Ecography最新文献

It has been hypothesized that the Araucaria Forest in southern Brazil underwent expansions in the past, driven either by human groups or by climate fluctuations of the Holocene and Pleistocene. Fossil pollen records of the Paraná pine Araucaria angustifolia, a dominant tree in that forest, provide some insights into when those may have occurred. Still, the timing of those expansions has never been estimated. To infer past range shifts and shed light on their main drivers, we employed next-generation DNA sequencing (ddRADseq), machine learning, and a comprehensive database of fossil pollen records into a study of historical demographic inference and paleo-distribution modeling of the Paraná pine. We found that A. angustifolia comprises two populations expanding at different times: one in the Mantiqueira mountain chain, the other in the southern Brazilian plateau. The southern population began to expand during the Last Glacial Period ~ 70 kya, long before human arrival in South America. Still, genetic analyses support that humans later impacted this population, resulting in lower genetic diversity, higher inbreeding, and high levels of gene flow over large distances with a weak pattern of isolation-by-distance. It is possible this resulted from human influence on seed dispersal and germination on the southern Brazilian plateau. The Mantiqueira population, in contrast, expanded only recently (~ 3 kya). This timing coincides with Holocene climatic changes and human settlements established further south, although, to date, there is little archeological evidence of human impact in the Mantiqueira. In addition, multitemporal species distribution models built from a combination of present-day and pollen records infer a range expansion of the Araucaria Forest during glacial times until the cold humid HS1 event (~ 16 kya), when the forest was most widespread, with no evidence of glacial refugia. The combination of genomic and spatial analyses suggests that both human and climatic controls played a role in the dynamics of the Araucaria Forest.

The study of functional diversity (FD) provides ways to understand phenomena as complex as community assembly or the dynamics of biodiversity change under multiple pressures. Different frameworks are used to quantify FD, either based on dissimilarity matrices (e.g. Rao entropy, functional dendrograms) or multidimensional spaces (e.g. convex hulls, kernel-density hypervolumes), each with their own strengths and limits. Frameworks based on dissimilarity matrices either do not enable the measurement of all components of FD (i.e. richness, divergence, and regularity), or result in the distortion of the functional space. Frameworks based on multidimensional spaces do not allow for comparisons with phylogenetic diversity (PD) measures and can be sensitive to outliers.

We propose the use of neighbor-joining trees (NJ) to represent and quantify FD in a way that combines the strengths of current frameworks without many of their weaknesses. Importantly, our approach is uniquely suited for studies that compare FD with PD, as both share the use of trees (NJ or others) and the same mathematical principles.

We test the ability of this novel framework to represent the initial functional distances between species with minimal functional space distortion and sensitivity to outliers. The results using NJ are compared with conventional functional dendrograms, convex hulls, and kernel-density hypervolumes using both simulated and empirical datasets.

Using NJ, we demonstrate that it is possible to combine much of the flexibility provided by multidimensional spaces with the simplicity of tree-based representations. Moreover, the method is directly comparable with taxonomic diversity (TD) and PD measures, and enables quantification of the richness, divergence and regularity of the functional space.

Ebolaviruses have the ability to infect a wide variety of species, with many African mammals potentially serving either as primary reservoirs or secondary amplifying hosts. Previous work has shown that frugivorous bats and primates are often associated with spillover and outbreaks. Yet the role that patterns of biodiversity, either of mammalian hosts or of common fruiting species such as Ficus (figs, fruit resources used by a wide variety of species), play in driving outbreak risk remains unclear. We investigated what factors most directly influence Ebolavirus outbreak risk in Sub-Saharan Africa by using a phylogenetically informed path analysis to compare a wide array of potential models (path diagrams) of spatial dynamics. We considered mammalian frugivore richness, cercopithecid and hominid primate richness, richness of pteropodid (fruit) bats, the spatial distribution of species that have tested positive for Ebolavirus antibodies in the wild, Ficus habitat suitability, and environmental conditions (mean annual and variability in temperature and rainfall). The proximate factors that most influenced whether a given host species range contained a site of a previous outbreak event were 1) habitat suitability for Ficus and 2) the diversity of cercopithecid primates. Frugivore richness overall (including bats, primates, and a few other mammals) and the richness of bats in the family Pteropodidae had a strong effect on which species tested positive for Ebolavirus antibodies, but did not influence outbreak risk directly in pathways explored. We interpret this as evidence that foraging around Ficus and frugivorous mammals (such as cercopithecid primates which are commonly hunted for food) play a prominent role in driving outbreaks into human communities, relative to other factors we considered which influence outbreak risk more indirectly.

