Variation Partitioning Procedure Research Articles

Patterns of non‐migratory fish metacommunity from Neotropical floodplains: Local mechanisms, regional scale and hydrological dynamics

AbstractThe spatial distribution of biological communities may be regulated by environmental and spatial processes, and the intensity of these processes depend on the species characteristics, spatial heterogeneity and spatial extent. We investigated the relationship between the non‐migratory fish metacommunity with environmental and spatial variables using the variance partitioning procedure. We used data from lakes of four Neotropical floodplains: Amazon, Araguaia, Pantanal and Paraná. We hypothesised that the processes that drive the spatial distribution of non‐migratory fish in floodplain systems depend on connectivity driven by flood pulse. We predict that spatial variables are less important to explaining the fish community structures during rainy periods when there is no dispersal limitation. In contrast, environmental variables influence these structures during rainy and dry periods. During dry periods, metacommunities depend on species' dispersal abilities, but during rainy and dry periods, spatial distribution depends on the environmental filters selected by each species. For most of the environmental variables, it was possible to observe more similarity in the rainy period. Our results showed different patterns of fish communities for the lakes of the four floodplains systems, which led us to reject our hypothesis. Non‐migratory fish remain in their natal environment and perform only small lateral movements. In this scenario, we found a little influence from spatial variables in both periods and a great contribution of environmental variables for Amazon (16%) and Pantanal (32%) floodplains in structuring fishes' distribution in the rainy period.

Weed Species’ Diversity and Composition as Shaped by the Interaction of Management, Site, and Soil Variables in Olive Groves of Southern Greece

Gaining a comprehensive understanding of how weed communities respond to both environmental and human-induced factors is of paramount importance in developing effective and ecologically sound weed control strategies. The objectives of the current research were to (1) assess the effect of the main weed management practices used in Greek olive groves on weed species’ diversity; (2) explore the filtering effect of management, site, and soil variables in determining weed species’ composition; and (3) shed light on the association between weed species’ composition and the diversity of the understory vegetation of olive groves. To accomplish these objectives, winter weed species’ coverage was assessed in 116 olive groves, both conventional and organic, distributed across three provinces in southern Greece. The investigation encompassed 29 explanatory variables, categorized into three groups: soil (22), management practices (6), and site conditions (1). It was confirmed that glyphosate use may lower biodiversity and species richness; however, this trend was not universal. In fact, the negative influence of the presence of Oxalis pes-caprae L. on species richness and diversity far outweighed the effect of spraying glyphosate. Redundancy analysis (RDA) revealed that among the 29 variables used to describe the ecological niche, eight (i.e., Mn, Mg, chemical spraying, mowing, rotary tiller, grazing, irrigation, and elevation) were significant and explained 21.5% of the total variation in weed species’ data. Interestingly, the soil Mn concentration was identified as the most influential one, highlighting the importance of soil micronutrients in determining weed species’ composition. The variation partitioning procedure demonstrated that the effect of the management variables on weed species’ composition accounted for 2.2 times the variance of soil variables and 4.5 times the variance of elevation. The present findings might help to enhance optimal management in olive groves that can sustain the biodiversity of flora and, in turn, provide various ecosystem services to agro-ecosystems.

Eutrophication modifies the relationships between multiple facets of macroinvertebrate beta diversity and geographic distance in freshwater lakes

AbstractAimUnderstanding the distance–decay relationship (DDR) has been considered important because it reflects a combination of several ecological processes such as dispersal limitation and environmental sorting. However, effects of human disturbances on DDR are poorly known, especially in freshwater lakes. This study is aimed to examine how anthropogenic eutrophication modified the relationships between three facets (taxonomic, functional and phylogenetic) of macroinvertebrate beta diversity and geographic and environmental distances across 30 freshwater lakes.LocationThe Yangtze River floodplain, China.MethodsWe used Mantel tests to examine the relationships between multiple facets of assemblage dissimilarities (overall beta diversity, replacement and richness difference components) and geographic and environmental distances. Distance‐based redundancy analysis (dbRDA) and associated variation partitioning procedures were applied to explore the relative contributions of environmental and spatial factors on the three facets of beta diversity.ResultsWe found that none of the three beta diversity facets was related to geographic distance, but all were significantly related to environmental distance, mainly mirroring eutrophication‐related variables. Based on the variation partitioning approach, the macroinvertebrate assemblages examined were almost exclusively structured by environmental factors associated with eutrophication, while spatial variables had a negligible effect. Nevertheless, the different facets of beta diversity did not decrease (i.e., no homogenization trend) in lake groups showing the highest eutrophication levels, implying complex influences of anthropogenic disturbances in driving homogenization or differentiation in assemblage compositional dissimilarity.Main ConclusionsOur findings suggested that the high degrees of eutrophication acted as an environmental filter to significantly modify the spatial distance–decay relationships, possibly via decreasing the importance of dispersal limitation in shaping macroinvertebrate assemblages in the studied lakes. Given the sensitivity of beta diversity patterns to eutrophication we found in this study, we recommend that the role of anthropogenic disturbances should be incorporated into research on general ecological patterns like the DDR.

Large scale spatio-temporal modelling of risk factors associated with tuberculosis exposure at the wildlife-livestock interface.

The management of animal tuberculosis (TB) is a priority for European Union animal health authorities. However, and despite all the efforts made to date, a significant part of Spain has as yet been unable to obtain the officially tuberculosis-free (OTF) status. Information regarding wildlife disease status is usually scarce, signifying that the role played by wildlife is usually ignored or poorly assessed in large-scale TB risk factor studies. The National Wildlife Health Surveillance Plan in Spain now provides information on infection rates in wildlife reservoirs at a national level, but there are limitations as regards the sample size, the spatio-temporal distribution of the samples, and the lack of homogeneity of the diagnostic techniques employed. The objective of the study described herein was, therefore, to employ a Bayesian approach with the intention of identifying the risk factors associated with four TB rates in cattle: prevalence, incidence, maintenance and persistence in Spain during the period 2014-2019. The modeling approach included highly informative spatio-temporal latent effects with which to control the limitations of the data. Variation partitioning procedures were carried out, and the pure effect of each factor was mapped in order to identify the most relevant factors associated with TB dynamics in cattle in each region. This made it possible to disclose that the movement of cattle, particularly from counties with herd incidence >1%, was the main driver of the TB dynamics in cattle. The abundance of herds bred for bullfighting was retained in all four models, but had less weight than the movements. After accounting for farm-related factors, the TB prevalence in wild boar was retained in all the models and was significantly related to incidence, maintenance and persistence. With regard to the incidence, variation partitioning revealed that wildlife was the most explicative factor, thus suggesting that it plays a role in the introduction of the pathogen into uninfected herds, and consequently highlighting its importance in breakdowns. These results show, for the first time on a national scale, that wild ungulates play a relevant role in the spatio-temporal variability of TB in cattle, particularly as regards their disease status. Moreover, the spatial representation of the pure effect of each factor made it possible to identify which factors are driving the disease dynamics in each region, thus showing that it is a valuable tool with which to focus efforts towards achieving the OTF status.

Changes in plant biodiversity facets of rocky outcrops and their surrounding rangelands across precipitation and soil gradients

Climate and soil factors induce substantial controls over plant biodiversity in stressful ecosystems. Despite of some studies on plant biodiversity in extreme ecosystems including rocky outcrops, simultaneous effects of climate and soil factors have rarely been studied on different facets of biodiversity including taxonomic and functional diversity in these ecosystems. In addition, we know little about plant biodiversity variations in such extreme ecosystems compared to natural environments. It seems that environmental factors acting in different spatial scales specifically influence some facets of plant biodiversity. Therefore, we studied changes in taxonomic and functional diversity along precipitation and soil gradients in both landscapes (i) rocky outcrops and (ii) their nearby rangeland sites in northeast of Iran. In this regard, we considered six sites across precipitation and soil gradients in each landscape, and established 90 1m2 quadrates in them (i.e. 15 quadrats in each site; 15 × 6 = 90 in each landscape). Then, taxonomic and functional diversity were measured using RaoQ index, FDis and CWM indices. Finally, we assessed impacts of precipitation and soil factors on biodiversity indices in both landscapes by performing regression models and variation partitioning procedure. The patterns of taxonomic diversity similarly showed nonlinear changes along the precipitation and soil factors in both landscapes (i.e. outcrop and rangeland). However, we found a more negative and significant trends of variation in functional diversity indices (except for CWMSLA) across precipitation and soil factors in outcrops than their surrounding rangelands. Variations of plant biodiversity were more explained by precipitation factors in surrounding rangelands, whereas soil factors including organic carbon had more consistent and significant effects on plant biodiversity in outcrops. Therefore, our results represent important impacts of soil factors in structuring plant biodiversity facets in stressful ecosystems. While, environmental factors acting in regional and broad scales such as precipitation generally shape vegetation and plant biodiversity patterns in natural ecosystems. We can conclude that rocky outcrops provide suitable microenvironments to present plant species with similar yields that are less able to be present in rangeland ecosystems.

Multivariate analyses of the vegetation of the western Himalayan forests of Muzaffarabad district, Azad Jammu and Kashmir, Pakistan

Abstract Muzaffarabad district, Azad Jammu and Kashmir, Pakistan is part of the western Himalaya and rich in phytodiversity, but until now little was known about its plant diversity on larger spatial scale and vegetation composition through multivariate statistical tools. To fill this research gap, the whole district was ecologically explored for the collection of field data from August 2014 to July 2016. For vegetation studies, a total of 16 altitudinal transects comprising 110 sampling stations (samples) with 990 plots were studied by using a stratified random vegetation sampling method. Different multivariate statistical tools including Monte Carlo permutation test, Indicator species analysis, hierarchical clustering, ordination, variation partitioning and multi-response permutation procedures tests were used for the first time for the study area to elucidate the number of significant vegetation groups, ranking and placement of plant species in these groups, classification of vegetation units, detection of important gradients, importance of groups of environmental variables and pairwise compositional differences of the species groups respectively. The results showed that all the recorded 343 plant species belong to seven significant plant associations which were further placed into 5 major forest types. Out of the total 19 variables studied, CCA detected the significant contribution of the majority (simple effects: 12; unique effects: 8) of them. The latter (unique effects) in descending order included altitude, forest cover, deforestation, community maturity, forest density, latitude, slope aspect, and longitudinal variations. Similarly, variation partitioning results depicted that topography was the leading driver affecting vegetation distribution, followed by the biotic and edaphic factors. The forest edges, especially the sub-alpine ecosystem, were most diverse, supported higher tree density and also faced maximum deforestation pressure. Furthermore, rangelands in the temperate to alpine zones were affected by heavy overgrazing. Due to the disrupted local ecosystem functioning, the study area needs proper management and conservations plans to save its biodiversity wealth in this part of western Himalaya.

Local environment and space drive multiple facets of stream macroinvertebrate beta diversity

AbstractAimUnderstanding variation in biodiversity typically requires consideration of factors operating at different spatial scales. Recently, ecologists and biogeographers have recognized the need of analysing ecological communities in the light of multiple facets including not only species‐level information but also functional and phylogenetic approaches to improve our understanding of the relative contribution of processes shaping biodiversity. Here, our aim was to disentangle the relative importance of environmental variables measured at multiple levels (i.e., local, catchment, climate, and spatial variables) influencing variation in macroinvertebrate beta diversity facets (i.e., species, traits, and phylogeny) and their components (i.e., replacement and abundance difference) in boreal streams.TaxonAquatic macroinvertebratesLocationWestern FinlandMethodsA total of 105 streams were sampled in western Finland, encompassing a geographical extent over 500 km. We analysed variation in the different beta diversity facets and components using distance‐based redundancy analysis and associated variation partitioning procedures. We modelled spatial structures using distance‐based Moran eigenvector maps.ResultsWe found that the relative influence of explanatory variables on each diversity facet and component revealed relatively similar patterns. Our main finding was that local environmental and spatial variables generally contributed most to the total explained variability in all facets and components of beta diversity, whereas catchment and climate variables explained less variation in the beta diversity facets at the spatial scale considered in this study.Main conclusionsDifferent facets of beta diversity were mainly influenced by local environmental variables and spatial structuring, likely acting through deterministic and stochastic pathways respectively. Identifying the ecological variables and mechanisms that drive variation in beta diversity may be used to guide the conservation and restoration efforts for biodiversity under global change.

Beyond neutrality: disentangling the effects of species sorting and spurious correlations in community analysis

The methods of direct gradient analysis and variation partitioning are the most widely used frameworks to evaluate the contributions of species sorting to metacommunity structure. In many cases, however, species are also driven by spatial processes that are independent of environmental heterogeneity (e.g., neutral dynamics). As such, spatial autocorrelation can occur independently in both species (due to limited dispersal) and the environmental data, leading to spurious correlations between species distributions and the spatialized (i.e., spatially autocorrelated) environment. In these cases, the method of variation partitioning may present high Type I error rates (i.e., reject the null hypothesis more often than the pre-established critical level) and inflated estimates regarding the environmental component that is used to estimate the importance of species sorting. In this paper, we (1) demonstrate that metacommunities driven by neutral dynamics (via limited dispersal) alone or in combination with species sorting leads to inflated estimates and Type I error rates when testing for the importance of species sorting; and (2) propose a general and flexible new variation partitioning procedure to adjust for spurious contributions due to spatial autocorrelation from the environmental fraction. We used simulated metacommunity data driven by pure neutral, pure species sorting, and mixed (i.e., neutral+species sorting dynamics) processes to evaluate the performances of our new methodological framework. We also demonstrate the utility of the proposed framework with an empirical plant dataset in which we show that half of the variation initially due to the environment by the standard variation partitioning framework was due to spurious correlations.

Aquatic community structure in Mediterranean edge-of-field waterbodies as explained by environmental factors and the presence of pesticide mixtures.

Studies addressing the predicted effects of pesticides in combination with abiotic and biotic factors on aquatic biota in ditches associated with typical Mediterranean agroecosystems are scarce. The current study aimed to evaluate the predicted effects of pesticides along with environmental factors and biota interactions on macroinvertebrate, zooplankton and phytoplankton community compositions in ditches adjacent to Portuguese maize and tomato crop areas. Data was analysed with the variance partitioning procedure based on redundancy analysis (RDA). The total variance in biological community composition was divided into the variance explained by the multi-substance potentially affected fraction [(msPAF) arthropods and primary producers], environmental factors (water chemistry parameters), biotic interactions, shared variance, and unexplained variance. The total explained variance reached 39.4% and the largest proportion of this explained variance was attributed to msPAF (23.7%). When each group (phytoplankton, zooplankton and macroinvertebrates) was analysed separately, biota interactions and environmental factors explained the largest proportion of variance. Results of this study indicate that besides the presence of pesticide mixtures, environmental factors and biotic interactions also considerably influence field freshwater communities. Subsequently, to increase our understanding of the risk of pesticide mixtures on ecosystem communities in edge-of-field water bodies, variations in environmental and biological factors should also be considered.

Macroinvertebrate community in relation to water quality and riparian land use in a substropical mountain stream, China.

Exploring how water quality and land use shape the benthic macroinvertebrate community composition is of widespread interest in biodiversity conservation and environmental management. In this study, we investigated the structures of benthic macroinvertebrate assemblages and their environmental controls in terms of water quality and riparian land use in the Jinshui River, China. We carried out three campaigns including wet season (August 2009), dry season (November 2009), and normal season (April 2010) based on the hydrological regime in Jinshui basin. The result showed that macroinvertebrate assemblage variations were better explained by water quality factors than land use based on variance partitioning procedure. The land use of 2km upstream from the sampling sites had explained more variation than that of the whole riparian zone in upstream catchment on macroinvertebrate community, and land use of 2km upstream also had more interactions with water quality. Canonical correspondence analysis (CCA) indicated that the elements or nutrient of magnesium (Mn), selenium (Se), strontium (Sr), silicon (Si), dissolved inorganic nitrogen (DN), sulfur (S), total organic carbon (TOC), and total nitrogen (TN) in water exhibited a strong relationship with macroinvertebrate assemblages. However, the variance in water quality explained by land use was lower than that explained by water quality in rivers using redundancy analysis. Our study suggested that proximate factors (i.e., water quality) were more important to interpret the macroinvertebrate community compared to ultimate factors (i.e., land use) for macroinvertebrate assemblages in river system.

Regression commonality analyses on hierarchical genetic distances

Landscape genetics is emerging as an important way of supporting decision‐making in landscape management, in response to the deterioration of matrix permeability due to habitat loss and fragmentation. In line with unremitting methodological developments in landscape genetics, a new analytical procedure was recently proposed as a way of evaluating the effects of landscape gradients on genetic structures. This procedure is based on the computation of inter‐individual hierarchical genetic distances (HGD), a metric of genetic differentiation taking into account the hierarchical structure in populations as inferred from clustering algorithms. HGD can be used as dependent variables in multivariate regressions to assess the effects of various landscape predictors on spatial patterns of genetic differentiation. However, multicollinearity may obscure the interpretation of multivariate regressions. We illustrate how regression commonality analyses (CA), a detailed variance partitioning procedure that can be used to deal with multicollinearity issues, can thoroughly improve our understanding of landscape connectivity when HGD are used as a dependent variable, with the red deer Cervus elaphus as an empirical example. Using logistic regression commonality analyses on HGD, we showed that semi‐natural open areas, transportation infrastructures and, to a lesser extent, urban areas and rivers, were associated with an increase in hierarchical genetic differentiation in red deer. Regressions based on HGD provided detailed results that could not have been obtained with regressions based on standard genetic distances, with notably additional insights as to the possible influence of linear features such as roads and highways on landscape connectivity. Furthermore, CA helped identify synergistic associations among variables as well as suppressors, thus resolving inconsistencies among hierarchical levels and revealing spurious correlations that may have gone unnoticed in the course of classical regression analyses. We thus recommend the use of regression commonality analysis on hierarchical genetic distances as a promising statistical tool for landscape geneticists.

Different roles of environmental variables and spatial factors in structuring stream benthic diatom and macroinvertebrate in Yangtze River Delta, China

Exploring the relative contribution of spatial factors and environmental variables in shaping communities is of widespread interest in biodiversity conservation and environmental management. Stream communities are hierarchically regulated by environmental variables over multiple spatial scales, and the reaction of different organisms to stressors are still equivocal. We sampled both macroinvertebrates and diatom at 80 sites and additional 10 sites for macroinvertebrates, field measured and laboratory analyzed environmental variables, from the tributaries of Qiantang River, Yangtze River Delta China in 2011. We used PCNM (principal coordinates of neighbor matrices) to generate spatial predictors. We applied redundancy analysis and variation partitioning procedures to identify key spatial and environmental factors, and to quantify their relative roles in shaping diatom and macroinvertebrate assemblages. Our results demonstrated the role of spatial and environmental variables differed in shaping benthic diatom and macroinvertebrate. Diatom assemblage variations were better explained by spatial factors, however macroinvertebrate assemblage variations were better explained by environmental variables. In terms of environmental variables, catchment scale variables (e.g., land use estimators, land use diversity) played the primary role in determining the patterns of both diatom and macroinvertebrate assemblages, whereas the influence of reach-scale variables (e.g., pH, substrates, and nutrients) appeared less. However, nutrients were the stronger factors influencing benthic diatom, whereas physical habitat (e.g., substrates) played more important role than water chemistry in structuring macroinvertebrates. Our results provided more evidence to the incorporation of spatial factors interpreting spatial patterns of stream organisms, and highlighted the useful of multiple organisms and environmental variables at different spatial scales in diagnosing mechanism of stream degradation and in building a sound stream conditions monitoring program for Yangtze River Delta.

The effect of pesticides on the composition of aquatic macrofauna communities in field ditches

Ditches surrounding agricultural fields in the Netherlands are predominantly used for flood control, and they accommodate aquatic plant and animal species. Studies addressing the effects of pesticides in combination with abiotic and biotic factors on aquatic biota in ditches are scarce. The current study aimed to investigate the effects of pesticides along with environmental factors, presence of other biota and time on the community composition of aquatic macrofauna in ditches next to flower bulb fields and pastures. Macrofauna samples and environmental data were collected during two consecutive years. Ponds in a sandy dune area of a nature reserve next to the polders were sampled as control sites. Data was analyzed with the variance partitioning procedure based on the redundancy analysis (RDA). The total variance in macrofauna community composition was divided into the variance explained by pesticides, environmental factors (water chemistry parameters and macrophyte coverage), time (study year and the number of the month), shared variance, and unexplained variance. The total explained variance in macrofauna community reached 22.6%. The largest proportion of explained variance was attributed to environmental factors (10.1%) followed by pesticides (5.4%) and time (4.8%). When each macrofauna group was analyzed separately, presence of other biota and environmental factors explained the largest proportion of variance in most of the macrofauna groups. Results of the study indicate that environmental factors, biotic interactions and temporal variation influence freshwater macrofauna considerably along with pesticides. We suggest that environmental managers should consider the multiple stressor contexts of aquatic ecosystems.

Scale‐specific processes shape plant community patterns in subtropical coastal grasslands

AbstractProcesses responsible for shaping community patterns act at specific spatial scales. In this study, we aimed at disentangling the effects of climate, soil and space as drivers of variation in a coastal grassland plant community. We were specifically interested in evaluating the relative influence of those processes at broad and fine spatial scales as well as when considering species groups with good and poor long‐distance dispersal capacity. We sampled grassland vegetation at 16 sites distributed along a latitudinal gradient of more than 500 km in subtropical southern Brazil and used variation partitioning procedures to ascertain the relative influence of climatic, edaphic and spatial processes on variation in species composition at different spatial scales, considering the entire community and subsets with only species from the Asteraceae family (good long‐distance dispersal) and Poaceae (poor long‐distance dispersal). Climatic filters were the most responsible for shaping grassland community composition at the broad scale, while edaphic filters showed higher importance at the fine scale. When not considering the influence of spatial scale, we observed higher influence of climate structured in space. Composition patterns of species with poor long‐distance dispersal (Poaceae) were more closely related to spatial variables than those of species with effective dispersal (Asteraceae). Our results stressed the importance of addressing different spatial scales to rightly ascertain the magnitude that different drivers exert on plant community assembly. Dividing the community into groups with different dispersal abilities proved useful for a more detailed understanding of the community assembly processes.

Macroecological factors explain large-scale spatial population patterns of ancient agriculturalists

Aim: It has been well demonstrated that the large-scale distribution patterns of numerous species are driven by similar macroecological factors. However, understanding of this topic remains limited when applied to our own species. Here we take a large-scale look at ancient agriculturalist populations over the past two millennia. The main aim of this study was to test the hypothesis that the patterns of agriculturalist populations were shaped by relevant macroecological factors. Location: China. Methods: Using detailed historical census data, we reconstructed spatial patterns of human population density over 13 imperial dynasties in ancient China, which was dominated by agrarian societies. We used simultaneous autoregressive models to examine the population densities of agriculturalists in relation to climatic, topographic, edaphic and hydrological variables, together with the spatial structure of a concentration of population toward national capitals. The pure and shared effects of these variables and the population-concentration structure were decomposed using a variation partitioning procedure. Results: Spatial population patterns of ancient agriculturalists can be well modelled by climate, topography, soil properties and local hydrological systems. A plausible explanation is that by influencing crop yield these environmental factors essentially drive the distribution of agriculturalists. The population-concentration structure can also explain agriculturalist patterns to a considerable extent. This structure and those environmental factors have largely shared effects in simultaneously shaping these agriculturalist patterns. Main conclusions: While humans can effectively temper environmental constraints at small spatial scales, our results demonstrate that macroecological factors underpin the spatial patterns of humans at large scales. Macroecological constraints and their relative importance are found to be similar for humans and other species, suggesting that similar mechanisms are likely to underlie these macroecological patterns. Our findings have potential implications for the assessment of future responses of humans to global environmental changes.

The effect of ecological niche and spatial pattern on the diversity of oak forest vegetation

Background: Ecological niche and spatial processes are known to shape the species composition of plant communities. However, the relative importance of these factors can vary considerably from one habitat to another.Aims: To determine the effect of environmental conditions and spatial processes on multiple scales on the species composition of forest vegetation, we studied a patchy system consisting of overgrown oak stands of coppice origin on slopes with a southern exposure in a diverse, submontane landscape.Methods: Spatial patterns were surveyed with the principal coordinate analysis of neighbour matrices method, using a ‘staggered’ matrix to examine the effect of nested spatial scales. The variation partitioning procedure was applied to assess the relative influence of spatial and environmental components. Redundancy analysis was carried out to detect the effect of particular environmental variables.Results: Vegetation composition was related to environmental variables (mostly water-holding capacity and Ca content), as well as spatial processes, such as dispersal limitation, at the large (ca. 15 km) and medium (ca. 3.5 km–1.0 km) scales, whereas at small scales (<1 km), these factors were not related to species composition.Conclusions: The vegetation of the studied forests should be considered as a metacommunity, and the main drivers of species composition are species sorting and dispersal limitation.

Winter habitat selection and partitioning in two sympatric farmland small mammals: Apodemus sylvaticus and Mus spretus

Patterns of small mammal habitat selection vary according to scale, although there are discrepancies about the importance of macro and micro-scale factors in rodent community assembly. We assess whether differences in their micro and macrohabitat selection patterns explain the coexistence of two sympatric rodents, Mus spretus and Apodemus sylvaticus, in an agricultural area of central Spain. We trapped mice in uncultivated and crop fields using a grid of Sherman traps. Food availability and vegetation structure (microhabitat) and landscape composition variables (macrohabitat) were measured in each plot. We used GLMs to determine the scale predictors related to specific abundance. The importance of each scale in the assemblage was assessed by a variance partitioning procedure. At microhabitat scale, A. sylvaticus was positively related to shrub cover and M. spretus to seed availability. At macrohabitat scale, A. sylvaticus was negatively associated with distance to the nearest tree, whereas M. spretus was positively associated with this variable. Macrohabitat explained 39 % and microhabitat 8 % of the variance in the assemblage. Results suggest a relative segregation of food preferences at microhabitat scale, and a habitat partitioning at macrohabitat scale, which may allow spatial coexistence of both species, according to community assembly theory. This study shows the importance of both micro and macrohabitat in the configuration of rodent assemblages.

Influences of dispersal and local environmental factors on stream macroinvertebrate communities in Qinjiang River, Guangxi, China

ABSTRACT: Identifying the underlying mechanismsthat explain the spatial variation of stream macroin-vertebrate assemblages is crucial for the protectionof species diversity. Consequently, questionsregarding how much variance in macroinvertebratecommunity structure is related to spatial dispersaland local environmental factors, and which envi-ronmental vari ables are the key drivers havebroad research and management implications.Based on data from 22 stream sites within the Qin-jiang River watershed, Guangxi, China, we exam-ined the variation in macro invertebrate communitystructure attributable to local environmental factors(i.e. stream physical habitat and water chemistry)vs. spatial dispersal factors (i.e. overland andwatercourse spatial eigenvectors among samplingsites) using variation partitioning procedures. Over-all, we found that stream macro invertebrates areinfluenced both by local environmental factors andspatial dispersal factors. The most important envi-ronmental factors structuring macro invertebrateassemblages were current velocity, dissolved oxy-gen, conductivity, total phosphorus, and physicalhabitat quality. Both overland and watercourse dis-persal pathways had a similar influence onmacroinvertebrate assemblages. These results dem -onstrate that stream macroinvertebrates within thestudied landscape are constrained by local envi-ronmental conditions and dispersal factors, andhence comply with the niche-based species sortinghypo thesis in the context of metacommunity ecol-ogy.KEY WORDS: Macroinvertebrate · Spatial factors ·Local environment · Stream · China

Biotic and abiotic factors modulating wild boar relative abundance in Atlantic Spain

The population dynamics of wild ungulates, particularly wild boar (Sus scrofa), are modulated by biotic (e.g. predation) and abiotic (environmental) determinants. Despite the evident potential interference of predation in the environmental patterns of wild boar population abundance, studies including both predation and abiotic factors are scarce. Here, using spatially explicit predictive models, we investigated the effects of habitat features on the relative abundance of wild boar populations and how the abundance of boars is related to frequency of Iberian wolf (Canis lupus signatus; hereafter, wolf) in the area. Wild boar relative abundance was determined by hunting bag statistics, including hunting effort-related variables (in order to avoid problems derived from modeling rates) as covariates, while wolf attacks to livestock were considered as a proxy of wolf frequency in the drive. After modeling, variation partitioning procedures were used to determine the relative importance of each factor and their overlaid effects. Our results showed that wild boar and wolf relative abundances are associated. According to previous knowledge on the wild boar ecology, we found that the species abundance is positively related to the percentage of surface occupied by mature forest and heather providing high food diversity and refuge, but these environmental variables achieved a low explanatory capacity in the models in relation to wolf frequency. The holistic approach followed in this study was attended to open new perspectives for thinking on the wolf-livestock conflict and to adequate wild boar management strategies taking into account hunting interests and natural processes.

Disentangling the Spatio-Environmental Drivers of Human Settlement: An Eigenvector Based Variation Decomposition

The relative importance of deterministic and stochastic processes driving patterns of human settlement remains controversial. A main reason for this is that disentangling the drivers of distributions and geographic clustering at different spatial scales is not straightforward and powerful analytical toolboxes able to deal with this type of data are largely deficient. Here we use a multivariate statistical framework originally developed in community ecology, to infer the relative importance of spatial and environmental drivers of human settlement. Using Moran’s eigenvector maps and a dataset of spatial variation in a set of relevant environmental variables we applied a variation partitioning procedure based on redundancy analysis models to assess the relative importance of spatial and environmental processes explaining settlement patterns. We applied this method on an archaeological dataset covering a 15 km2 area in SW Turkey spanning a time period of 8000 years from the Late Neolithic/Early Chalcolithic up to the Byzantine period. Variation partitioning revealed both significant unique and commonly explained effects of environmental and spatial variables. Land cover and water availability were the dominant environmental determinants of human settlement throughout the study period, supporting the theory of the presence of farming communities. Spatial clustering was mainly restricted to small spatial scales. Significant spatial clustering independent of environmental gradients was also detected which can be indicative of expansion into unsuitable areas or an unexpected absence in suitable areas which could be caused by dispersal limitation. Integrating historic settlement patterns as additional predictor variables resulted in more explained variation reflecting temporal autocorrelation in settlement locations.