https://github.com/rtdeb/GeoPick).

Keywords: Darwin Core, georeferencing, natural history collections, point-radius method, web application, Well Known Text Format, WKT

Liverworts are an ancient plant lineage that occurs worldwide with the highest species richness in cool and humid habitats such as tropical montane and temperate rain forests. It has been proposed that liverworts originated under such temperate climatic conditions and have later expanded into more tropical conditions, but how this is reflected in their phylogenetic diversity along the strong climatic gradients associated with elevation remains unexplored. We studied the phylogenetic diversity of regional liverwort floras along the elevational gradient in the tropical Andes, comparing indices that emphasize deeper and shallower phylogenetic relationships, and relating these to temperature- and precipitation-related variables, as well as to climatic extremes and seasonality. We found that whereas liverwort species richness peaks at around 2000 m a.s.l., richness-corrected phylogenetic diversity increases with elevation, and the standardized effect of size of phylogenetic diversity is highest at 2500–4000 m a.s.l. This is in accordance with an origin of liverworts under cool conditions, followed by more recent diversification in warmer climates at lower elevations. We further found temperature-related climatic parameters to be stronger predictors of phylogenetic diversity of liverworts than precipitation-related variables, and climatic extremes to have a stronger influence than climatic seasonality. We interpret these patterns as reflecting the physiological challenges of adapting to low temperatures as well as rare occurrences of extreme climatic events. All this reveals a strong signal of the evolutionary dynamics of this ancient plant lineage linked with its physiological adaptations to climatic conditions. The age of this group and its poikilohydric nature, i.e. its inability to regulate water loss, lead to patterns that contrast with those of vascular plants, allowing for discerning evolutionary generalities that are independent of physiology and lineage age.

The impact of fragmentation on biodiversity is driven by more than the spatial configuration of suitable habitat patches. Habitat is embedded in the surrounding anthropogenic land cover, known as the matrix, which plays a key role in species movement and connects the fragmented habitat. Whether the matrix is a barrier or a conduit to movement depends on the mortality of the moving individuals. However, individuals differ in their behavioural response to the risk posed by the matrix, with the willingness to enter the matrix depending on an individual's risk-taking behaviour. This individual-level behavioural variability is rarely considered but represents an additional mechanism shaping inter- and intraspecific competition as well as evolutionary behavioural responses. We used an individual-based model to scale up from individual foraging movements to the resulting community structure of a competitive small mammal community in differently fragmented landscapes. The model interactively considers extrinsic matrix conditions, given as a certain mortality rate, and individual differences in intrinsic movement decisions when moving into the matrix. The model was used to investigate consequences of fragmentation and matrix mortality for species and behavioural diversity. Low matrix mortality resulted in a positive effect of fragmentation on species diversity. At the same time, it led to a high average risk-taking behaviour. While this was an important adaptive response to fragmentation, it also led to a loss of intraspecific diversity. High matrix mortality reversed the effect of fragmentation, leading to a drastic loss of species with increasing fragmentation. High mortality risk reduced average risk-taking, especially at high fragmentation. Study findings suggest that the feasibility of movement in the matrix can influence species diversity and evolutionary responses of movement-related behavioural traits in fragmented landscapes. The matrix may thus play a key role in reconciling contrasting empirical results and provides a promising tool for future biodiversity conservation.

Remote sensing is an invaluable tool for tracking decadal-scale changes in vegetation greenness in response to climate and land use changes. While the Landsat archive has been widely used to explore these trends and their spatial and temporal complexity, its inconsistent sampling frequency over time and space raises concerns about its ability to provide reliable estimates of annual vegetation indices such as the annual maximum normalised difference vegetation index (NDVI), commonly used as a proxy of plant productivity. Here we demonstrate for seasonally snow-covered ecosystems, that greening trends derived from annual maximum NDVI can be significantly overestimated because the number of available Landsat observations increases over time, and mostly that the magnitude of the overestimation varies along environmental gradients. Typically, areas with a short growing season and few available observations experience the largest bias in greening trend estimation. We show these conditions are met in late snowmelting habitats in the European Alps, which are known to be particularly sensitive to temperature increases and present conservation challenges. In this critical context, almost 50% of the magnitude of estimated greening can be explained by this bias. Our study calls for greater caution when comparing greening trends magnitudes between habitats with different snow conditions and observations. At a minimum we recommend reporting information on the temporal sampling of the observations, including the number of observations per year, when long-term studies with Landsat observations are undertaken.