Complex Environmental Gradients Research Articles

Biogeographic shifts in the microbial co-occurrence network features of three domains across complex environmental gradients in subtropical coastal waters

BackgroundBacteria, Archaea, and Microeukaryotes comprise taxonomic domains that interact in mediating biogeochemical cycles in coastal waters. Many studies have revealed contrasting biogeographic patterns of community structure and assembly mechanisms in microbial communities from different domains in coastal ecosystems; however, knowledge of specific biogeographic patterns on microbial co-occurrence relationships across complex coastal environmental gradients remains limited. Using a dense sampling scheme at the regional scale, SSU rRNA gene amplicon sequencing, and network analysis, we investigated intra- and inter-domain co-occurrence relationships and network topology-based biogeographic patterns from three microbial domains in coastal waters that show environmental gradients across the inshore-nearshore-offshore continuum in the East China Sea.ResultsOverall, we found the highest complexity and connectivity in the bacterial network, the highest modularity in the archaeal network, and the lowest complexity, connectivity, and modularity in the microeukaryotic network. Although microbial co-occurrence networks from the three domains showed distinct topological features, they exhibited a consistent biogeographic pattern across the inshore-nearshore-offshore continuum. Specifically, the nearshore zones with intermediate levels of terrestrial impacts reflected by multiple environmental factors (including water temperature, salinity, pH, dissolved oxygen, and nutrient-related parameters) had a higher intensity of microbial co-occurrence for all three domains. In contrast, the intensity of microbial co-occurrence was weaker in both the inshore and the offshore zones at the two ends of the environmental gradients. Archaea occupied a central position in the microbial inter-domain co-occurrence network. In particular, members of the Thaumarchaeota Marine Group I (MGI, now placed within the Family Nitrosopumilaceae of the Phylum Thermoproteota) appeared to be the hubs in the biogeographic shift between inter-domain network modules across environmental gradients.ConclusionsOur work offers new insights into microbial biogeography by integrating network features into biogeographic patterns, towards a better understanding of the potential of microbial interactions in shaping biogeographic patterns of coastal marine microbiota.

Evaluating the feasibility of using plant‐specific metabarcoding to assess forest types from soil eDNA

AbstractQuestionsAn essential aspect of variation in natural systems is that species respond to complex environmental gradients. Recognizing plant composition gradients associated with abiotic factors (ecoclines) can be foundational for defining habitat types, which, in turn, helps map natural variation. Typically, ecoclinal structures are assessed through visual evaluation of above‐ground vegetation and analysis of covarying abiotic factors. However, the correlation between ecological structures detected by soil eDNA plant assessments and those identified by visual assessment remains largely unexplored.LocationHvaler archipelago, southern Norway.MethodsPlant diversity assessments were conducted using metabarcoding of the trnL (UUA) intron p6 loop and ITS2 from 31 soil samples collected across six forest types. These forest types span gradients related to drought risk and calcium richness.ResultsThe barcode amplicons identified 70 plant taxa, primarily vascular plants (67), with most assigned to the species level (59), representing common forest taxa across the sites. Comparisons between soil eDNA compositions and theoretical forest‐type compositions showed a low to medium correspondence (26% to 76%) between the two. Ordinations of soil eDNA compositions revealed two axes without clear ecological interpretation and correlated poorly with the calcium–richness gradient previously identified by visual assessments.ConclusionsOverall, our results emphasize the necessity for comprehensive sequence reference libraries to conduct thorough plant biodiversity assessments. They also highlight the potential of soil eDNA to assess plant composition, which can aid in ecosystem mapping.