Climate warming has triggered shifts in plant distributions, resulting in changes within communities, characterized by an increase in warm-demanding species and a decrease in cold-adapted species – referred to as thermophilization. Researchers conventionally rely on co-occurrence data from vegetation assemblages to examine these community dynamics. Despite the increasing availability of presence-only data in recent decades, their potential has largely remained unexplored due to concerns about their reliability. Our study aimed to determine whether climate-induced changes in community dynamics, as inferred from presence-only data from the Global Biodiversity Information Facility (GBIF), corresponded with those derived from co-occurrence plot data. To assess the differences between these datasets, we computed a community temperature index (CTI) using a transfer function, weighted-averaging partial least squares regression (WA-PLS). We calibrated the transfect function model based on the species–temperature relationship using data before recent climate warming. Then we assessed the differences in CTI and examined the temporal trend in thermophilization. In a preliminary analysis, we assessed the performance of this calibration using three datasets: 1) Norwegian co-occurrence data, 2) presence-only data from a broader European region organized into pseudo-plots (potentially capturing a larger part of the species niches), and 3) a combined dataset merging 1) and 2). The transfer function including the combined dataset performed best. Subsequently, we compared the CTI for the co-occurrence plots paired up spatially and temporally with presence-only pseudo-plots. The results demonstrated that presence-only data can effectively evaluate species assemblage responses to climate warming, with consistent CTI and thermophilization values to what was found for the co-occurrence data. Employing presence-only data for evaluating community responses opens up better spatial and temporal resolution and much more detailed analyses of such responses. Our results therefore outline how a large amount of presence-only data can be used to enhance our understanding of community dynamics in a warmer world.

Pollinator activity is affected by landscape-scale flower availability, and by pollinator interactions with co-occurring organisms. Of special interest are potentially detrimental effects of herbivores on the attractiveness of plants to pollinators. While insect herbivores are abundant in natural and agro-ecosystems, the combined effect of herbivory and landscape floral resources on pollinator activity and the delivery of pollination services is little studied and understood. Here we investigated the combined effects of surrounding flower cover and aphid herbivory on pollination services in agricultural landscapes. We apply a resource landscape approach for mapping the spatial distribution of floral resources across landscapes, using neighbourhood modelling and empirical data on flower availability in specific land-use types. In each of 25 Mediterranean landscapes spanning a gradient of land-use intensity ranging from natural to agricultural, we established paired patches of potted aphid-infested or aphid-free phytometer plants Diplotaxis erucoides. In each patch, we recorded the activity of insects visiting flowers and subsequent seed set. We also recorded the relative abundance of flowers in dominant land-use locales within a 1 km radius of each patch. Neighbourhood analyses revealed that plant–pollinator interactions in our study system are shaped by herbivory, distribution of floral resources across the landscape, and the interaction between these factors. We found a negative competitive effect of flower cover on pollinator activity and phytometer seed-set; this effect was stronger on aphid-infested than aphid-free plants. The main pollinator guilds in the study sites (wild bees, honeybees and non-bee pollinators) responded differently to these factors. Our results highlight the importance of combining a resource landscape approach with the exploration of interactions among different organisms, when mapping pollination services and identifying the scale at which pollinators respond to foraging resources.

West Nile virus (WNV) is a globally widespread arthropod-borne virus that poses a significant public health concern. Mosquitoes transmit the virus in an enzootic cycle among birds, which act as reservoirs. Climate plays a crucial role in these outbreaks as mosquitoes are highly influenced by climatic conditions, and bird migrations are also affected by weather patterns. Consequently, changes in climate can potentially impact the occurrence of WNV outbreaks. We used biogeographic modelling based on machine learning algorithms and fuzzy logic to analyse and evaluate separately the risk of WNV outbreaks in two different biogeographic regions, the Afrotropical and the Western Palaearctic region. By employing fuzzy logic tools, we constructed a comprehensive risk model that integrates the Afro-Palaearctic system as a unified operational unit for WNV spread. This innovative approach recognizes the Afro-Palaearctic region as a pathogeographic system, characterized by biannual connections facilitated by billions of migratory bird reservoirs carrying the disease. Subsequently, we forecasted the effects of different climate change scenarios on the spread of WNV in the Afro-Palaearctic system for the years 2040 and 2070. Our findings revealed an increasing epidemic and epizootic risk south of the Sahara. However, the area where an upsurge in risk was forecasted the most lies within Europe, with the anticipation of risk expansion into regions presently situated beyond the virus' distribution range, including central and northern Europe. Gaining insight into the risk within the Afro-Palaearctic system is crucial for establishing coordinated and international One Health surveillance efforts. This becomes particularly relevant in the face of ongoing climate change, which disrupts the ecological equilibrium among vectors, reservoirs, and human populations. We show that the application of biogeographical tools to assess risk of infectious disease, i.e. pathogeography, is a promising approach for understanding distribution patterns of zoonotic diseases and for anticipating their future spread.

We assessed the impact of road disturbances on the dominant mycorrhizal types in ecosystems at the global level and how this mechanism can potentially lead to lasting plant community changes. We used a database of coordinated plant community surveys following mountain roads from 894 plots in 11 mountain regions across the globe in combination with an existing database of mycorrhizal–plant associations in order to approximate the relative abundance of mycorrhizal types in natural and disturbed environments. Our findings show that roadside disturbance promotes the cover of plants associated with arbuscular mycorrhizal (AM) fungi. This effect is especially strong in colder mountain environments and in mountain regions where plant communities are dominated by ectomycorrhizal (EcM) or ericoid-mycorrhizal (ErM) associations. Furthermore, non-native plant species, which we confirmed to be mostly AM plants, are more successful in environments dominated by AM associations. These biogeographical patterns suggest that changes in mycorrhizal types could be a crucial factor in the worldwide impact of anthropogenic disturbances on mountain ecosystems. Indeed, roadsides foster AM-dominated systems, where AM-fungi might aid AM-associated plant species while potentially reducing the biotic resistance against invasive non-native species, often also associated with AM networks. Restoration efforts in mountain ecosystems will have to contend with changes in the fundamental make-up of EcM- and ErM plant communities induced by roadside disturbance.