Generalized Dissimilarity Modeling Research Articles

Temporal changes in spatial scale and autocorrelation structure of forest openings based on taxonomic, phylogenetic, and functional turnover

ContextDuring European settlement, Illinois grasslands were converted for agricultural purposes. Remaining natural areas in southern Illinois include natural xeric forest openings, with communities representative of remnant grasslands and adjacent hardwood forests. Previous research in these openings shows plant communities are driven by edaphic conditions. ObjectivesThe first objective aimed to characterize spatial scale and autocorrelation structure of these openings based on climatic, environmental, and diversity variables. The second objective was to predict taxonomic, phylogenetic, and functional turnover between 1988 and 2019, using climatic and environmental variables. MethodsSurveys were conducted to calculate taxonomic, phylogenetics and functional trait metrics and analyses of these dimensions of diversity. Randomization tests were used to assess phylogenetic and functional clustering and over-dispersion at each site. Spatially-explicit climatic and environmental variables were included from earlier surveys and data repositories. Global Moran's I and spatial autocorrelograms were used to assess spatial structure of climatic, environmental, and diversity variables and generalized dissimilarity modeling was used to characterize taxonomic, phylogenetic, and functional turnover based on environmental variables. ResultsSoil depth was the only environmental variable which exhibited significant global spatial autocorrelation. Overall, sandstone sites were phylogenetically over-dispersed while loess sites were phylogenetically clustered. Climate variables and diversity metrics exhibited significant spatial structure during surveys. Generalized dissimilarity models showed that geographic distance between openings was the most influential driver of turnover across surveys. ConclusionsPrevious glacial events explained the spatial structure of soil depth across sites, due to Quaternary loess deposition in loess sites. High diversity values were clustered in the southeastern portions of the study area. Functional generalized dissimilarity models best predicted turnover in these openings compared to taxonomic and phylogenetic models.

Integrated environmental and genomic analysis reveals the drivers of fine‐scale divergence and local adaptation in northern populations of two wild rice species in China

Societal Impact StatementCrop wild relatives represent precious genetic resources for crop improvement. Investigating their local adaptation to marginal environments is important for the utilization of wild genetic resources. Oryza officinalis and Oryza granulata are wild relatives of cultivated rice and possess genes that convey resistance to insects, disease, and tolerance to shade and drought. The northern edge for the distribution of these two lies in China where populations are facing habitat destruction. This study found that the northern marginal populations of both species have adapted to local conditions, with specific implications for the conservation and utilization of wild rice.Summary O. officinalis and O. granulata, wild relatives of cultivated rice, represent important gene reservoirs with the potential to improve rice with respect to insect resistance and stress tolerance. However, the northern marginal populations of these two species in China are facing habitat destruction. Here, we investigated the genetic diversity and divergence of northern marginal populations of O. officinalis and O. granulata. The genomic variation of two species was examined by whole‐genome sequencing on 357 individuals. Generalized dissimilarity modeling was applied to investigate the effects of geographic and environmental isolation on population differentiation. Genetic‐environment association analysis and genome‐wide FST outlier scans were used to identify environmentally driven signals of selection. The marginal populations of both species exhibited low genetic diversity and obvious genetic differentiation stemmed from the joint effects of isolation by geographic distance and the environment. Both genomes exhibited specific signals of adaptation to cold environments in the north. Investigation of the divergence and adaptation of marginal populations of O. officinalis and O. granulata will help us to determine how wild rice can adapt to local environments, thus allowing for the development of scientific conservation policies and the identification of new genetic resources for rice with improved resistance.

Fish Beta Diversity Patterns across Environmental Gradients in 63 European Shallow Lakes: Effects of Turbidity, Nutrient Enrichment, and Exotic Species

The beta diversity among lakes is affected by natural environmental sorting, dispersal constraints, and anthropogenic disturbances. We hypothesized that fish beta diversity would increase towards lower latitudes and be higher in less disturbed lakes at within-region scale, but environmental disturbances could affect these patterns due to community homogenization or heterogenization (e.g., gain of exotic species) among lakes. We used generalized dissimilarity modeling to assess the relative importance of geographic distance, climate, and environmental heterogeneity on fish beta diversity across Denmark, Belgium/The Netherlands, and Spain. We also tested whether differences in beta diversity changed between lake types (e.g., clear vs. turbid lakes and lakes with vs. without exotics fish) within-region and across latitude. Beta diversity increased from Denmark to Spain and geographic distance and climate variability were the main drivers of community change across latitude, but the rate of change varied between lake types. At the within-region scale, factors such as turbidity, lake size, and presence of exotics had varying impacts on beta diversity (i.e., increasing, decreasing, or no effect) across the three regions. Our findings suggest that understanding the effects of environmental disturbances on beta diversity requires consideration of both biogeographic and local factors.

Chilean bee diversity: Contrasting patterns of species and phylogenetic turnover along a large‐scale ecological gradient

AbstractChile's isolation and varied climates have driven the evolution of a unique biodiversity with a high degree of endemism. As a result, Chile encompasses diverse environments, including the Mediterranean‐type ecosystem, a global biodiversity hotspot. These environments are currently threatened by anthropogenic land use change impacting the integrity of local biomes and associated species. This area is the most intensively sampled in the country with high endemicity of native bee species. Characterizing habitat requirements of bees is a pressing priority to safeguard these insects and the ecosystem services they provide. We investigated broadscale patterns of bee (Hymenoptera: Apoidea: Anthophila) diversity using newly accessible expert‐validated datasets comprising digitized specimen records from Chilean and US collections, and novel expert‐validated‐type specimen data for the bees of Chile. We used a generalized dissimilarity modeling (GDM) approach to explore both compositional and phylogenetic β‐diversity patterns across latitudinal, altitudinal, climate, and habitat gradients in well‐sampled bee assemblages in Central Chile. Using the GDM measures of increasing compositional and environmental dissimilarity, we categorized and compared the most important drivers of these patterns and used them to classify “wild bee ecoregions” (WBEs) representing unique assemblages. Turnover of bee assemblages was explained primarily by latitudinal variation (proxy for climate) from south to north in Chile. However, temperature variations, precipitation, and the presence of bare soil also significantly explained turnover in bee assemblages. In comparison, we observed less turnover in phylogenetic biodiversity corresponding to spatial gradients. We identified six de novo ecoregions (WBEs), all with distinct taxa, endemic lineages, and representative species. The WBEs represent distinct spatial classifications but have similarities to existing biogeographical classifications, ecosystems, and bioclimatic zones. This approach establishes the baseline needed to prioritize bee species conservation efforts across this global biodiversity hotspot. We discuss the novelty of this classification considering previous biogeographical characterizations and their relevance in assessing conservation priorities for bee conservation. We argue that Chile's WBEs highlight areas in need of funding for bee species surveys and description, distribution mapping, and strengthening of conservation policies.

Uncovering the determinants of biodiversity hotspots in China: Evidence from the drivers of multiple diversity metrics on insect assemblages and implications for conservation

Understanding large-scale biodiversity patterns and underlying mechanisms during the formation process is essential for guiding conservation efforts. However, previous studies on the identification and formation mechanism of diversity hotspots in China were often limited to a single (alpha) diversity metric, while multiple (beta or zeta) diversity has rarely been used for exploring drivers and conservation actions. Here, a comprehensive species distribution dataset consisting of representative families of three insect orders was compiled to explore biodiversity hotspots based on different algorithms. Furthermore, to assess the effects of environmental factors on hotspots, we fitted generalized additive mixed-effects models (GAMMs) for species richness, generalized dissimilarity models (GDMs) and multi-site generalized dissimilarity modeling (MS-GDM) for the total beta and zeta diversity. Our results showed that biodiversity hotspots were mainly concentrated in central and southern China, especially in mountainous areas with complex topography, which indicated the insects' affinity to montane environments. Further analyses based on multiple models showed that water-energy factors exerted the strongest explanatory power for the insect assemblage diversity in hotspots of both alpha and beta (or zeta) levels. Additionally, anthropogenic factors also exerted a significant effect on hotspots, and this effect was higher for beta diversity than for alpha diversity. Overall, our study elucidates a comprehensive analysis of the identification and underlying mechanism of biodiversity hotspots in China. Despite several limitations, we still believe that our findings can provide some new insights for conservation efforts in Chinese hotspots.

Fatores associados à diversidade beta de macrófitas na Baía de Caxiuanã, localizada na Amazônia Oriental

Abstract Aim In this study, we investigated the beta diversity of macrophytes (total, turnover, and nestedness) in Caxiuanã Bay, localized in the Eastern Amazon. We also investigated the environmental factors determining the beta diversity and its components. Methods Macrophytes and physical-chemical variables (pH, water temperature, electrical conductivity, dissolved oxygen, and water turbidity) were sampled in 45 sites in 2017. Beta diversity was calculated based on Jaccard dissimilarity (using a presence/absence matrix) and partitioned in turnover and nestedness. We performed a Generalized Dissimilarity Modeling to analyze the influence of local (physical-chemical) and spatial factors (geographic distance) on total beta diversity and its components. Results A total of 16 macrophyte species were identified belonging to five morphological groups (free-floating, emergent, submerged, epiphytes, and rooted with floating leaves). The total beta diversity of macrophytes was 0.29, the turnover component had the highest contribution to total beta compared to nestedness. The beta total was influenced by geographic distance and conductivity, turnover by geographic distance and turbidity, and nestedness was explained by conductivity and pH. Conclusions In our study, physical-chemical factors influenced the structure of the macrophyte community, indicating that niche processes (deterministic) were acting and changing species composition. However, the spatial component and the low explanatory power of the models, especially for turnover, can also indicate the influence of stochastic processes such as ecological drift and/or limitations in dispersal. Our study provides new insights into the diversity patterns of macrophytes in Amazonian ecosystems, particularly in blackwater rivers. Our data also contribute to a better understanding of the processes that structure the species composition of macrophytes in these environments.

Using the Zeta (ζ) diversity approach for understanding the effects of variations in climatic covariates, vegetation patterns, and human influence on species composition of arboreal frogs in India

The biodiversity patterns of an ecosystem provide an opportunity for understanding the drivers of the community structure and, together, interpreting better conservation strategies for the species. Here we map the patterns in compositional turnover of the arboreal frog species (Anura: Rhacophoridae) in India and explore the impacts of climatic covariates, vegetation patterns, and human influence on driving their species composition. Using the previously published data, we compiled the occurrence matrix for the species of nine genera of the family Rhacophoridae from India. The species turnover trends were analyzed using the zeta diversity decline and retention-rate analysis. We further used the multisite generalized dissimilarity modeling (MS-GDM) to test the variations in climatic, vegetational, and anthropogenic drivers that better explain the species turnover. The results suggested a low nestedness among the genera of arboreal frogs barring Polypedates and Raorchestes. The difference in the mean temperature of the warmest quarter in the colder temperature regime is the primary driver of the compositional turnover of arboreal frog species. Also, differences in the precipitation seasonality of the lower and higher precipitation regime emerged as a driver of the compositional turnover for some genera. The differences in diversity patterns and their corresponding drivers are ideally only species-specific or group-specific. We suggest their utility while designing conservation efforts for co-occurring groups in a region.

Effects of Edaphic Factors at Different Depths on β-Diversity Patterns for Subtropical Plant Communities Based on MS-GDM in Southern China

Previous research on the relationship between edaphic factors and species diversity patterns has mostly focused on topsoil between 0 and 30 cm, with less attention paid to deeper layers where many plant root systems are concentrated. Since considering deeper edaphic layers might help to unravel the maintenance mechanisms of plant diversity, in the present study we explored the relationship between vegetation β-diversity and a comprehensive set of soil chemical attributes at different depths. Based on vegetation and soil data from subtropical broad-leaved forest plots in the Nanling Mountains, China, we analyzed the driving factors of β-diversity patterns of trees, shrubs, and herbs using multi-site generalized dissimilarity modeling (MS-GDM). We found that the species composition dissimilarity of trees, shrubs, and herbs layers in the study area was highly diversified and dominated by species turnover components. Topsoil chemical properties were the best explainers for the β-diversity of trees (52.5%), followed by herbs (40.3%) and shrubs (21.8%). With the increase of soil depth, especially for depth >60 cm, soil chemical elements gradually lost explanatory power. Regarding the β-diversity of trees, it was mainly affected by altitude and available nitrogen (AN), total iron (Fe), and nickel (Ni) content in the soil of 0–60 cm depth. Concerning shrubs, the best β-diversity explainers were altitude, geographical distance, and nutrient elements of the soil above 40 cm. The main factors driving the β-diversity of herbs were altitude, total boron (B), total cadmium (Cd), and total nickel (Ni) of 0–40 cm soil. Overall, our results suggest that the environmental filtration process driven by altitude and soil factors, and dispersal limitations represented by geographical distance, affected the β-diversity patterns of Nanling forest communities.

Complex cycles of divergence and migration shape lineage structure in the common kingsnake species complex.

The Nearctic is a complex patchwork of habitats and geologic features that form barriers to gene flow resulting in phylogeographic structure and speciation in many lineages. Habitats are rarely stable over geologic time, and the Nearctic has undergone major climatic changes in the past few million years. We use the common kingsnake species complex to study how climate, geography, and history influence lineage formation over a large, complex landscape. Nearctic/North America. Common kingsnake, Lampropeltis getula, species complex. We analyzed genome-wide sequence data from 51 snakes spanning the majority of the species complex's range. We used population clustering, generalized dissimilarity modeling, and coalescent methods to identify the number of genetic clusters within the L. getula complex, infer the environmental correlates of genetic differentiation, and estimate models of divergence and gene flow among lineages. We identified three major lineages within the L. getula complex and further continuous spatial structure within lineages. The most important ecological correlates of genetic distance in the complex are related to aridity and precipitation, consistent with lineage breaks at the Great Plains/Desert ecotone and the Cochise Filter Barrier. Lineages are estimated to have undergone multiple rounds of isolation and secondary contact, with highly asymmetric migration occurring at present. Changing climates combined with a large and geologically complex landscape have resulted in a mosaic of discrete and spatially continuous genetic structure. Multiple rounds of isolation and secondary contact as climate fluctuated over the past ~4.4 My have likely driven the evolution of discrete lineages that maintain high levels of gene flow. Continuous structure is strongly shaped by aridity and precipitation, suggesting roles for major precipitation gradients in helping to maintain lineage identity in the face of gene flow when lineages are in geographic contact.

Disentangling the relative roles of geographical and ecological factors in driving genomic variations of a widely distributed bird across a longitudinal gradient

Unraveling geographical modes of speciation processes has been a longstanding topic in biogeography. Divergence can be driven by factors operating on multiple spatial scales, such as geographical distance (isolation by distance, IBD), landscape resistance (isolation by resistance, IBR) and environmental heterogeneity (isolation by environment, IBE). However, it is challenging to assess the relative contributions of such factors, which are usually autocorrelated with each other. On the basis of ~294 K nuclear single‐nucleotide polymorphisms from 53 samples, we integrated population genomics, geographical information and environmental variables to delineate genetic differentiation in the common pheasant Phasianus colchicus across a longitudinal gradient in northern China. Generalized dissimilarity modeling (GDM) was used to analyze the relative importance of IBD, IBR and IBE. We found that the common pheasant in northern China was grouped into six genetic clusters, which was consistent with the taxonomic affinities. Genetic diversity changed along the longitudinal gradient, reaching its lowest level at the eastern edge of the Qinghai–Tibetan Plateau (QTP). The spatial pattern of gene flow suggested that the mountains surrounding the QTP and the mountains in central China have acted as geographical barriers impeding common pheasant dispersal. GDM analysis indicated that environmental heterogeneity is the most important driver explaining the lineage divergence, which supports the IBE model. These results suggest that multiple isolation mechanisms shaped genetic diversity and genomic divergence in this wide‐ranging bird species. Together, our results underscore the importance of leveraging genome‐wide variations and ecological modeling to facilitate a deeper understanding of population divergence processes.

Turnover in butterfly communities and traits along an elevational gradient in the eastern Himalaya, India

AbstractBeta (β)‐diversity varies along environmental gradients, and understanding what drives such variation might provide insights into the factors that shape community structure from place to place. Here, we delineate the spatial pattern of β‐diversity, analyze its underlying mechanisms, and examine variation in functional traits of butterflies along an extensive elevational gradient (300–3000 m) in the eastern Himalaya, the largest mountain system in the world. We sampled butterflies at 16 sites along this gradient using a fixed‐width point count method and estimated habitat variables at each site. We obtained trait data from our field collections and secondary sources as necessary. We partitioned β‐diversity into its turnover, nestedness, balanced variation, and abundance gradient components. We used generalized dissimilarity modeling to determine the underlying mechanisms affecting the pattern of β‐diversity along the gradient. The pattern of β‐diversity in butterflies at adjacent sites exhibited a mid elevation peak. Dissimilarity between sites increased with the increase in distance between the sites. Turnover or the balanced variation made major contributions to the overall β‐diversity. Among the set of factors, actual evapotranspiration was positively correlated with β‐diversity. The trait‐based analysis revealed biogeographic affinity as the best predictor of community composition along the elevational gradient. The high β‐diversity arises from turnover rather than nestedness component. We conclude that the pattern of β‐diversity of butterflies in the Himalaya is largely due to environmental filtering rather than geographic extent.

Drivers of Taxonomic, Phylogenetic, and Functional Beta Diversity of Himalayan Riverine Birds

Abiotic and biotic factors drive compositional differences among local species assemblages. Determining the influence of different drivers on beta diversity patterns can provide insights into processes governing community organization. Examining beta diversity patterns along taxonomic, phylogenetic and functional dimensions enables a nuanced understanding of underlying processes that govern community assembly and dynamics. The dynamic and complex riparian habitats in the Himalaya, and the hyper-diverse riverine bird community offer a fascinating setup to examine the role of environmental factors in influencing community structuring. Using a large dataset on river bird communities from field census across multiple drainages in the Indian Himalaya, we aimed at discerning processes that structure these communities through an understanding of pair-wise dissimilarities in species composition across sites. We determined the relative contributions of turnover and nestedness in taxonomic, phylogenetic, and functional beta diversity patterns in the Eastern and Western Himalaya that differ in species richness. Generalized Dissimilarity Modeling was used to examine the relative contributions of climatic, geographic, and anthropogenic factors toward explaining different metrics of beta diversity. The riverine bird communities in the drier and seasonal Western Himalaya were poorer in species richness, more phylogenetically and functionally clustered than that in the Eastern Himalaya. The contribution of the turnover component to the overall beta diversity was higher than the nestedness component in river bird communities, particularly in the Eastern Himalaya. Habitat and climatic factors differentially influenced the beta diversity patterns in both Eastern and Western Himalaya, with river width consistently explaining a large variation in beta diversity in the east and the west. The results show that environmental filtering plays a crucial role in structuring riverine bird communities in the Himalayan headwaters, highlighting the need to ameliorate the threats posed by the slew of hydroelectric projects and forest loss in the region.

Can a national afforestation plan achieve simultaneous goals of biodiversity and carbon enhancement? Exploring optimal decision making using multi-spatial modeling

There is a growing awareness of the need to integrate climate and biodiversity policies. As forests play an important role in mitigating biodiversity loss and climate change, numerous countries have established goals and are managing their forests to achieve them. However, forest management measures and land prioritization may differ depending on the target chosen, leading to conflicts. This research aims to seek optimized national afforestation plans in the Republic of Korea by assessing trade-offs between plant biodiversity persistence and carbon stocks. To this end, afforestation scenarios were spatially established based on the national forest management plans, with a target of 5800 ha expansion by 2022. Generalized Dissimilarity Modeling (GDM) and Global Forest Model (G4M) were applied to the selected afforestable regions to obtain scenarios that maximize biodiversity and carbon, respectively. Furthermore, another afforestation scenario that considers both objectives equally, was proposed using spatial simulated annealing (SSA) optimization algorithm to mitigate trade-offs. The constructed scenarios were compared, both spatially and quantitatively. As a result, the maximization scenarios were found to have few overlapping areas, with both scenarios resulting in ~50% trade-offs. These findings reveal that there is no universal solution and different management strategies are needed to enhance biodiversity persistence and carbon stocks. Thus, to strike a balance among the various goals, forest management requires a compromise solution to minimize trade-offs. Our national-scale assessment can help to guide future planning of national forest management with the consideration of the joint goals of biodiversity and carbon enhancement.

Predicting climate change-related genetic offset for the endangered southern South American conifer Araucaria araucana

Understanding adaptive genetic variation is key for predicting the evolutionary response of species and populations to climate change, decisively influencing management and conservation decisions. Landscape genomics provides a framework to disentangle the effects of local adaptation from those of geographic distance and demographic history, through genomic analysis and the modeling of genotype-environment relationships. This approach can inform how evolutionary forces shape the neutral and adaptive genetic structure, helping to identify those populations subject to a greater risk of maladaptation due to anthropogenic climate change, i.e., the “genetic offset”. Using restriction-site associated DNA sequencing (RAD-Seq) and more than 49,000 single nucleotide polymorphisms screened from 12 locations of Araucaria araucana in Chile, we assessed the genetic structure and predicted the genetic offset of this emblematic tree species under two future climate scenarios. Using generalized dissimilarity modeling (GDM) we found that the temperature annual range was the most important variable shaping the observed patterns of adaptive divergence. Our results show that populations living in the piedmont of the southern Andes Mountain range are at the greatest risk of maladaptation, while populations living in the high elevation zones in the Andes Mountain range are at the lowest risk. This study constitutes an important tool for forestry management and conservation of A. araucana forests.

Intraspecies Genomic Divergence of a Fig Wasp Species Is Due to Geographical Barrier and Adaptation

Understanding how intraspecies divergence results in speciation has great importance for our knowledge of evolutionary biology. Here we applied population genomics approaches to a fig wasp species (Valisia javana complex sp 1) to reveal its intraspecies differentiation and the underlying evolutionary dynamics. With re-sequencing data, we prove the Hainan Island population (DA) of sp1 genetically differ from the continental ones, then reveal the differed divergence pattern. DA has reduced SNP diversity but a higher proportion of population-specific structural variations (SVs), implying a restricted gene exchange. Based on SNPs, 32 differentiated islands containing 204 genes were detected, along with 1,532 population-specific SVs of DA overlapping 4,141 genes. The gene ontology (GO) enrichment analysis performed on differentiated islands linked to three significant GO terms on a basic metabolism process, with most of the genes failing to enrich. In contrast, population-specific SVs contributed more to the adaptation than the SNPs by linking to 59 terms that are crucial for wasp speciation, such as host reorganization and development regulation. In addition, the generalized dissimilarity modeling confirms the importance of environment difference on the genetic divergence within sp1. Hence, we assume the genetic divergence between DA and the continent due to not only the strait as a geographic barrier, but also adaptation. We reconstruct the demographic history within sp1. DA shares a similar population history with the nearby continental population, suggesting an incomplete divergence. Summarily, our results reveal how geographic barriers and adaptation both influence the genetic divergence at population-level, thereby increasing our knowledge on the potential speciation of non-model organisms.

Spatial distribution patterns and predictors of fish beta‐diversity in a large dam‐free tributary from a Neotropical floodplain

AbstractUnderstanding how and why fish species composition varies between locations through beta‐diversity has received increased interest recently. The physical structure, extension and environmental characteristics along the river basins influence the dispersal of organisms, which ultimately affects metacommunity dynamics and biodiversity patterns. Here, we aimed to identify major breaks delimiting fish assemblages in a large dam‐free river basin on its main channel, which is almost pristine in hidrology, and to evaluate the influence of geo‐climatic variables in the observed beta‐diversity patterns. We used the statistical techniques Species Composition Interpolation (SCI) and Generalized Dissimilarity Modeling (GDM) to analyse beta‐diversity patterns based on georeferenced fish records from the Ivaí River basin. Ichthyofauna units were delimited, estimating the association between geo‐climatic predictors and beta‐diversity. We identified three major breaks delimiting fish assemblages in the Ivaí River basin (i.e. the upper, middle and lower sections). The fish communities were very distinct at the upper and lower sections, while the middle section was recovered as less differentiated. Turnover was the main component contributing to total beta‐diversity, and dissimilarity in fish species composition was moderately associated with geo‐climatic variables. Fish communities from the Ivaí River basin must be associated with niche‐based processes, and we hypothesize that dispersal processes can be equally significant at the basin scale. The investigations may produce insights on strategies for conservation and restoration of degraded rivers, contributing to the long‐term maintenance of fish communities and to the delimitation of new strategic areas for the effective conservation of freshwater biodiversity.

Modeling of Microlicieae (Melastomataceae) species composition provides insights into the evolution of campo rupestre vegetation on eastern Brazilian mountaintops

The Cadeia do Espinhaço (also referred to as “Espinhaço Range”) is a mountain range that extends for more than 1,200 km from northern Bahia to southern Minas Gerais in eastern Brazil. Mountains in the Cadeia do Espinhaço usually have impoverished soils and complex micro-habitats, where outstanding levels of endemism are found. Pleistocene glaciations are often considered as relevant events that shaped communities and favored speciation in this region. We used the statistical techniques of Species Composition Interpolation and Generalized Dissimilarity Modeling to analyze beta-diversity patterns across the Cadeia do Espinhaço, delimit floristic units, identify geo-climatic predictors of species composition, and estimate changes in communities during the Last Glacial Maximum and Mid-Holocene. We used as our study group the Microlicieae, a species-rich tribe of Melastomataceae with remarkable endemism in campo rupestre, the dominant vegetation type on mountaintops of the Espinhaço Range. Two breaks in species composition and three floristic regions (Southern Espinhaço, Septentrional Espinhaço, and Chapada Diamantina) were recognized for the study area. The floristic regions differed from each other in climate and matched geologic sections of the Cadeia do Espinhaço. Climatic predictors related to climate explained beta-diversity patterns better than geography. During the Last Glacial Maximum and Mid-Holocene, the Southern Espinhaço suffered less severe changes in species composition than the Septentrional Espinhaço and the Chapada Diamantina.

Forest management can mitigate negative impacts of climate and land-use change on plant biodiversity: Insights from the Republic of Korea

Over the past century, the decline in biodiversity due to climate change and habitat loss has become unprecedentedly serious. Multiple drivers, including climate change, land-use/cover change, and qualitative change in habitat need to be considered in an integrated approach, which has rarely been taken, to create an effective conservation strategy. The purpose of this study is to quantitatively evaluate and map the combined impacts of those multiple drivers on biodiversity in the Republic of Korea (ROK). To this end, biodiversity persistence (BP) was simulated by employing generalized dissimilarity modeling with estimates of habitat conditions. Habitat Condition Index was newly developed based on national survey datasets to represent the changes in habitat quality according to the land cover changes and forest management, especially after the ROK's National Reforestation Programme. The changes in habitat conditions were simulated for a period ranging from the 1960s to the 2010s; additionally, future (2050s) spatial scenarios were constructed. By focusing on the changes in forest habitat quality along with climate and land use, this study quantitatively and spatially analyzed the changes in BP over time and presented the effects of reforestation and forest management. The results revealed that continuous forest management had a positive impact on BP by offsetting the negative effects of past urbanization. Improvements in forest habitat quality also can effectively reduce the negative impacts of climate change. This quantitative analysis of successful forest restoration in Korea proved that economic development and urbanization could be in parallel with biodiversity enhancement. Nevertheless, current forest management practices were found to be insufficient in fully offsetting the decline in future BP caused by climate change. This indicates that there is a need for additional measures along with mitigation of climate change to maintain the current biodiversity level.

Identifying the Drivers of Spatial Taxonomic and Functional Beta-Diversity of British Breeding Birds

Spatial variation in community composition may be driven by a variety of processes, including environmental filtering and dispersal limitation. While work has been conducted on the relative importance of these processes on various taxa and at varying resolutions, tests using high-resolution empirical data across large spatial extents are sparse. Here, we use a dataset on the presence/absence of breeding bird species collected at the 10 km × 10 km scale across the whole of Britain. Pairwise spatial taxonomic and functional beta diversity, and the constituent components of each (turnover and nestedness/richness loss or gain), were calculated alongside two other measures of functional change (mean nearest taxon distance and mean pairwise distance). Predictor variables included climate and land use measures, as well as a measure of elevation, human influence, and habitat diversity. Generalized dissimilarity modeling was used to analyze the contribution of each predictor variable to variation in the different beta diversity metrics. Overall, we found that there was a moderate and unique proportion of the variance explained by geographical distance per se, which could highlight the role of dispersal limitation in community dissimilarity. Climate, land use, and human influence all also contributed to the observed patterns, but a large proportion of the explained variance in beta diversity was shared between these variables and geographical distance. However, both taxonomic nestedness and functional nestedness were uniquely predicted by a combination of land use, human influence, elevation, and climate variables, indicating a key role for environmental filtering. These findings may have important conservation implications in the face of a warming climate and future land use change.

Effects of human‐dominated landscape on the community structure of silphid and dung beetles collected by carrion pitfall traps

AbstractThe objective of this study was to evaluate the effects of landscape and local environmental factors on the community structure of carrion beetles (silphid and dung beetles) and the abundance of major species in artificial (agricultural and urban landscapes) and forest landscapes in northeastern Japan. Eight study sites were set up in forest landscapes, six in agricultural landscapes, and six in urban landscapes. From June to October 2019, we collected carrion beetles using 385 pitfall traps. A total of 2,119 carrion beetles belonging to 15 species were captured. This included six species of silphid beetles and nine species of dung beetles. The non‐metric multidimensional scaling (NMDS) for carrion beetle community showed that carrion beetles have different community structures in forest landscapes compared to other landscapes. Generalized dissimilarity modeling (GDM) showed that canopy openness and a landscape factor had the large influence on the community structure. The generalized linear mixed model (GLMM) showed that the abundance of the major species was low in open environments. This study indicates that the community structure of carrion beetles differs depending on the landscape in northeastern Japan. The local environment, especially the canopy openness, had a great influence on the community structure and abundance of carrion beetles. Anthropogenic changes at the landscape scale may alter carrion beetle community by significantly changing the local and surrounding environment.