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• We assessed interspecific and intraspecific variation in litter consumption rate of aquatic and terrestrial macro-detritivores. • We observed a substantial amount of intraspecific variation (34%) relative to the interspecific variation (53%). • Intraspecific variation was repeatable among individuals, reflecting phenotypic features of individuals rather than inconsistent variation (13%). • Our study highlights the importance of the intraspecific level in trait-based ecological studies on macro-detritivores. Traits of organisms vary both at inter- and intraspecific levels. For macro-detritivores inhabiting lands and waters, there is only scattered information on the relative contribution of the intraspecific level for traits like litter consumption rates. This basic knowledge is nevertheless required to know how much the intraspecific level could matter to the study of macro-detritivore communities and ecosystem processes like leaf litter decomposition. We performed a laboratory experiment, where thirty individuals each of five abundant macro-detritivore species from a stream and a meadow ecosystem fed ash (Fraxinus excelsior) leaf litter in microcosms, twice at a 1-week interval. This nested and repeated design (individuals nested within species, species within ecosystems) was setup in controlled conditions and then analysed following a variance partitioning approach with linear mixed-effect models, to assess the variance attributable to different levels of biological organisation (i.e., inter- and intraspecific level). Then, we performed the same analysis, but separately on aquatic and terrestrial datasets. From the whole dataset, we demonstrated that half of the trait variation occurred at the interspecific level and a third at the intraspecific level. The variance found at the residual level, accounting for both measurement errors and for the variation of the same individuals between the two times (i.e., intra-individual variation), was significantly lower than what was observed at the other levels of biological organisation. Variance partitioning on separate aquatic and terrestrial datasets were consistent altogether, confirming the global pattern. With this study, we stress the relevance of the intraspecific level for future trait-based approaches applied to macro-detritivores. [ABSTRACT FROM AUTHOR]

Abstract Research on factors determining soil metacommunity patterns across multiple spatial scales is quite rare. In this study, we aimed to compare the mechanisms that drive species co-occurrence and consequently form the ground-dwelling macro-arthropod metacommunity structure at local (104 m) and regional (106 m) scales. For the comparison, we used three distant (approximately 200 km from each other) locations within the northeast black soil region of China. At each location, we had five sampling plots (at a distance of 500 m from each other), and at each plot, we had five sampling sites within agrolandscapes (10 m away from each other). At each site, we set three pitfall traps. Animals were collected three times: in May, July and September 2015. The analysis of the elements of metacommunity structure showed that the regional level of the metacommunity always demonstrated a Clementsian structure (a grouped distribution of species along environmental gradients), while the local scale metacommunity structure was dependent on sampling month and varied between Clementsian, random and nested distributions. Based on the results of a variance partitioning analysis, including pure environmental (environmental filtering) and pure spatial predictors (dispersal), as well as the interaction of environmental and spatial factors (shared fraction), we observed that the shared fraction at the regional scale was 30% larger than at the local scale. A species co-occurrence analysis further demonstrated that the observed C-scores were not significantly higher than simulated indices for each guild separately at the local scale. Our results suggest that biotic interactions are not the key drivers of metacommunity structure at the local scale in agriculture, while environmental filtering and dispersal appear to be key drivers of metacommunity structure at the regional scale. Highlights • Research on soil metacommunity patterns across multiple spatial scales is quite rare. • We aim to explore the drivers of metacommunity at local and regional scales. • Biotic interactions are not the key drivers of metacommunity structure at local scale. • Abiotic factors and dispersal to be the key drivers of structure at regional scale. [ABSTRACT FROM AUTHOR]

Abstract More often than not, rivers are impacted by multiple stressors simultaneously affecting water quality, ecological flow, habitat diversity and ultimately lotic biodiversity. Identifying individual stressors as specific causes of deterioration can help inform water managers about stressor hierarchy and appropriate management options. Here, we investigate whether biological metrics from bioassessment schemes hold diagnostic capabilities to distinguish between the impact of individual stressors. We hypothesise that stressor-specific responses occur, when individual stressors show independent 'modes of action' (i.e. the specific stress-induced changes of environmental factors that modify the ecological niches of the species constituting the biological community). The stress receptors comprised three aquatic organism groups (macrophytes, benthic invertebrates, fish) represented by 437 biological metrics relevant in aquatic bioassessment. The stressor groups under investigation were physico-chemical, hydromorphological and hydrological stress. The data originated from official monitoring programmes with 769 sampling sites located at three broad river types in Western and Central Germany. Linear and non-linear variance partitioning was performed separately for each river type, with the non-linear analysis using a combination of boosted regression tree modeling and variance partitioning. We considered metrics to be potentially stressor-specific, if the corresponding models were explained predominantly by one stressor group. The linear analyses revealed 16 metrics that met our criteria. Subsequent non-linear modeling resulted in two genuinely stressor-specific metrics, both based on invertebrate data: The Index of Biocoenotic Region (specifically indicating hydromorphological stress) and the Relative abundance of alien invertebrate species (specifically indicating physico-chemical stress). We conclude that stressor-specific metrics can be empirically derived based on available monitoring data, and thus help support decision making in environmental management. However, their applicability is restricted to specific regions (e.g. river basin districts) reflecting the case-specific circumstance to which these metrics are conditioned. Graphical abstract Unlabelled Image Highlights • We tested 437 biological metrics with respect to their stressor-specific indication. • Our data covers three different groups of stress and three broad river types. • Stressor-specific indication depends on data-specific features attributable to the biogeographical context. • Stressor-specific metrics provide evidence to guide appropriate mitigation measures by environmental managers. [ABSTRACT FROM AUTHOR]

Highlights • Understory richness and α-diversity increase with area sampled. • β-diversity and sampling efficacy maximized at smaller spatial scales. • Monitoring efficiency increased by identification of suitable sampling effort. Abstract Monitoring understory plant diversity is important, allowing managers to track current diversity status and trends both spatially and temporally at a landscape-scale. Improving precision in quantifying patterns in understory plant diversity improves efficiency in monitoring design and more accurate measures of success of management intervention over time. Patterns of species diversity are dependent upon the scale in which they are examined – an increase in small-scale diversity across a gradient can convert to a decrease in large-scale diversity across that same gradient. Using two extensive datasets including both mined historical data and supplemental experimental data, we performed an additive partitioning of plant diversity to elucidate the hierarchical spatial patterns of understory plant species richness, and independent measures of alpha and beta diversity in the species-rich longleaf pine ecosystem at Eglin Air Force Base in northwestern FL, USA. This analysis allowed us to identify the spatial scale that most effectively captures plant diversity to inform monitoring efforts by using measures of species turnover, specifically beta diversity. We found that while species richness and alpha diversity increased with spatial scale, beta diversity began to reach an asymptote at smaller (1 m2) scales. Furthermore, we found the sampling effort at this 1 m2 scale required as few as 60 plots to effectively estimate plant diversity within management blocks. While our results are attributable to Eglin AFB specifically, these scaling analyses can help to streamline monitoring efforts in other ecosystems that seek to elucidate the individual contributions of diversity components. [ABSTRACT FROM AUTHOR]

• Investigated key drivers of soil carbon pools and their interactions related to soil carbon cycling. • Identified unique and combined effects of macro, micro drivers and spatial dependence on soil carbon. • Micro-environmental drivers had a larger unique fraction compared to macro-environmental drivers. • The soil carbon variation patterns are highly spatial-dependent. • The study will be a successful initiative to improve the reliability of future soil carbon predictions. The current study examined macro-environmental (climate and topography), micro-environmental (soil chemical properties) drivers, and spatially derived parameters that are significantly associated with soil carbon pools (0–15 cm) across tropical paddy-growing areas in Sri Lanka using the data from 987 sampling sites across the country. Redundancy analysis was performed to identify the relationships between the explanatory variables and the variation in different soil carbon pools i.e., total carbon (TC), Microbial Biomass Carbon (MBC), Permanganate Oxidizable Carbon (POXC), and Dissolved Organic Carbon (DOC). The spatial patterns in soil carbon pools were evaluated using Moran's eigenvector maps. Results indicated that macro, micro-environmental drivers and spatial variables explained 47% of the inherent variation of the TC, MBC, POXC and DOC. Micro-environmental drivers had a larger unique fraction relative to macro-environmental drivers (4% and 1% of the total variation, respectively). Most of the variation explained by macro-environmental drivers was shared by micro-environmental drivers (11% out of 15%). Among macro-environmental drivers, rainfall and enhanced vegetation index were more strongly related to the soil carbon pools compared to the topography-related factors. In terms of micro-environmental drivers, total N, available K, Ca, and soil pH (H 2 O) were the best explanatory variables of soil carbon pools. Spatial patterns in soil carbon pools were largely induced by the environmental predictors that are spatially structured. Our findings provide insights into improving the reliability of spatial estimation of the soil carbon by incorporating important soil carbon preditors and quantifying the impacts of environmental changes on soil carbon pools. [ABSTRACT FROM AUTHOR]

• Increased trait divergence with spatial and temporal variation. • Trait variances are maximally distributed at the species level (∼48%). • Broadleaved showed increased trait coordination with varying environments. • Coniferous species showed increased trait adaptability to changing environments. • Soil nutrients showed maximum variance with root > stem > leaf traits. Trait variation across spatial and temporal scales allows plants to adapt to changing environments. Understanding the mechanisms driving trait variability, it is important to unravel how plant functional traits adapt to changing climates. Plant chemical traits (C, N, P, K, S, Ca, Mg, Mn, Zn, Fe, Cu, and Na) for leaf, stem, and root were studied for ten dominant evergreen tree species along increasing elevation (1500–3000 m asl) for three seasons (summer, monsoon, and winter) in temperate forests of western Himalaya, India. We also collected five soil samples from each plot to analyze chemical trait variation with respective soil nutrient concentrations. Our results suggested that temperature significantly (P < 0.05) affected leaf traits, whereas stem and root traits were maximally driven by light and water availability (P < 0.05). Maximum trait variance was observed at species level (∼48%) followed by individual level (∼45%). Coniferous species displayed strong trait coordination among organs, whereas broad-leaved species showed strong correlation with environmental resources. Trait correlation with respective soil nutrient concentration was found strongest for the root, followed by stem, and ultimately got lost for leaf traits (except Ca, Mg, and Mn). Weaker plant–soil interaction for leaf traits showed external factors such as lopping alter plant-soil relationship. We provide evidence of varying degrees of trait conservatism within broad-leaved and coniferous trees that leads to increased trait variability. We also emphasize the importance of considering major abiotic and biotic stresses exerted on different plant organs when investigating trait variation along environmental gradients. [ABSTRACT FROM AUTHOR]

Abstract Higher elevations and, early as well as late phase of growing season are expected to be more stressful for plants in high altitudes. The present study was carried out on Rhododendron anthopogon D. Don, an evergreen shrub of Himalaya to understand variation in eco-physiological and biogeochemical traits due to combined effect of elevation gradient and growing season. We conducted our study at Rohtang, India (32°22′04″ N 77°15′17″ E) and undertook random sampling of leaves at four elevations (3200 m, 3600 m, 4000 m and 4250 m), and three time periods (late June, early August and late September) during growing season. We assessed 12 eco-physiological and biogeochemical variables and analysed results through ANOVA and multivariate analysis. It was found that leaf relative water content, nitrogen percentage (N%), carbon/nitrogen ratio (C/N ratio), total chlorophyll, malondialdehyde equivalents and proline content varied along two gradients (factors) with their interaction being statistically significant. Variance partitioning analysis of studied traits revealed that both factors contribute significantly, with 'season' component ranging between 55.75 % and 94.03 % for most of the parameters, whereas, 'elevation' component contributed more for leaf area, N% and C/N ratio (48.08 %–75.03 %). Our results suggest that eco-physiology of R. anthopogon is significantly influenced by interaction of seasonal variations coupled with elevation gradient. The study highlights the importance of examining both seasonal and elevational gradients in understanding plant adaptation strategies. Overall, our findings revealed that plasticity in eco-physiological and biogeochemical traits underline the wide distribution of R. anthopogon in the high altitudes. Highlights • Interaction of seasonal and elevation gradient affects eco-physiology of R. anthopogon. • Seasonal variation contributes more than elevation to overall trait variability. • Physiological trait plasticity may influence its expansion under climate change. [ABSTRACT FROM AUTHOR]

Leaf area index (LAI) controls many eco-physiological processes and can be widely used to scale-up leaf processes to ecosystem, landscape and regional levels. However, the macro-scale spatial heterogeneity of LAI and its controlling factors are not fully understood. We estimated annual maximum LAI using an LAI-2200 plant canopy analyzer in a 9-ha, old-growth, mixed broadleaved-Korean pine ( Pinus koraiensis ) forest in China. We analyzed the spatial heterogeneity of LAI and mapped its distribution using geostatistical methods; then, through variance partitioning, we examined the influences of several biotic factors, abiotic factors and spatial autocorrelation on the LAI distribution. Variance partitioning showed that these factors altogether explained 59% of the variation in the distribution of LAI. Compared to biotic and abiotic factors, spatial autocorrelation controlled more spatial heterogeneity of LAI by explaining 51.4% of the total variation in LAI. For biotic and abiotic factors, the mean diameter at breast height (DBH) of large trees (DBH > 10 cm), elevation, soil temperature and soil mass moisture content significantly affected the LAI distribution ( P  < 0.01). Notably, spatial autocorrelation unexpectedly explained the most variation in the LAI values, and it also varies with cardinal direction and is a key descriptor of LAI spatial variability. These results suggest that the influence of spatial autocorrelation on LAI distribution should attract more attention and that both the relative importance of and interactions among different determining factors is helpful for better understanding the mechanistic determinants of LAI distributions in temperate mixed forests. [ABSTRACT FROM AUTHOR]

River systems and their communities are exposed to diverse and multiple threats. Understanding how these threats affect the behaviour of biomonitoring indices is essential in order to provide reliable tools for the management and conservation of watercourses. To this purpose we tested the relationship of the STAR_ICMi index and its metrics, LIFE index and macroinvertebrate community with hydrology, water chemistry and land use in 8 sites located along the Oglio River course (Northern Italy), a watercourse originating from a large and deep lake. Macroinvertebrates and water samples were collected seasonally from summer 2013 to summer 2015 and daily discharge data were used to calculate several indices of hydrological alteration. A subset of these variables was selected by principal component analysis for using in the data analysis. The influence of hydrology, water chemistry and land use on macroinvertebrate community structure was explored with the variance partitioning method, while their influence on biomonitoring indices was analysed in a linear mixed effect model framework. Temporal and spatial constraints were explicitly considered in both analyses. Macroinvertebrate community structure was mainly related to these last two factors and to their joint effects with water chemistry and hydrology. STAR_ICMi, its metrics (with the exception of the Shannon index) and LIFE were related to the distance from the lake outlet, a proxy of mean annual discharge, groundwater input and artificial land use. STAR_ICMi, ASPT and EPT richness were also inversely related to the flow variability in the 3 months preceding sample collection. Surprisingly LIFE index was not related to any of the hydrological variables. The results of this study highlight weakness in the current biomonitoring tools and support the need for further investigations on macroinvertebrate interrelations with environmental drivers and their spatial and temporal structure. This is essential to overcome the limitations that may affect the reliability of macroinvertebrate-based indices in aquatic biomonitoring. [ABSTRACT FROM AUTHOR]

Species Distribution Models (SDMs) constitute an important tool to assist decision-making in environmental conservation and planning. A popular application of these models is the projection of species distributions under climate change conditions. Yet there are still a range of methodological SDM factors which limit the transferability of these models, contributing significantly to the overall uncertainty of the resulting projections. An important source of uncertainty often neglected in climate change studies comes from the use of background data (a.k.a. pseudo-absences) for model calibration. Here, we study the sensitivity to pseudo-absence sampling as a determinant factor for SDM stability and transferability under climate change conditions, focusing on European wide projections of Quercus robur as an illustrative case study. We explore the uncertainty in future projections derived from ten pseudo-absence realizations and three popular SDMs (GLM, Random Forest and MARS). The contribution of the pseudo-absence realization to the uncertainty was higher in peripheral regions and clearly differed among the tested SDMs in the whole study domain, being MARS the most sensitive — with projections differing up to a 40% for different realizations — and GLM the most stable. As a result we conclude that parsimonious SDMs are preferable in this context, avoiding complex methods (such as MARS) which may exhibit poor model transferability. Accounting for this new source of SDM-dependent uncertainty is crucial when forming multi-model ensembles to undertake climate change projections. [ABSTRACT FROM AUTHOR]

Organic farming may be more beneficial to biodiversity than nonorganic farming but the comparison is often confounded by regional within-farm and landscape differences. We compared breeding bird species composition and abundance on 10 farm pairs of each type matched at the site level for land cover in the prairie parklands of Saskatchewan, Canada in 1990. Land cover was measured around bird point counts at two extents; ‘site’ (6.3 ha area) and ‘field’ (16.3 ha area). We pooled species into functional groups; linear mixed models showed no significant differences between farm types for species richness but that all birds, migratory birds using crops and aerial insectivores were more abundant on organic farms. A permutational multivariate analysis of variance demonstrated that farm type did not have a significant overall effect on compositional similarity but that pairwise differences existed between about half of the farm pairs (the direction of differences in beta diversity was not consistent between organic and nonorganic farms according to tests for the homogeneity of multivariate dispersions). Farm-pair differences were more pronounced for all birds and for migratory bird species using crops, migratory birds consuming grains and ground feeders, but not grassland birds. n MDS ordinations suggested that there was more variation in species composition and abundance on organic farms than nonorganic ones but the difference was not significant. Distance-based redundancy analysis ( db RDA) was used to examine the main drivers of bird species composition and abundance and to see which extent was most important; land cover at the field extent was more important than land cover at the site extent or the farming practices measured. The most important field-extent land cover was t h e amount of native grassland, woodland (including shelterbelts) and wetlands. After controlling for significant field-extent land cover, seed treatment, herbicide use, and number of passes were significant. At the site extent, greater non-crop heterogeneity had a significantly positive effect on abundance and species richness of several groups (e.g., grassland birds, migratory granivores, ground feeders, ground nesters) but a negative effect on richness of woodland birds and abundance of aerial insectivores. Relationships with crop heterogeneity were mostly negative and non-significant. Overall land cover heterogeneity at the site level was positively related to the richness of grassland birds. In contrast at the field extent, non-crop heterogeneity did not have any significant effects on the richness and abundance of any functional group. Crop heterogeneity had a significantly negative effect on aerial insectivore richness and abundance. In the early 1990s, differences in birds between organic and nonorganic farms in Saskatchewan were evident but subtle and variable among farms, and apparently most related to land cover-bird assemblage interactions/relationships. [ABSTRACT FROM AUTHOR]

Alpine meadows have been exposed to relevant management shifts in the last decades, with changes in plant species composition and biodiversity losses often occurring in favor of augmented foraging capabilities, especially in marginal rural contexts. In this study, we analyzed the relationships among the plant species composition, biodiversity and forage value of meadows and two sets of variables, environmental and management ones, in a dairy district of the Central Italian Alps. Results indicate that management variables could only explain limited variability of the meadows under study: for instance, the number of cuts per year is available to justify the plant species composition and biodiversity of such coenoses. Moreover, the environmental variables better described the variability of responses, due to the harsh environmental constraints of the area under examination, located at high altitudes. The shared effects of the two sets explained larger variance than the management set alone, due to the complex relationships of environmental and management factors in the context. The forage value of meadows, an indicator of hay quality, was found negatively associated with the Shannon Index. This behavior highlights a known dilemma which especially refers to high altitude communities as the ones under study, clearly highlighting trade-offs between their production and biodiversity. Some taxa as Anthriscus sylvestris , Heracleum sphondylium and others critically unbalance the species composition of meadows, thus their overall biodiversity, at low altitudes. This finding, explainable by the late first cuttings commonly adopted by all farmers, suggests the eutrophication of coenoses. The management choices inspected did not reflect on the wide variability of meadows, but indeed they made possible to understand how this farming system should be deeply revised, with respect to environmental constraints and meadows’ fodder capabilities. [ABSTRACT FROM AUTHOR]

Despite the introduction of agri-environmental schemes, no general increase of farmland biodiversity in Europe has been observed. Farmers take decisions about the implementation of agri-environmental schemes at the farm scale, and it is thus highly relevant to assess the relationship between farm management and biodiversity at this scale to increase the effectiveness of agri-environmental schemes. The present study quantifies to what extent and with which practices farmers can influence biodiversity on their farm and to what extent conditions outside farmers’ control may mediate biodiversity. We grouped 27 variables into four variable sets: (1) ecological compensation (mainly semi-natural habitats), (2) in-field options (e.g. no growth regulator, insecticide and herbicide treatment), and (3) farm characteristics, which can be influenced by farmers (e.g. land-use types) as well as (4) farm settings, which cannot be influenced by farmers (e.g. altitude). As biodiversity metrics, plant, grasshopper, butterfly and bird richness and abundance of farmland target species were assessed on 133 farms of the Swiss Central Plateau from 2009 to 2011. Variance partitioning and generalised linear mixed models were used to analyse the impact of each variable set on farmland species diversity. Our results provide evidence that farmers can indeed positively influence biodiversity by ecological compensation and in-field options. The variables of the ecological compensation set explained the highest proportion in the variation of plant richness and butterfly abundance. We found a significant positive relationship between in-field options and plant abundance. Our study illustrated that the effects of biodiversity-related farming practices differ between species and biodiversity metrics. Conditions outside farmers’ control explained a high variation in grasshopper and bird diversity. One variable within the set of farm settings, the degree of consolidation, had a significant negative impact on five out of eight biodiversity metrics (plant, butterfly and bird richness; plant and bird abundance). We demonstrate that farmers can substantially enhance biodiversity on their farms and provide knowledge on how such biodiversity improvements can be achieved by farmers. Further, we highlight the value of new biodiversity-related management practices such as in-field options. [ABSTRACT FROM AUTHOR]

Several biogeographical hypotheses have been proposed to explain microbial distribution, but there is ongoing debate about the magnitude of the contribution of niche–based processes and historical contingencies in determining patterns of microbial structure. In this context, currently fragmented relict forests of olivillo ( Aextoxicon punctatum Ruiz et. Pav.), which belonged to a continuous community along the coast of Chile during the Pleistocene, and their surrounding scrublands are ideally–suited for testing these hypotheses, since they remain as patches located at the northern tip of the distribution of the relicts. In each study site, edaphic and geographic variables were determined, and the bacterial structures were evaluated at the genetic and metabolic levels through fingerprint approaches along with multivariate analytical methods including redundancy (RDA) and variance partitioning (VPA) analyses. Forests possessed lower pH, and higher contents of moisture and organic matter. In addition, bacterial communities from both habitats differed, whereas the bacterial communities of the forests in different regions were very similar to each other. Our conclusion is that current abiotic soil factors, but not past events due to the historical connection of the forests, account for the variance in the structure of these soil bacterial communities. [ABSTRACT FROM AUTHOR]

It is increasingly acknowledged that creative potential involves partly a generalized ability, partly a set of domain-specific abilities, and partly a set of task-specific abilities. We extend and illustrate this view in a study of 482 children and adolescents, exploring the extent to which the scores variance of the Evaluation of Potential Creativity (EPoC)'s eight subtests can be decomposed by five variance components: thinking-process general, thinking-process specific, domain-specific, task-specific, and measurement error. A structural equation model derived from an extension of the multi-trait multi-method matrix analysis revealed that (1) the contribution of each variance component depends greatly on the task under consideration, and that (2) the contribution of a general creative thinking-process factor is overall limited. This study outlines the multidimensional and hierarchical structure of creative potential and the need to measure it with comprehensive test batteries sampling a range of creative tasks, domains and creative thinking-modes. [ABSTRACT FROM AUTHOR]

[Display omitted] • Pedogenon classes are created by K means clustering on soil forming factors. • Pedogenons define unique soils and characterise the pedodiversity of the study area. • Soil properties of genosoil and phenosoil are predicted using VisNIR spectra. • The result shows that genosoils had twice the variation of phenosoils. Mapping soil classes can support the understanding of soil origin and development, subsequently the soil classes can be used to support monitoring and assessing soil change due to human influence. Pedogenon was proposed as a conceptual soil taxon derived from a set of quantitative state variables representing the soil-forming factors for a given reference time. This study aims to test the pedogenon concept in the Edgeroi region in New South Wales. This paper developed local pedogenons, designed a sampling scheme to capture soil variation under natural conditions and under intensive human activities, and tested the hypothesis that pedogenon is an efficient method of stratifying the landscape to capture soil variation. This study derived the 14 pedogenons by employing layers of soil-forming factors (soil, climate, organism, topography, and parent material and age) using an unsupervised classification technique (k-means clustering). Within each pedogenon, genosoils were identified based on areas with native vegetation, while phenosoils were identified as areas with cropping practises. One meter soil cores were collected for each genosoil and phenosoil, and scanned using Vis-NIR spectrometer for predicting soil properties (clay, sand, cation exchange capacity, pH, and organic carbon). Results show that each pedogenon was characterised by a soil type formed under a dominant parent material occupying a unique position in the landscape. Redundancy discriminant analysis of the soil properties as a function of pedogenon and depth of observations show that pedogenon significantly explained the variation in soil properties. Variance partitioning analysis confirmed that pedogenon explained a large proportion of the variation (49 %) as opposed to landuse (5 %). Principal component analysis of the soil properties shows that genosoils had twice the variation of phenosoils. The results indicate that agricultural activities homogenised the variation of soil profiles. This study demonstrated that pedogenon clasess can effectively characterise soil variation and be used as a benchmark to compare how human activities have altered soil conditions. [ABSTRACT FROM AUTHOR]

Arbuscular mycorrhizal (AM) fungi are present in all soils and comprise an important component of soil biota with respect to plant nutrition and growth as well as soil quality. Previous research in a number of agroecosystems had documented large impacts from various management practices (e.g., tillage, fertilization, crop rotation) on the levels of host root colonization and/or composition of the AM fungal communities in the roots and soil. Here, we tested whether a standardized mycorrhizal bioassay could contribute to deciphering soil-use legacy through detection of consistent changes in the colonization pattern of a mycorrhizal bait plant (leek). To this end, we grew the leek in a large number (154) of soils under uniform environmental conditions. Most of the variation in the mycorrhizal colonization of bait plants grown in the different soils could be attributed to soil properties and sampling site altitude, whereas the occurrence of specific structures (vesicles) was particularly correlated with abundance of certain AM fungal taxa such as Rhizophagus sp. Contributions of the root colonization of bait plants to explaining agricultural management practices and soil heavy metal concentrations (frequently used as indicators of soil quality) were comparatively small and partly counterintuitive. For example, higher incidence of arbuscules was detected in soils to which mineral fertilizers were applied as compared to organically farmed soils. Moreover, the explanatory power of the bioassay was much less than was that for soil respiration, a well established bioindicator of soil quality. Therefore, the mycorrhizal bioassay tested here appears not to be suitable as an interpreter of soil-use legacy, even though it does uncover very clear trends in colonization patterns of the bait plants by indigenous AM communities across large environmental gradients. [ABSTRACT FROM AUTHOR]

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The attributes of yield and yield stability of two coexisting lines within the old landrace of small-sized tomatoes ‘Tomataki Santorinis’, i.e., ‘Genuine Santorinis’ (‘G’-line) and ‘Traditional Santorinis’ (‘T’-line) were defined, quantifying the interaction of the lines with the environment. The experiments were conducted in parallel at two environments: (a) two-year intra-selection experiments in situ (island of Santorini) under traditional agronomic management, (b) two-year evaluation experiments ex situ (Agricultural Research Center of Northern Greece) under the usual ‘farmer’s technique’, and (c) final comparative trials of selected entries of each line with the source material in situ and ex situ . Especially, for the attributes of yield, the number and the weight of early and total fruits were measured. Additionally, descriptive (fruit ribbing and shape) and qualitative (total soluble solids, total solids and pH) characteristics were recorded. In the in situ environment, genetic variance for yield components was medium to high for ‘G’-line and zero to low for ‘T’-line. In the ex situ environment , the genetic variance was high for ‘G’-line and low for ‘T’-line. Ranking of yield components, between the two environments, showed significant correlations of ‘G’-line and ‘T’-line in situ . Ex situ, the ‘T’-line performed similarly, while the ‘G’-line showed reduced association between phenotypic and genotypic performance. The comparative trials showed significant difference between selected entries and source material solely for the ‘G’-line, revealing different compensation profiles of the lines’ adaptive ability. The ‘G’-line profile revealed productivity, efficiency to direct selection and specific adaptability. The ‘T’-line profile revealed lower productivity, high homogeneity and broad adaptation. These profiles permit breeders to develop two distinctive types of the landrace, either as a Protected Designation of Origin (PDO) cultivar or as a line. [ABSTRACT FROM AUTHOR]

Land use effects are considered among the main stressors on freshwater biodiversity, with up to 80% of land in Europe under intensive use. Here, we address the impact of arable and urban landscapes on taxon richness, Shannon–Wiener diversity, taxon rareness and taxonomic distinctness of eleven organism groups encompassing vertebrates, invertebrates and plants, occurring in five freshwater ecosystem types across Europe: rivers, floodplains, lakes, ponds and groundwater. In addition, nine geo-climatic descriptors (e.g. latitude, longitude, precipitation) were used to disentangle land use effects from those of natural drivers of biodiversity. Using a variance partitioning scheme based on boosted regression trees and generalised linear regression modelling, we sought: (i) to partition the unique, shared and unexplained variation in the metrics explained by both groups of descriptor variables, (ii) to quantify the contribution of each descriptor variable to biodiversity variation in the most parsimonious regression model and (iii) to identify interactions of land use and natural descriptors. The variation in biodiversity uniquely described by land use was consistently low across both ecosystem types and organism groups. In contrast, geo-climatic descriptors uniquely, and jointly with land use, explained significantly more variance in all 39 biodiversity metrics tested. Regression models revealed significant interactions between geo-climatic descriptors and land use for a third of the models, with interactions accounting for up to 17% of the model's deviance. However, no consistent patterns were observed related to the type of biodiversity metric and organism group considered. Subdividing data according to the strongest geo-climatic gradient in each dataset aimed to reduce the strength of natural descriptors relative to land use. Although data sub-setting can highlight land use effects on freshwater biodiversity, sub-setting our data often failed to produce stronger land use effects. There was no increase in spatial congruence in the subsets, suggesting that the observed land use effects were not dependent on the spatial extent of the subsets. Our results confirm significant joint effects of, and interactions between, land use and natural environmental descriptors on freshwater biodiversity, across ecosystem types and organism groups. This has implications for biodiversity monitoring. First, the combined analysis of anthropogenic and natural descriptors is a prerequisite for the analysis of human threats to biodiversity. Second, geo-climatically, but not necessarily geographically more homogeneous datasets can help unmask the role of anthropogenic descriptors. And third, whole community-based biodiversity metrics (including taxon richness) are not ideal indicators of anthropogenic effects on biodiversity at broad scales. [ABSTRACT FROM AUTHOR]

Most studies of landscape effects on plants in forests have explored only relatively small landscape scales (size of spatial extent) considering the poor-dispersal ability generally reported for forest plants, or failed to verify confidently that the scales at which landscape is considered best predicts plant patterns. We investigated the effect of landscape composition on response of plant communities according to three scales - 400 ha, 100 ha and 25 ha - in 263 forests in the northern half of France. We hypothesized that landscape composition at the 400-ha scale better predicted plant responses than smaller scales. We built models to compare the effects of each scale on individual species response and plant composition of 1902 700-m 2 vegetation plots, considering the shared and pure effects of scales. Only landscape composition at the 400-ha scale showed a critical pure effect on plant composition. Similarly, the 400-ha scale better predicted individual species response. Using a large dataset, we brought evidence that landscape composition further than 100 ha and at least up to 400 ha had more effects on local plant diversity in forests, which means that smaller-scale investigations may miss the influence of landscape on plant patterns. The effects of large spatial scale may reflect the legacies of past landscape or the long-distance dispersal capacity of plants. Our findings call for better consideration of the large-scale effects of landscape on plants both in scientific studies and management plans. [ABSTRACT FROM AUTHOR]

Based on multiple geo-accumulation indices and correlation and partial redundancy analyses, we examined the spatial patterns of agricultural soil contaminations for As, Pb, Cd, Cr, and Ni in the Pearl River Delta, South China and their relations with landscape heterogeneity at small, medium and large spatial scales. We found that the concentrations of trace elements were slightly elevated, and most trace metals had a geogenic origin. Landscape variables explained 21–53% of the variation of elevated trace metal concentrations with an increasing explanatory power from the small to the large scale. The three variable groups representing parent materials, distance density characteristics and land use had different contributions to the elevated trace metals among scales. Both the distance density variables and land use pattern had a stronger influences on trace metal concentrations at a small scale than at a larger scale, while the parent materials was important at all the scales. [ABSTRACT FROM AUTHOR]

Since landscape attributes show different patterns at different spatial extents, it is fundamental to identify how the relation between landscape structure and plant species diversity at local scale varies with scale. Then, it is fundamental to assess the appropriate extent at which landscape factors affect plant species richness at the local scale. To investigate this relation, data on plant species richness of forest communities at plot scale were extracted from a large data set and landscape metrics were calculated around the same plots for a range of extents (250–3000 m). Then, multiple regression models and variance partitioning techniques were applied to assess the amount of variance explained by the landscape metrics on plant species richness for a range of extents. In general, we found that increasing extent of the surrounding landscape analyzed, improved the strength of relationship between the landscape metrics and the properties of plant communities at plot scale. The medium-large extent was most informative as it combined a decent total variance explained with high variance explained by the pure fractions of complexity, fragmentation and disturbance and the minimum of collinearity. In conclusion, we found that it is possible and beneficial to identify a specific extent, where the redundancy in the predictor variables is minimized and the explanatory power of the pure fractions (or single groups) maximized, when examining landscape structure effects on local plant species richness. [ABSTRACT FROM AUTHOR]

Potential effects of pesticides on stream algae occur alongside complex environmental influences; in situ studies examining these effects together are few, and have not typically controlled for collinearity of variables. We monitored the dynamics of periphyton, phytoplankton, and environmental factors including atrazine, and other water chemistry variables at 6 agricultural streams in the Midwest US from spring to summer of 2011 and 2012, and used variation partitioning of community models to determine the community inertia that is explained uniquely and/or jointly by atrazine and other environmental factors or groups of factors. Periphyton and phytoplankton assemblages were significantly structured by year, day of year, and site, and exhibited dynamic synchrony both between site–years and between periphyton and phytoplankton in the same site–year. The majority of inertia in the models (55.4% for periphyton, 68.4% for phytoplankton) was unexplained. The explained inertia in the models was predominantly shared (confounded) between variables and variable groups (13.3, 30.9%); the magnitude of inertia that was explained uniquely by variable groups (15.1, 18.3%) was of the order hydroclimate > chemistry > geography > atrazine for periphyton, and chemistry > hydroclimate > geography > atrazine for phytoplankton. The variables most influential to the assemblage structure included flow and velocity variables, and time since pulses above certain thresholds of nitrate + nitrite, total phosphorus, total suspended solids, and atrazine. Time since a ≥ 30 μg/L atrazine pulse uniquely explained more inertia than time since pulses ≥ 10 μg/L or daily or historic atrazine concentrations; this result is consistent with studies concluding that the effects of atrazine on algae typically only occur at ≥ 30 μg/L and are recovered from. [ABSTRACT FROM AUTHOR]

Dispersal limitation and environmental conditions are crucial drivers of plant species distribution and establishment. As these factors operate at different spatial scales, we asked: Do the environmental factors known to determine community assembly at broad scales operate at fine scales (few meters)? How much do these factors account for community variation at fine scales? In which way do biotic and abiotic interactions drive changes in species composition? We surveyed the plant community within a dry grassland along a very steep gradient of soil characteristics like pH and nutrients. We used a spatially explicit sampling design, based on three replicated macroplots of 15 × 15, 12 × 12 and 12 × 12 m in extent. Soil samples were taken to quantify several soil properties (carbon, nitrogen, plant available phosphorus, pH, water content and dehydrogenase activity as a proxy for overall microbial activity). We performed variance partitioning to assess the effect of these variables on plant composition and statistically controlled for spatial autocorrelation via eigenvector mapping. We also applied null model analysis to test for non-random patterns in species co-occurrence using randomization schemes that account for patterns expected under species interactions. At a fine spatial scale, environmental factors explained 18% of variation when controlling for spatial autocorrelation in the distribution of plant species, whereas purely spatial processes accounted for 14% variation. Null model analysis showed that species spatially segregated in a non-random way and these spatial patterns could be due to a combination of environmental filtering and biotic interactions. Our grassland study suggests that environmental factors found to be directly relevant in broad scale studies are present also at small scales, but are supplemented by spatial processes and more direct interactions like competition. [ABSTRACT FROM AUTHOR]

Larval fish are extremely variable in space and time while sampling of populations is generally restricted and incomplete. However, estimates of abundance and mortality are important for understanding population dynamics, habitat quality, and anthropogenic impacts. Acknowledging and addressing variability during sampling and data analysis are imperative to producing informative estimates. A combination of spatially and temporally distributed ichthyoplankton sampling and Bayesian hierarchical and state-space modeling was used to partition variance and estimate abundance and mortality of larval walleye (Sander vitreus) in the Maumee River during 2010 and 2011. System variability and degree of sampling coverage have a direct impact on the quality of abundance estimates. Small scale factors (i.e., within site and day-to-day) accounted for the most variation in larval walleye densities, therefore sampling should concentrate on capturing these sources. Bayesian state-space modeling can improve estimates by sharing information through time, properly accounting for uncertainty, and producing probability distribution based estimates. Larval fish are highly variable and difficult to sample; however, the application of Bayesian methods during the data analysis process can lead to improved estimates of abundance and informed management actions. [ABSTRACT FROM AUTHOR]

Coffee berry borer (CBB) (Hypothenemus hampei ; Coleoptera: Curculionidae: Scolytinae) is a major insect pest affecting coffee cultivation that causes large economic losses worldwide. Characteristics related to its life cycle makes it very difficult to control. Usually, CBB control measures are carried out at plot scale, with almost no actions taken at wider landscape scales. It is unclear how plot level control strategies and landscape factors act alone or in combination to influence CBB infestation levels. We evaluated the joint effects of crop management at the plot level, of farm features, and of landscape structure at different spatial scales on CBB infestation in 50 Costa Rican coffee farms. On five plants in each farm, we estimated the maximum number of infested berries during the fruiting period. We measured three separate groups of variables related to plot management practices, farm features and landscape structure. To assess their single and joint contributions, their relative importance and the effects of these variables on the number of infested berries we used the variance partitioning approach of the RandomForest algorithm. When evaluating the groups of factors separately, we found that crop management explained 35% of the variability of number of infested berries, farm features 42% and landscape structure 27%. The joint contribution of all three groups of variables explained 48% of variability of the number of infested berries. However, when we assessed the single contributions of each set of variables, i.e., when controlling the other two set of variables, we found that farm features explained 17% of the variance of the number of infested berries, landscape structure 6% and crop management practices only 3%. The larger amount of the variance explained by the joint effect of crop management practices, farm features, and landscape structure suggests that to develop a pest management strategy at a local scale it is important to consider the effect of both local and landscape factors affecting pest abundance. The integrated CBB management plan should consider influences at multiple spatial scales and a coordinated action among farmers that share the same landscape would be beneficial. • Factors modulating CBB infestation are poorly known. • RandomForest analysis allows the joint and single effects of variables modulating CBB density to be assessed. • Integrated CBB management strategies should consider factors operating at both local and landscape scales. • The resource concentration hypothesis should be extended to a landscape scale. • The joint effect of plot and landscape variables is higher than any single effect. [ABSTRACT FROM AUTHOR]

Disturbance and change to C inputs can alter microbial community structure and impact ecosystem function. Particularly in temperate regions, seasonal change also has an effect on microbial communities both directly through climate and indirectly through plant function. The temporal change in microbial communities of an undisturbed pasture, disturbed pasture (similar to a single tillage event) and pasture soil amended with two forms of particulate carbon were monitored over eight consecutive seasons after grass was reestablished. The soil microbial community was assessed by a DNA fingerprinting technique (terminal restriction fragment length polymorphism, TRFLP) of bacterial, fungal and archaeal communities, and also from phospholipid fatty acid (PLFA) analysis. The single disturbance had a significant effect on fungal microbial community structure (by TRFLP) and significantly decreased the fungal:bacterial ratio. Though the change was relatively small, it persisted throughout the sampling period. Nitrate was also higher on the disturbed treatment providing evidence for the theory that changes to fungal:bacterial ratios can alter nutrient cycling and retention. Fungal communities were the most altered by the C amendments, and while bacteria were also affected by the C amendments, seasonal change was a greater cause of variation. Correlation to soil and climatic variables explained more of the total variability for PLFA (78% for all treatments) than bacterial (50%), fungal (35%) and archaeal (14%) restriction fragments. Most climate and soil variables explained significant variation for seasonal patterns in the multivariate community structures but measurements of soil moisture were important for all communities while pH was relatively more important for bacteria, temperature for fungi, and soil C:N ratio for archaea. Autumn was particularly distinct from other seasons for bacteria (less so for the fungal community) and although there was seasonal change in pH suggesting pasture management was a factor, the significant correlation of other soil characteristics suggests that plant physiological changes (most probably root exudates) also played a significant role. The large change in the saprotrophic fungal community due to the particulate C addition but minor seasonal change would tend to suggest that the fungal community may be more responsive to changes in litter inputs rather than root exudates while the reverse is true for bacteria. [ABSTRACT FROM AUTHOR]

Management of forest sites has the potential to modulate soil organic matter decomposition by changing the catalytic properties of soil microorganisms within a soil profile. In this study we examined the impact of forest management intensity and soil physico-chemical properties on the variation of enzyme activities (β-glucosidase, β-xylosidase, α-glucosidase, phenol oxidase, N-acetyl-glucosaminidase, l-leucine aminopeptidase, phosphatase) in the topsoil and two subsoil horizons in three German regions (Schorfheide-Chorin, Hainich-Dün, Schwäbische Alb). The sandy soils in the Schorfheide-Chorin (SCH) showed lower ratios of the activity of carbon (C) acquiring enzymes (β-glucosidase) relative to nitrogen (N) acquiring enzymes (N-acetyl-glucosaminidase+ l-leucine aminopeptidase), and activity of C acquiring enzymes relative to phosphorous (P) acquiring enzymes (phosphatase) than the finer textured soils in the Hainich-Dün (HAI) and Schwäbische Alb (ALB), indicating a shift in investment to N and P acquisition in the SCH. All enzyme activities, except phenol oxidase activity, decreased in deeper soil horizons as concentrations of organic C and total N did, while the decrease was much stronger from the topsoil to the first subsoil horizon than from the first subsoil to the second subsoil horizon. In contrast, phenol oxidase activity showed no significant decrease towards deeper soil horizons. Additionally, enzyme activities responsible for the degradation of more recalcitrant C relative to labile C compounds increased in the two subsoil horizons. Subsoil horizons in all regions also indicate a shift to higher N acquisition, while the strength of the shift depended on the soil type. Further, our results clearly showed that soil properties explained most of the total variance of enzyme activities in all soil horizons followed by study region, while forest management intensity had no significant impact on enzyme activities. Among all included soil properties, the clay content was the variable that explained the highest proportion of variance in enzyme activities with higher enzyme activities in clay rich soils. Our results highlight the need for large scale studies including different regions and their environmental conditions in order to derive general conclusions on which factors (anthropogenic or environmental) are most influential on enzyme activities in the whole soil profile in the long term at the regional scale. [ABSTRACT FROM AUTHOR]

Small metazoans in soil are typically animals of hydrobiont origin: They live in small amounts of water in capillaries and water film around soil particles. We studied the effects of occasional flooding on communities of soil Rotifers in the Gemenc floodplain (Duna-Dráva National Park). Based on the abundances of 31 rotifer species, an ordination determined flood frequency as a significant driving factor in rotifer development. The effect of flooding is stronger than seasonality or forest type. Many species establish populations only in never flooded (Encentrum sp., Adineta gracilis) or rarely flooded areas, while some species are present in sites flooded from time to time. Species populations showed a continuum on the given gradient with no species having their optimum on frequently flooded sites. The impact of flooding on communities is much more important than the effect of forest type or season. Significant species responses to the effect of flood frequency have been determined, which demonstrate an occupation of different niches of each species. Based on this sample of soil rotifers, it appears that aquatic animals in floodplain soil are negatively affected by floods in general. This effect is comparable with the effect of seasonal changes in the community, but is much higher than the effect of forest type or differences among replicate series. [ABSTRACT FROM AUTHOR]

Highlights: [•] Local abiotic factors explain 19% of aquatic macrophyte distribution. [•] Both water column and sediment variables are important in explaining distribution. [•] Main gradients are ionic content of the water and water body productivity. [•] In general, species richness is low and shows weak correlations with abiotic variables. [•] Only temporary pools exhibit high species richness (twofold increase). [ABSTRACT FROM AUTHOR]

Abstract: The scale dependence of ecological phenomena remains a central issue in ecology. Particularly in aquatic ecology, the consideration of the accurate spatial scale in assessing the effects of landscape factors on stream condition is critical. In this context, our study aimed at assessing the relationships between multi-spatial scale land cover patterns and a variety of water quality and diatom metrics measured at the stream reach level. This investigation was conducted in a major European river system, the Adour-Garonne river basin, characterized by a wide range of ecological conditions. Redundancy analysis (RDA) and variance partitioning techniques were used to disentangle the different relationships between land cover, water-chemistry and diatom metrics. Our results revealed a top-down “cascade effect” indirectly linking diatom metrics to land cover patterns through water physico-chemistry, which occurred at the largest spatial scales. In general, the strength of the relationships between land cover, physico-chemistry, and diatoms was shown to increase with the spatial scale, from the local to the basin scale, emphasizing the importance of continuous processes of accumulation throughout the river gradient. Unexpectedly, we established that the influence of land cover on the diatom metric was of primary importance both at the basin and local scale, as a result of discontinuous but not necessarily antagonist processes. The most detailed spatial grain of the Corine land cover classification appeared as the most relevant spatial grain to relate land cover to water chemistry and diatoms. Our findings provide suitable information to improve the implementation of effective diatom-based monitoring programs, especially within the scope of the European Water Framework Directive. [Copyright &y& Elsevier]

Abstract: According to legal regulations, all slaughtered pigs in the European Union are subject to routine meat inspection at the slaughterhouses. The resulting post-mortem findings are valuable indicators that help improve slaughterhouse and farm management and can be used to establish a feedback system regarding animal health. A sufficiently high quality of meat inspection is therefore imperative, which implies that the results of the inspection must not depend on the person carrying out the examination. The objective of the study at hand is the estimation of the amount of variation in these post-mortem findings that can be attributed to the official meat inspectors. In order to reduce the influence of the heterogeneity in the health state of the pigs, the variation due to the farms of origin was considered in the statistical model as well. The analyzed meat inspection data were recorded by 12 official meat inspectors under real working conditions at an Austrian slaughterhouse. Logistic Multilevel Models with cross-classified random effects were applied to 20 post-mortem findings. On the basis of these models, variance partitioning coefficients (VPCs) were used to estimate the amount of variation in the probabilities of these findings due to meat inspector and farm levels. The estimated VPCs suggest that especially meat inspection of blood aspiration, scalding water lungs, skin lesions and hepatitis can be deemed as not sufficiently standardized. Hardly any variation in meat inspection could be identified for other post-mortem findings, such as pericarditis, peritonitis, arthritis and milkspots. [Copyright &y& Elsevier]

Highlights: [•] The relation between the aboveground biomass (AGB) and soil fertility showed a quadratic form. [•] Remaining large trees facilitate a quicker recovery of forest structure. [•] Functional diversity was the dominant factor determining AGB stocks. [•] Canopy closure varies in time according to local environmental conditions. [•] Secondary forests can provide practical guidance for forest management and conservation. [ABSTRACT FROM AUTHOR]

Abstract: Belowground communities support a great diversity of organisms, but the factors that maintain and regulate this diversity are poorly understood. Both abiotic and biotic factors affect the abundance, diversity and distribution of soil organisms, and the spatial heterogeneity in these factors is a key in explaining belowground biodiversity. However, a combined approach estimating the relative importance of spatial and environmental factors in small-scale structuring of soil communities is yet missing. Here, a semi-natural grassland in south-central Sweden with high diversity of plants was sampled at two spatial scales (10 and 60 cm intervals) with the aim to examine the relative roles of plant identity, abiotic environmental factors and spatial factors for the small-scale spatial patterns of nematodes. The data were analysed by variance partitioning with redundancy analysis. Space, vegetation and abiotics were of similar importance for variation in nematode community composition. However, the contribution of the different sets of variables differed between the different nematode feeding groups: plant-feeding nematodes were influenced more by spatial variables, fungal-feeding nematodes and omnivores/predators more by plants and bacterial-feeding nematodes more by abiotic variables. The ranges of spatial dependence for the different feeding groups were all of the same magnitude, around 1 m. The results add to the understanding of the factors that contribute to soil biodiversity, and they show that combining plant and abiotic variables into one set of environmental variables hide important information about the drivers for belowground community assembly. [Copyright &y& Elsevier]

Abstract: Proper classification of sites is critical for the use of biological indices that can distinguish between natural and human-induced variation in biological response. The macrophyte-based index of biotic integrity was developed to assess the condition of Minnesota lakes in relation to anthropogenic stressors, but macrophyte community composition varies naturally across the state. The goal of the study was to identify environmental characteristics that naturally influence macrophyte index response and establish a preliminary lake classification scheme for biological assessment (bioassessment). Using a comprehensive set of environmental variables, we identified similar groups of lakes by clustering using flexible beta classification. Variance partitioning analysis of IBI response indicated that evaluating similar lake clusters could improve the ability of the macrophyte index to identify community change to anthropogenic stressors, although lake groups did not fully account for the natural variation in macrophyte composition. Diagnostic capabilities of the index could be improved when evaluating lakes with similar environmental characteristics, suggesting the index has potential for accurate bioassessment provided comparable groups of lakes are evaluated. [Copyright &y& Elsevier]

Abstract: Taxonomic sufficiency (TS) — defined as the minimum taxonomic detail required to discern some ecological pattern of interest — has been used extensively in bioassessment and biodiversity studies as a way of avoiding a portion of the time and monetary costs associated with species diagnoses. The taxonomic sufficiency for detecting species-level patterns among floodplain-lake benthic-invertebrate assemblages remains unexplored. We examined cross-taxonomic-level congruence in assemblage-environment relationships among 23 Chinese floodplain lakes. Our objectives were: (1) to compare the correlation between species richness and density and those at coarser taxonomic resolution; (2) to identify whether assemblage-environment relationships depend on taxonomic scale; and (3) to test whether the proportion of between-lake variability accounted for by environmental variables was independent of taxonomic scale. When taxonomic structure was described using sequentially coarser taxonomic aggregations, species-level patterns of richness and abundance were sequentially obscured (i.e., genus-level taxonomy best preserved patterns in species composition, order- and class-level taxonomy poorly represented species composition). Similar environmental variables were important for distinguishing lake species assemblages and genus assemblages; however, different environmental variables were important for describing family-, order-, and class-level assemblage patters. Moreover, environmental variables accounted for a similar amount of biological variability, regardless of taxonomic scale. Our results suggest genus taxonomy as sufficient for rapid assessments of lake diversity. Numerical dominance of the species- and genus-rich Chironomidae, Tubificidae, and Naididae, may account for the marked loss of information that occurs when lake invertebrates are assigned only to their families. In summary, we describe taxonomic sufficiency to detecting patterns of richness and abundance among subtropical lake macroinvertebrate faunas. This study will interest Chinese benthologists concerned with conservation and bioassessment. [Copyright &y& Elsevier]

Abstract: Hydrological connectivity and the frequency and intensity of floods are the key factors determining the structure of macroinvertebrates inhabiting wetland ecosystems in river valleys. In 2007, water and macroinvertebrate samples were collected on four occasions in the middle course of the Słupia River and in five oxbow lakes (Northern Poland) to determine the hydrological relations in a regulated lowland river environment marked by a moderate climate. The water bodies selected for the study featured different types of connections with the main river valley: two of them were completely cut off from the valley, one was connected via a single branch, one featured a forced-flow connection through drainage pipes, and one was connected by a system of drainage channels. Macroinvertebrates, mostly Chironomidae larvae, were predominant in the eutrophic waters of the river. The prevalent macroinvertebrates found in the eutrophicated oxbow lakes isolated from the river were Chironomidae larvae and Crustacea (mainly Asellus aquaticus). In unobstructed oxbow lakes, the main component of benthic fauna was Crustacea, while Ephemeroptera were found mostly in the water body connected to the river via a drainage channel. A canonical correspondence analysis (CCA) showed that hydrological connectivity was the main factor responsible for the structure of invertebrate populations, followed by the physical and chemical parameters of the local environment. A non-conformance analysis revealed that hydrological connectivity enhanced invertebrate abundance and biological diversity, while the overall abundance was marked by unimodal distribution. The developed general model indicates that in the group of measured environmental variables, nitrite concentrations were highly correlated with Shannon diversity and invertebrate composition, while sulphate levels were closely associated with invertebrate abundance in the waters of the analyzed ecosystems. [Copyright &y& Elsevier]

Abstract: Understanding the major drivers of diversity in forests is crucial for ecologists, conservationists, and particularly forest managers. In most forested habitats, bryophytes are diverse and important primary producers. Here we report the first study of the relative importance of regional macroclimate as compared to local variables on abundance, species richness, and community composition of bryophytes growing in soil and in dead wood in a mountain temperate forest. Using PCA axes, we built predictor sets for macroclimate, microclimate, soil attributes, and dead wood availability. The explanatory power of each set was tested using variance partitioning. Abundance and species richness of soil bryophytes was best explained by microclimate, whereas the community composition did not distinctively differ between the environmental sets. In contrast, dead wood bryophyte abundance, species richness, and community composition was clearly driven by macroclimate. Among the single axes, the component represented best by soil moisture was the main driver for soil bryophyte abundance. In contrast, dead wood bryophyte abundance was mostly affected by components correlated with minimum global radiation and minimum temperatures as well as by the component represented by dead wood. The component represented by canopy openness was superior in explaining the community composition of both soil and dead wood bryophytes. We conclude that (1) dead wood amounts should be increased in closed stands to act as a buffer during climate changes, and (2) open canopy, which provides important habitats for soil-inhabiting bryophytes, should be provided by management with slow reforestation after natural or logging openings. [ABSTRACT FROM AUTHOR]

Abstract: Although the effect of forest management on lichens in temperate forests has been widely examined, little is known about the influence of management-related factors on their biodiversity relative to factors that cannot be altered by management. Here we determined whether forest structure or climate determines lichen diversity in the Bavarian Forest National Park in southeastern Germany, taking spatial variables into account. We investigated 517 single tree stems along 4 transects in 113 pre-stratified plots (8m in diameter) in this montane forest. We grouped environmental variables into three sets: climate (macroclimate, non-manageable), forest structure (manageable), and space. The explanatory powers of these sets of variables for lichen diversity were compared using variance partitioning for the lichen community, species density, and threatened species density. The relationships of single characteristics of forest structure with lichen species diversity were analyzed using generalized linear models (GLM). Lichen diversity was better explained by stand structures than by climate. Spatial effects influenced the number of species per plot. Among the structural features, the availability of dead wood and sycamore maple as well as forest continuity were most important for the enhancement of lichen diversity. Open canopy structures affected the total diversity positively. Although the availability of large trees was not an influential factor in the GLM at the plot level, high diversity levels were generally associated with large stem diameters at the level of single stems. We provide recommendations for sustainable forest-management practices that aim at specifically enhancing lichen diversity in temperate areas experiencing low levels of air pollution. [Copyright &y& Elsevier]

Plant communities of 57 field boundaries, in four regions of Finland, were sampled for this study focusing on factors affecting species diversity and community composition. All the boundaries were buffer strips established following the guidance of an Agri-Environmental Support Scheme. Data on edaphic factors, boundary management practices and spatial coordinates were used as explanatory variables in the data analyses using variation partitioning by Redundancy Analysis and univariate statistics. The variation of the plant species composition and diversity was found to be strongly spatially structured. On the variation of species composition, spatial variables alone explained 35.0% and jointly with environmental factors 32.4% of the variation in species composition. Moreover, mowing, soil pH and P content and boundary width were shown to be important factors determining species composition. The species diversity was the lowest where the land use for agricultural production was most intensive and classification of species traits indicated high soil nitrogen levels. On the basis of this study, biodiversity in boundaries could be enhanced by appropriate management techniques and greater boundary width. Regional differences in agricultural land use should also be taken into account when planning practices for improving biodiversity. [Copyright &y& Elsevier]

Many annual cropping lands are being converted to perennial pasture in humid and subhumid areas of the USA as the economic, social, and environmental benefits of managed grazing become evident. Recent evidence about the positive effects of plant diversity on productivity is driving farmers towards management for more complex species mixes than were promoted historically for grazed pastures, but this emphasis has highlighted a lack of understanding about plant community management in pastures. To better understand this system we examined sources of variability in the plant community of a subhumid grassland that was subjected to combinations of disturbance (graze or burn), and amendment (nitrogen, carbon, or ambient), and native grass seeding treatments over 3 years (2004 to 2006). We estimated species cover five times during the study period and ordinated these data with nonmetric multidimensional scaling (NMS). The ordination explained 80% of the variation in the plant community data set. Variance in ordination site scores was ascribed to management (disturbance, soil amendment, and native grass seeding time), the environment (year, season within year, and block), or unexplained (residual) realms with a linear mixed-effects model. The overwhelming source of variability in the plant community (62–99%) was attributed to management. Ordination results illustrated that plant groups sorted out along management gradients: burned plots were shifted towards grasses while forbs and clovers were associated with grazed plots. We demonstrate how a community-level approach can be used to evaluate management regimes in agroecosystems. Our results indicate that disturbance and soil amendments can be used to shape plant communities in subhumid grasslands for specific agronomic and conservation goals. [Copyright &y& Elsevier]

Abstract: Baseline information on the biodiversity of plantation forests, including how it varies with silvicultural methods and along geographic and edaphic gradients, is fundamental when designing conservation and enhancement programmes. Ground flora communities in Sitka spruce (Picea sitchensis), ash (Fraxinus excelsior) and Japanese larch (Larix kaempferi) forests at the main stages of stand structural development, and located across the Republic of Ireland on a range of varied site types, are examined. Using flexible beta clustering and indicator species analysis, eight distinct ground flora community types are identified, varying in composition, structure and/or diversity: (i) grassland, (ii) heath, (iii) basophilic forest, (iv) closed-canopy conifer forest: first stage, (v) closed-canopy conifer forest: second stage, (vi) acidophilic forest: bryophyte-dominated, (vii) acidophilic forest: grass-dominated, and (viii) bramble-dominated. