Ecography最新文献

Glaciers are retreating worldwide at an ever-increasing rate, exposing new ice-free areas to ecological succession. This process leads to changes in biodiversity and potentially to novel species interactions. However, we still have a limited understanding of how glacier retreat influences species interaction networks, particularly the structure and robustness of mutualistic networks. After reconstructing plant–pollinator networks along a 140-years chronosequence on a glacier foreland, we address the effects of glacier retreat on network structure and robustness. Our results show that the prevalence of different network motifs changes over spacetime, leading to a decrease of network robustness. With glacier retreat, mutualistic networks shift from highly connected with diverse specialist interactions to loosely connected with few generalist interactions. Furthermore, despite the turnover of plant species, we find that species structural roles remain constant over spacetime while depending on species identity. Our findings suggest that glacier retreat reshuffles mutualistic networks with motifs posing low robustness, leading to increased fragility. Understanding the assembly and breaking down of species interaction networks provides novel insights into the development and stability of novel, post-glacial ecological systems facing glacier extinction.

Numerous studies have reported that observed species shifts in mountain areas lag behind expectations under current warming trends, however, the mechanisms remain poorly understood. One important mechanism might be microclimatic heterogeneity causing migration of species to cooler conditions under closed forest canopies, but evidence is scarce. We here compared the distributions of 710 species (11 taxonomic groups including fungi, plants, and animals) along an elevation gradient (287–1419 m a.s.l.) in a temperate low mountain range between 2006–2008 and 2016–2017 to address this open question. We characterized each species' distribution (peak and breadth) based on their abundance along two environmental gradients: elevation and canopy cover. We then analysed changes in species' distribution peaks, asking whether shifts in canopy distribution and initial distribution characteristics explain variation in elevational distribution shifts. Across all taxa, the mean shift in elevational distribution peak was + 35.3 m (i.e. upslope). Species' baseline distribution peaks were strong predictors of elevational distribution shifts with stronger upslope shifts in low-elevation and open-forest species. Even though we observed considerable variation in the responses among species, canopy distribution shifts had a significant negative effect on elevational distribution shifts overall and in six taxonomic groups. We suggest that this is related to cooler microclimatic conditions under closed compared to open forest canopies. Shifts to closed-canopy forests may thus partly compensate for elevational distribution shifts, highlighting the conservation value of heterogeneous landscapes featuring microclimatic refugia. Yet, it is likely that other mechanisms, such as habitat limitation, are also at play. Future studies need to quantify the potential of microclimatic refugia under accelerating forest dynamics, considering the interplay of canopy cover and other factors driving microclimate, and to illuminate the complex climate change response mechanisms among species and taxonomic groups.

Life is not a beach for those animals that survive in the rough ecological conditions found in marine sandy beaches – and yet, microscopic animals thrive on them. We explore the drivers for meiofaunal diversity in beaches by analysing taxonomic and functional patterns of 348 flatworm communities across 116 reflective beaches in the western Mediterranean, totalling 152 species (61.2% new to science). First, we confirm that species richness does not differ between beach hydrodynamic levels (swash, shoaling and surf) but rather depends on the characteristics of each beach. Second, we demonstrate that species composition across those levels depends on the species traits, in addition to geographical and abiotic factors. Third, we highlight that the species functional space has a lower richness than expected and a lower redundancy in the wave-exposed swash level compared to the shoaling and subtidal levels, suggesting a trait-based ecological filtering. Finally, we show that those differences depend on the higher frequency of hydrodynamics-related traits in the species of the swash level. Our results suggest that the rough hydrodynamic conditions in the swash level favour a unique combination of species traits, which might be linked to ecological speciation in flatworms but also in other interstitial animals.

Phylogenetic indexes summarize the evolutionary information within a given assemblage pool based on the topology and branch lengths of a hypothesized phylogenetic tree. However, different historical contingencies experienced by these assemblages can unevenly distribute evolutionary information through time and over the phylogeny. ‘treesliceR' is an R package containing tools to flexibly cut phylogenies at different depths, and also has built-in functions to assess spatially explicit phylogenetic patterns over time. ‘treesliceR' can slice phylogenies in any temporal orientation (‘rootwardly' or ‘tipwardly'), using different criteria (million years or phylogenetic diversity). Moreover, ‘treesliceR' contains functions to assess the rates of accumulation of any phylogenetic information (e.g. α and β diversities) through time. These functions are unique to the package and provide outputs that are ready-to-use in graphing functions. We demonstrated the main uses of ‘treesliceR' by investigating areas of paleo-endemism and neo-endemism of Passeriformes in Australia. Finally, we mapped rates of accumulation of phylogenetic β-diversity (Cpβ_rate) across Australia. ‘treesliceR' is an open-source R package under continuous progress, designed to decompose temporally any phylogenetic information.

Liverworts are one of the oldest lineages of the extant land plants but the geographic patterns and ecological determinants of their species richness have not yet been studied at a global scale until now. Here, using a comprehensive global database, we find that regional species richness of liverworts in general 1) shows a clear latitudinal diversity pattern, 2) is highest in mountains, presumably reflecting the effects of habitat heterogeneity and the occurrence of cloud forest, 3) is more strongly influenced by contemporary climate than by climate change during the Quaternary, 4) is more strongly affected by precipitation-related than by temperature-related variables, reflecting the poikilohydric nature of liverworts and hence their water-dependence, and 5) is more strongly affected by climate extremes than by climate seasonality. However, we find regional deviations from these general patterns, especially in the Southern Hemisphere where the distinct arrangement of land masses leads to different climatic patterns and thus climate–species richness relationships. Compared with other major land plant lineages, liverworts show the same importance of precipitation-related factors as ferns, whereas in angiosperms temperature also plays an important role, reflecting the different physiological adaptations of these groups to drought and cold stress, and providing insights into the different evolutionary pathways taken by these lineages.

Habitat fragmentation per se – independent of habitat amount – often increases patch occupancy, possibly because patches are closer together in landscapes with higher fragmentation per se, which should increase dispersal success. Here, we ask whether this effect is influenced by the quality and/or heterogeneity of the landscape matrix, i.e. the non-habitat portion of the landscape. Specifically, we expect the positive effect of fragmentation per seshould be accentuated when matrix quality is high, reducing dispersal mortality. In contrast, when matrix quality is low, high dispersal mortality should lead to fewer colonisations, and accumulation of extinctions across the smaller patches in a more-fragmented landscape could lead to negative effects of fragmentation per se. Additionally, matrix heterogeneity could obscure fragmentation effects, as the link between habitat spatial distribution and between-patch dispersal becomes less predictable. We test these ideas using Glanville fritillary butterfly Melitaea cinxia occupancy data for 4291 habitat patches in the Åland Islands, Finland. Habitat patches for the study species are discrete and well-defined areas where at least one of the two host species occurs. Adult individuals disperse from habitat patches, spending time in the landscape matrix while searching for new habitat patches. Our predictions were mostly supported. Fragmentation effects were more strongly positive when matrix quality was high; however, we did not see the predicted negative effect of fragmentation per se in landscapes with low matrix quality. As predicted, fragmentation effects on patch occupancy were weaker in landscapes with a more heterogeneous matrix. Our findings may explain why fragmentation effects are often weak. They also suggest that the moderating effects of matrix quality and heterogeneity should be explicitly considered when interpreting effects of habitat fragmentation per se on species distributions.

Species distribution models (SDMs) underpin a wide range of decisions concerning biodiversity. Although SDMs can be built using presence-only data, rigorous evaluation of these models remains challenging. One evaluation method is the Boyce index (BI), which uses the relative frequencies between presence sites and background sites within a series of bins or moving windows spanning the entire range of predicted values from the SDM. Obtaining accurate estimates of the BI using these methods relies upon having a large number of presences, which is often not feasible, particularly for rare or restricted species that are often the focus of modelling. Wider application of the BI requires a method that can accurately and reliably estimate the BI using small numbers of presence records. In this study, we investigated the effectiveness of five statistical smoothing methods (i.e. thin plate regression splines, cubic regression splines, B-splines, P-splines and adaptive smoothers) and the mean of these five methods (denoted as ‘mean') to estimate the BI. We simulated 600 species with varying prevalence and built distribution models using random forest and Maxent methods. For training data, we used two levels for the number of presences (NP_train: 20 and 500), along with 2 × NP_train and 10000 random points (i.e. random background sites) for each modelling method. We used the number of presences at four levels (NP_bi: 1000, 200, 50 and 10) to investigate its effect, together with 5000 random points to calculate the BI. Our results indicate that the BI estimates from the binning and moving window methods are severely affected by the decrease of NP_bi, but all the estimates of the BI from smoothing-based methods were almost always unbiased for realistic situations. Hence, we recommend these methods for estimating the BI for evaluating SDMs when verified absence data are unavailable.

Anticipating the effects of global change on biodiversity has become a global challenge requiring new methods. Approaches like species distribution models have limitations which have fueled the development of joint species distribution models (JSDMs). However, JSDMs rely on systematic surveys community data, and no assessment has been made of their suitability with unstructured opportunistic databases data. We used hierarchical modeling of species communities (HMSC) to test JSDMs performance when using opportunistic databases. Using artificial data that mimic the limitations of such databases by subsampling complete co-occurrence matrices (i.e. original data), we analysed how the completeness of opportunistic databases affects JSDMs regarding 1) the role of independent variables on species occurrence, 2) residual species co-occurrence (as a proxy of biotic interactions) and 3) species distributions. Moreover, we illustrate how to evaluate completeness at the pixel level of real data with a study case of forest tree species in Europe, and evaluate the role of data completeness in model estimation. Our results with artificial data demonstrate that decreasing the completion percentage (the rate of original data presences represented in the subsampled matrices) increases false negatives and negative co-occurrence probabilities, resulting in a loss of ecological information. However, HMSC tolerates different levels of degradation depending on the model aspect being considered. Models with 50% of missing data are valid for estimating species niches and distribution, but interaction matrices require databases with at least 75% of completion data. Furthermore, HMSC's predictions often resemble the original community data (without false negatives) even more than the subsampled data (with false negatives) in the training dataset. These findings were confirmed with the real study case. We conclude that opportunistic databases are a valuable resource for JSDMs, but require an analysis of data completeness for the target taxa in the study area at the spatial resolution of interest.

Climate change-induced extreme weather and related drought and flood conditions are heterogeneous across space and time. The variability in location, timing, and magnitude of rainfall can alter how species respond to the drought and flood disturbances. To further complicate this matter, when droughts end they are often followed by extreme flooding, which are rarely considered as a disturbance (Humphries et al. 2024), let alone assessed with its own heterogeneity. Consequently, it is difficult to quantify impacts on ecological communities across large spatiotemporal scales without considering flood-drought disturbance characteristics in sequence (Burton et al. 2020). We hypothesized that native organisms have evolved resistance to withstand repeated cycles of drought-flood disturbances, and that established non-native species have adapted to persist in novel conditions. To test this, we fit spatiotemporal models of species occurrence with local rainfall patterns as covariates in the drought and flood impacted Murray-Darling basin in Australia during the decade long Millenium Drought, and its recovery period. During these drought conditions, river-floodplain organisms in the Murray-Darling became localized in refugia that limited longitudinal and lateral connectivity (Bond et al. 2008), and following flooding the same organisms were exposed to dispersal and recruitment opportunities (Humphries et al. 2020), as well as to hypoxic blackwater events that lead to the mortality of aquatic organisms (Small et al. 2014). At the basin-scale we found that the range size of most native and non-native fishes were highly resistant to the extreme drought and post-flood conditions. At local scales, species richness, or detection, actually increased under drought conditions. Both findings highlight the resistance of species to climate change driven extreme weather, which opens new questions on community adaptations.