A new method for bioassessment of ecosystems with complex communities and environmental gradients

Bioassessment of complex and heterogeneous ecosystems is a challenge when there are multiple, strong, natural environmental gradients; unknown, or spatially varying, mixtures of stressors; and large numbers of taxa with unknown responses to both the environmental gradients and the stressors. Current methods of bioassessment are not designed for use under this set of constraints. To address this gap, we have developed an assessment method appropriate for well-sampled, heterogeneous systems with many taxa. In the bioassessment described below, we model taxa occurrence as a function of natural environmental gradients, then use residual covariance patterns between all pairs of taxa to estimate the impact of human disturbance across sites as a latent construct. The derivation of the method from an underlying causal model allows the metric value at each site and the associated taxa responses to be partitioned into contributions from a set of putative stressors. We apply this method as a case study to the subtidal benthic invertebrate community of Puget Sound, WA (USA) and demonstrate a partial decomposition of the metric values to a set of stressors including sediment organic carbon, nitrogen, metals, and organic pollutants. While this method provides new opportunities to estimate, communicate, and understand the ecological condition of complex, heterogeneous ecosystems, due to the requirement for broad, detailed data to inform its estimates, it will likely be most appropriate for monitoring programs.

Rare methanotrophs adapt to broader environmental gradients than abundant methanotrophs in the riparian zone of the Three Gorges Reservoir

AbstractSoil communities are intricately linked to ecosystem functioning. Uncovering the responses of rare and abundant taxa to environmental change is vital for understanding methanotrophic community assembly and ecosystem function. It is unclear what the proportions of the different taxa are in riparian soil and how environmental change may impact these, and thereby affect the structure and assembly of different communities. Considering both abundant and rare taxa, we investigated environmental thresholds and phylogenetic signals related to the ecological preferences of methanotrophic communities under complex environmental gradients, and explore the factors that influence their assembly. It has ecological significance for predicting how communities will gather in response to changing environmental conditions. It was found that methanotrophs had different ecological network patterns across land‐use types, with the network complexity of abundant taxa being higher in grasslands and woodlands than that of rare taxa. Different ecological preference thresholds and phylogenetic signals were observed between abundant and rare subcommunities in the riparian zone, with rare taxa possessing potentially broader environmental adaptation capabilities. Rare taxa were phylogenetically clustered closer together than abundant taxa. The assembly of abundant taxa was dominated by stochastic processes, whereas the assembly of rare taxa was dominated by deterministic processes. Soil pH played an important role in regulating the balance between the assembly processes of abundant and rare subcommunities. The deterministic assembly of rare taxa and the stochastic assembly of abundant taxa increased with pH values. We revealed the complexity of a co‐occurring ecological network, identified the mediators of methanotrophic community assembly, and examined the adaptability of rare and abundant methanotrophic species to different environmental gradients. These findings indicate that it is possible to predict the generation and maintenance of methanotrophic community diversity by studying how methanotrophs will respond to environmental changes in the riparian zone during vegetation restoration projects.

Abundant and rare fungal taxa exhibit different patterns of phylogenetic niche conservatism and community assembly across a geographical and environmental gradient

Fungi play critical roles in the regulation of terrestrial ecosystem processes and functions. However, the biogeographic patterns, assembly mechanism and phylogenetic information of fungi across complex environmental gradients remains unexplored, especially the differences between abundant and rare fungi. Here, based on an extensive soil sampling (117 samples) covering almost all vegetation types in the Loess Plateau, we explored biogeography, community assembly, and phylogenetic niche conservatism of abundant and rare fungi. The results showed that the abundant fungal taxa exhibited less phylogenetic clustering than the rare fungi, but their environmental associations and phylogenetic signals were stronger. Stochastic processes dominated the assembly of abundant fungi. In contrast, the homogeneous selection of deterministic processes was the major assembly process of rare taxa. Soil organic carbon and nitrate nitrogen were the key factors driving the community assembly of abundant and rare fungi, respectively. Microbial network and niche analyses further indicated abundant fungi were more advantageous for maintaining microbial co-occurrence patterns and metabolic flexibility. We concluded that abundant fungi have broader environmental adaptation potential at spatially complex environmental scales and are less dispersed by environmental changes. These results provide insights for understanding the phylogenetic and community assembly mechanisms by which fungi adapt to large-scale environmental changes.

Summer snowline altitude gradients in Western Norway are influenced by maritime climate

ABSTRACT Mountain snowline dynamics are relatively underreported with few studies exploring spatial snowline dynamics. Whilst clear regional-scale relationships between snowline location and temperature exist in European mountains, recent research at higher latitudes reports no response to climate change. In maritime mountains, snowlines occupy complex environmental gradients. Using timeseries of satellite data from Landsat missions 5–8 (151 images between 1984 and 2021), we explored sub-regional summer snowline dynamics across the maritime-continental climate gradient in the Western Norwegian mountains. We characterize spatio-temporal snowline altitude dynamics and investigate the climate factors altering snowline patterns. Summer snowline altitudes were found to increase inland at around double the rate of the 0°C summer isotherm. Data from the European Centre for Medium-Range Weather Forecasts (ECMWF) land component of the fifth generation of European Reanalysis (ERA5-Land), showed a potential ‘maritime-mountain’ effect with coastal orographic snowfall and cloud cover-induced surface solar downwelling radiation amplifying maritime-continental snowline altitude gradients alongside surface atmospheric temperature. This was replicated in the Canadian Rocky Mountains. Between 1984 and 2021, we found spatial summer snowline gradients in Norway decreased and propose multiple climate forcings are responsible, potentially masking links between snowlines and climate change. Although non-significant, the data also suggest regional summer snowline altitudes increased. This study demonstrates the complex spatial heterogeneity in snow-climate relationships and highlights how long-term snow dynamics can be queried using fine-grain (Landsat) resolution satellite data. We share our approach through a Google Earth Engine web-app that rapidly executes spatial snowline analyses for global mountain regions via a graphical user interface.

Fungal diversities and community assembly processes show different biogeographical patterns in forest and grassland soil ecosystems.

Soil fungal community has been largely explored by comparing their natural diversity. However, there is a relatively small body of literature concerned with fungal community assembly processes and their co-occurrence network correlations carried out across large spatial-temporal scales with complex environmental gradients in natural ecosystems and different habitats in China. Thus, soil fungal community assembly processes were assessed to predict changes in soil function in 98 different forest and grassland sites from the Sichuan, Hubei, and Hebei Provinces of China using high-throughput sequencing of nuclear ribosomal internal transcribed spacer 2 (ITS-2). The 10 most abundant fungal phyla results showed that Ascomycota was the most abundant phylum in forests from Sichuan province (64.42%) and grassland habitats from Hebei province (53.46%). Moreover, core fungal taxa (487 OTUs) represented 0.35% of total fungal OTUs. We observed higher fungal Shannon diversity and richness (the Chao1 index) from diverse mixed forests of the Sichuan and Hubei Provinces than the mono-cultured forest and grassland habitats in Hebei Province. Although fungal alpha and beta diversities exhibited different biogeographical patterns, the fungal assembly pattern was mostly driven by dispersal limitation than selection in different habitats. Fungal co-occurrence analyses showed that the network was more intense at Saihanba National Forest Park (SNFP, Hebei). In contrast, the co-occurrence network was more complex at boundaries between forests and grasslands at SNFP. Additionally, the highest number of positive (co-presence or co-operative) correlations of fungal genera were inferred from grassland habitat, which led fungal communities to form commensalism relationships compared to forest areas with having higher negative correlations (mutual exclusion or competitive). The generalized additive model (GAM) analysis showed that the association of fungal Shannon diversity and richness indices with geographical coordinates did not follow a general pattern; instead, the fluctuation of these indices was restricted to local geographical coordinates at each sampling location. These results indicated the existence of a site effect on the diversity of fungal communities across our sampling sites. Our observation suggested that higher fungal diversity and richness of fungal taxa in a particular habitat are not necessarily associated with more complex networks.

Protecting biodiversity via conservation networks: Taxonomic, functional, and phylogenetic considerations

A key element of conservation action involves the incorporation of sites into networks of protected areas. Historically, most network-creation strategies have been based on considerations of species richness and site complementarity. Nonetheless, phylogenetic or functional biodiversity may be more critical to the maintenance of ecosystem resilience or functioning than is the number of species. Therefore, we explore the efficacy of three strategies (i.e., random, sequential, and simultaneous inclusion of sites into conservation networks of particular sizes) to maximize species richness in a network, and explore associated consequences to aspects of functional and phylogenetic biodiversity. We do so for passerines in Connecticut, bats in Paraguay, and trees in North Carolina, which differ in β, functional, and phylogenetic biodiversity. The efficacy of sequential and simultaneous strategies for conserving species richness are similar at all network sizes and represent improvements over random strategies for each of the three taxa, conserving all species in as few as 35 % of the sites required based on a random strategy. For aspects of functional and phylogenetic biodiversity, metrics converged on the value of the entire biota, even when networks contained as few as five sites, suggesting that richness-based approaches can be effective in guiding conservation action from multiple perspectives. Evaluation of networks intended to conserve biodiversity at spatial extents that include more complex environmental gradients than the examples presented here, or that comprise more heterogenous environments than those represented in our analyses, are needed to more fully explore the generality of our conclusions.

Rhizosphere bacterial communities of three minor grain crops exhibit distinct environmental adaptations and assembly processes

AbstractDeciphering responses of bacterial communities to environmental change, and understanding how communities assemble in response to environmental change, are important subjects. The assembly processes governing the rhizosphere bacterial communities of minor grain crops are rarely explored based on regional scales, especially in terms of the environmental adaptation. Here, we investigated the environmental thresholds and phylogenetic signals for ecological preferences of rhizosphere bacterial communities of three minor grain crop taxa across complex environmental gradients to reflect their environmental adaptation. Additionally, we reported environmental factors affecting their community assembly processes based on a large‐scale soil survey in agricultural fields across northern China using high‐throughput sequencing. The results demonstrated a narrower range of environmental thresholds and weaker phylogenetic signals for the ecological traits of rhizosphere bacteria in proso millet than in foxtail millet and sorghum fields. The proso millet rhizosphere community was the most phylogenetically clustered. Null model analysis indicated that homogeneous selection belonging to deterministic processes governed the sorghum rhizosphere community, whereas dispersal limitation belonging to stochastic processes was the critical assembly process in the foxtail millet and proso millet. Mean annual temperature was the decisive factor for adjusting the balance between stochasticity and determinism of the foxtail millet, proso millet and sorghum rhizosphere communities. A higher temperature resulted in stochasticity in the proso millet and sorghum communities. For the foxtail millet community, the deterministic assembly increased with an increase in temperature. These results contribute to the understanding of rhizosphere‐associated bacterial community assembly processes in agro‐ecosystems on a large scale.Highlights Proso millet rhizosphere bacterial taxa exhibited weaker environmental adaptation than foxtail millet and sorghum taxa. Determinism governed the sorghum rhizosphere community, whereas stochasticity was the critical assembly process in the foxtail and proso millet. Mean annual temperature mediated balance between stochastic and deterministic processes.

Crown closure affects endophytic leaf mycobiome compositional dynamics over time in Pseudotsuga menziesii var. menziesii

Old-growth Pseudotsuga menziesii var. menziesii forests produce complex environmental and spatial gradients along which biota assemble. Given this, it has been proposed that changes in the crown microenvironment are associated with different community assembly outcomes for needle fungi. Using high-throughput sequencing, the endophytic mycobiomes of needles were characterized for increasing ages of needles sampled along the boles of eight coastal Douglas-fir trees. Leveraging airborne light detection and ranging (LiDAR) data to create three-dimensional “point cloud” representations of tree crowns revealed that crown closure accounted for more fungal compositional variation than height in crown, and fungal richness and diversity were positively correlated with increasing crown closure. Supplementing the point clouds of each climbed tree with clouds from >5,000 randomly selected trees in the study area showed that fungal communities from closed portions of the crown were increasingly structured with needle age. These findings highlight the importance of the crown microenvironment in the development of foliar fungal communities for a foundation tree species.

Precipitation balances deterministic and stochastic processes of bacterial community assembly in grassland soils

Microbial biodiversity is crucial for maintaining ecosystem functions. As climate change progresses at both global and regional scales, there is a need to understand microbial community assembly processes and diversity to predict changes in soil function in different regions. However, our knowledge of the mechanisms that shape bacterial β diversity at multiple spatial scales with complex environmental gradients is very limited. To investigate the mechanisms driving bacterial β diversity at regional (across transects) and local (within transect) scales, soil samples were collected from 30 grassland ecosystems in three east-west transects in northern China. The regional species pools influenced β diversity by mediating rare taxa migration across the three transects. After correcting for regional differences in species, the importance of local community assembly processes in controlling bacterial diversity was independent of spatial scales. Homogeneous selection (HoS, 39%–60%) and dispersal limitation (DL, 31%–54%) proved to be the most important community assembly processes for soil bacteria. Two dominant bacterial taxa accounting for 65% of the total abundance were identified, mainly including Acidobacteria, Actinobacteria, and Proteobacteria, with 63% and 64% contributions for the HoS and DL, respectively. Mean annual precipitation (MAP) mediated the relative importance of deterministic and stochastic assembly in bacterial communities. Consistently across all spatial scales, the relative importance of DL increased with aridity, and the contribution of HoS decreased. Importantly, the relative abundance of the two dominant bacterial taxa controlled by the HoS and DL varied with MAP. Collectively, our results provide clear evidence that water availability mediates the community assembly process of soil bacteria. This conclusion is of utmost importance for predicting the dynamics of soil microbial diversity and nutrient cycling in natural ecosystems in drylands.

Optimizing stable isotope sampling design in terrestrial movement ecology research

AbstractThe recognition of adequate sampling designs is an interdisciplinary topic that has gained popularity over the last decades. In ecology, many research questions involve sampling across extensive and complex environmental gradients. This is the case for stable isotope analyses, which are widely used to characterize large‐scale movement patterns and dietary preferences of organisms across taxa. Because natural‐abundance stable isotope variation in the environment is incorporated into inert animal tissues, such as feathers or hair, it is possible to draw inferences about the type of food and water resources that individuals consumed and the locations where tissues were synthesized. However, modern stable isotope research can benefit from the implementation of robust statistical analyses and well‐designed sampling approaches to improve geographic assignment interpretation.We employed hydrogen stable isotope simulations to study inferences regarding the probability of origin of migratory individuals and reveal gaps in sampling efforts while highlighting uncertainties of assignment model extrapolations. We present an integrative approach that explores multiple sampling strategies across species with different geographic ranges to understand advantages and limitations of animal movement inferences based on stable isotope data.We show the characteristics of different sampling strategies through geographic and isotopic gradients and establish a set of diagnostic tools that uncover the attributes of these gradients and evaluate uncertainties of model results.Our analysis demonstrates that sampling regimes should be evaluated in relation to specific research questions and study constraints, and that adopting a single method across species ranges can lead to a costly but less effective sampling strategy.

Temperature and soils predict the distribution of plant species along the Himalayan elevational gradient

AbstractTropical montane systems are characterized by a high plant species diversity and complex environmental gradients. Climate warming may force species to track suitable climatic conditions and shift their distribution upward, which may be particularly problematic for species with narrow elevational ranges. To better understand the fate of montane plant species in the face of climate change, we evaluated a) which environmental factors best predict the distribution of 277 plant species along the Himalayan elevational gradient in Nepal, and b) whether species elevational ranges increase with increasing elevation. To this end, we developed ecological niche models using MaxEnt by combining species survey and presence data with 19 environmental predictors. Key environmental factors that best predicted the distribution of Himalayan plant species were mean annual temperature (for 54.5% of the species) followed by soil clay content (10.2%) and slope (9.4%). Although temperature is the best predictor, it is associated with many other covariates that may explain species distribution, such as irradiance and potential evapotranspiration. Species at both ends of the Himalayan elevational gradient had narrower elevational ranges than species in the middle. Our results suggest that with further global warming, most Himalayan plant species have to migrate upward, which is especially critical for upland species with narrow distribution ranges.

Niche Characterization of Shrub Functional Groups along an Atlantic-Mediterranean Gradient

The identification of the factors controlling the understory species distribution and abundance is essential to understand the ecology and dynamics of natural forests and their management response. We assess the relationships between environmental gradients and shrub functional groups distribution patterns and niche characteristics in a transitional area between the Eurosiberian and Mediterranean biogeographic regions in Northern Spain. Here, 772 plots from the 3rd Spanish National Forest Inventory were used. Shrub functional groups respond to the same complex environmental gradients as trees, i.e., the north-south climatic gradient and a slope gradient. Unimodal response curves of shrub functional groups and families dominate along both gradients, providing evidence of successful functional turnover. Similar to tree species, the niche location of functionally related shrubs is close. Functional groups occupying environments with sharp contrast or transitional environments have the broadest niches, whereas those specialized functional groups occupying localized habitats showed the narrowest niches. The knowledge of shrub species distributions and niche characteristics along complex environmental gradients will improve our ability to discuss potential conservation management goals or threats due to land-use changes and future climate change.

Linking phylogenetic niche conservatism to soil archaeal biogeography, community assembly and species coexistence

AbstractAimA predictive understanding of the mechanisms underlying microbial biogeographical patterns is of great interest, particularly with respect to phylogenetic distributions of their ecological adaptations. Here, we test whether phylogenetic information can predict the biogeographical distributions, community assembly and species co‐occurrence of soil archaea.LocationNorthern China.Time periodJuly and August 2017.Major taxa studiedArchaeal communities.MethodsBy conducting a large‐scale (transect intervals of 1,257.6 km) study across agricultural field, forest, wetland, grassland and desert biomes, we applied the phylogenetic framework of niche conservatism to investigate archaeal biogeography, community assembly and network topology. We examined the phylogenetic signal based on Blomberg's K to test whether the environmental preference of a given archaeal taxon was related to the phylogeny, corresponding to the degree of phylogenetic conservatism for environmental niches across complex environmental gradients. We evaluated the assembly processes of archaeal communities based on null model and Sloan neutral model analyses. We then explored the major factors that influenced the species coexistence and assembly processes of soil archaeal communities.ResultsSoil archaeal taxa exhibited strong climate‐related niche conservatism of ecological preferences. Mean annual precipitation (MAP) had the strongest phylogenetic signal, and this mediated both community assembly processes and species coexistence, with stronger deterministic assembly and less species coexistence in environments with lower precipitation. Phylogenetic diversity was closely linked to the balance of community assembly processes; that is, stochastic assembly processes were dominant in low‐diversity communities, whereas variable selection of deterministic processes promoted high phylogenetic diversity.Main conclusionsWe conclude that strong phylogenetic niche conservatism of soil archaea drives their biogeographical distributions. Our findings represent a considerable advance in linking phylogenetic niche conservatism to soil archaeal biogeography, community assembly and species coexistence, and therefore forecasting soil archaeal evolutionary adaptations in response to ongoing environmental changes.

Seasonal Relationships Between Diatom Assemblages and Environmental Conditions Vary Between Epipelic- and Epipsammic-dominated Tidal Flat Diatom Communities in the Yaquina Estuary, Oregon, USA

This research examined temporal and spatial patterns of microphytobenthos (MPB) and relationships with environmental variables in a Pacific Northwest, USA estuary with complex environmental gradients. Sediment composition, salinity, and nutrients varied between sites closer to the estuary mouth (MAR), and those further upstream (RIV) and seasonal patterns in these variables also differed between MAR and RIV sites. Average MPB biomass was 57.8 ± 22.9 μg chlorophyll cm−3 at MAR sites and 29.9 ± 13.3 μg chlorophyll cm−3 at RIV sites. Relationships between MPB biomass and environmental conditions depended on season. The MPB diatom assemblage was influenced primarily by location within the estuary and secondarily by season. Epipsammic taxa, including Catenula adhaerens, Planothidium delicatulum, and Opephora spp. 1, were most abundant at MAR sites, while highly motile taxa in the genera Navicula senso lato and Nitzschia were abundant at RIV sites. Seasonal shifts in diatom community structure were evident at RIV sites and were driven primarily by changes in dominant epipelic taxa. Relationships between the MPB diatom assemblage and environmental conditions varied between MAR and RIV sites. Physical variables, including distance from the estuary mouth, sediment composition, land use in the 100 m buffer, and to a lesser extent, salinity, were correlated to the MAR assemblage. In contrast for RIV sites, salinity and nutrients were correlated to the diatom assemblage. Despite the complexity inherent in elucidating diatom–environmental relationships, our results suggest that tidal flat diatoms can be used to assess the environmental conditions of estuaries.

Large-scale prediction of tropical stream water quality using Rough Sets Theory

Assessing water quality in streams is usually measured at the local scale and often it is spatially restricted. To scale-up water-condition assessment, there is a need to use new tools that enable prediction of large-scale changes in water quality by expanding the analysis to landscape-levels and bioclimatic predictors. In addition, the traditional use of linear models in biomonitoring can be inappropriate in detecting complex relationships, such as changing patterns of aquatic community structure and complex environmental gradients. In this context, Artificial Intelligence (AI) techniques such as Rough Sets Theory (RST) can be particularly useful for dealing with vague, imprecise, inconsistent and uncertain knowledge involving biotic and abiotic data to enable the classification and prediction of changes in stream water. Here, we applied RST to estimate the water quality in streams of the Brazilian Atlantic Forest by analyzing connections between landscape and climate data with the inclusion of up to 15 families of aquatic insect groups from the orders Ephemeroptera, Plecoptera and Trichoptera (usually known as EPT taxa). First, we developed different decision sets which were the arrangements of the response variable (EPT index) and the predictor classifications. Then, we applied the best decision sets to monitor the condition of stream water in the Atlantic Forest on a large-scale. Our results showed the best decision rules were 61% accurate. Depending on the initial stream condition, this approach on a large-scale led to variable accuracy. By combining the development of different decision sets, the application of the best one on a large-scale, and the use of open-access data (landscape and climate predictors), our study approach demonstrated the potential applicability to evaluate streams in an objective with low-cost manner. This method can complement the environmental assessment of streams based only on local variables. Our framework also creates new perspectives in the analysis of water quality to generate scenarios of changes in streams based on landscape measurements to optimize monitoring networks.

Patterns in intraspecific variation in root traits are species‐specific along an elevation gradient

Abstract Intraspecific trait variation is an important driver of plant performance in different environments. Although roots acquire essential resources that vary with the environment, most studies have focused on intraspecific variation in leaf traits, and research on roots is often restricted to a few species. It remains largely unclear how and to what extent root traits vary with the environment and whether general intraspecific patterns exist across species. We compared intraspecific variation in specific root length (SRL), root diameter, root tissue density (RTD) and root branching density of 11 species along a 1,000 m elevation gradient in the French Alps. We tested (a) the extent of intraspecific versus interspecific root trait variation along the gradient, (b) whether intraspecific trait patterns with elevation were consistent among species and (c) whether environmental variables better explained intraspecific variation in root traits than elevation. Specifically, we hypothesised that within a species, root trait values would adjust to enhance resource acquisition (either through an increase in SRL or root diameter, and/or in branching density) and/or conservation (increased RTD) at higher elevations. Species identity explained most of the overall variation in root traits. Elevation explained only a minor proportion of intraspecific root trait variation, which was larger within than between elevations. Also, trait relationships with elevation rarely agreed with our hypotheses, varied strongly across species and were often differently related to environmental variation. Generally, climate, soil and vegetation properties better explained intraspecific root variation than elevation, but these relationships were highly species‐dependent. Along complex environmental gradients where multiple properties simultaneously change, roots of different species vary in different ways, leading to species‐specific patterns in intraspecific root trait variation. The lack of support for our hypotheses may be caused by the multiple interactions between environmental properties, small‐scale soil heterogeneity, species phylogeny and changing plant–plant interactions. Our findings suggest that, to enhance our understanding of the effects of environmental change on plant performance, we need to better integrate the multiple dimensions of plant responses to change and measure a broader set of root traits and environmental variables. A free Plain Language Summary can be found within the Supporting Information of this article.

Composite landscape predictors improve distribution models of ecosystem types

AbstractAimDistribution modelling is a useful approach to obtain knowledge about the spatial distribution of biodiversity, required for, for example, red‐list assessments. While distribution modelling methods have been applied mostly to single species, modelling of communities and ecosystems (EDM; ecosystem‐level distribution modelling) produces results that are more directly relevant for management and decision‐making. Although the choice of predictors is a pivotal part of the modelling process, few studies have compared the suitability of different sets of predictors for EDM. In this study, we compare the performance of 50 single environmental variables with that of 11 composite landscape gradients (CLGs) for prediction of ecosystem types. The CLGs represent gradients in landscape element composition derived from multivariate analyses, for example “inner‐outer coast” and “land use intensity.”LocationNorway.MethodsWe used data from field‐based ecosystem‐type mapping of nine ecosystem types, and environmental variables with a resolution of 100 × 100 m. We built nine models for each ecosystem type with variables from different predictor sets. Logistic regression with forward selection of variables was used for EDM. Models were evaluated with independently collected data.ResultsMost ecosystem types could be predicted reliably, although model performance differed among ecosystem types. We identified significant differences in predictive power and model parsimony across models built from different predictor sets. Climatic variables alone performed poorly, indicating that the current climate alone is not sufficient to predict the current distribution of ecosystems. Used alone, the CLGs resulted in parsimonious models with relatively high predictive power. Used together with other variables, they consistently improved the models.Main conclusionsOur study highlights the importance of variable selection in EDM. We argue that the use of composite variables as proxies for complex environmental gradients has the potential to improve predictions from EDMs and thus to inform conservation planning as well as improve the precision and credibility of red lists and global change assessments.

Abundant fungi adapt to broader environmental gradients than rare fungi in agricultural fields.

Soil communities are intricately linked to ecosystem functioning, and a predictive understanding of how communities assemble in response to environmental change is of great ecological importance. Little is known about the assembly processes governing abundant and rare fungal communities across agro-ecosystems, particularly with regard to their environmental adaptation. By considering abundant and rare taxa, we tested the environmental thresholds and phylogenetic signals for ecological preferences of fungal communities across complex environmental gradients to reflect their environmental adaptation, and explored the factors influencing their assembly based on the large-scale soil survey in agricultural fields across eastern China. We found that the abundant taxa exhibited remarkably broader response thresholds and stronger phylogenetic signals for the ecological preferences across environmental gradients compared to the rare taxa. Neutral processes played a key role in shaping the abundant subcommunity compared to the rare subcommunity. Null model analysis revealed that the abundant subcommunity was less clustered phylogenetically and governed primarily by dispersal limitation, while homogeneous selection was the major assembly process in the rare subcommunity. Soil available sulfur was the major factor mediating the balance between stochastic and deterministic processes of both the abundant and rare subcommunities, as indicated by an increase in stochasticity with higher available sulfur concentration. Based on macroecological spatial scale datasets, our study revealed the potential broader environmental adaptation of abundant fungal taxa compared to rare fungal taxa, and identified the factors mediating their distinct community assembly processes in agricultural fields. These results contribute to our understanding of the mechanisms underlying the generation and maintenance of fungal diversity in response to global environmental change.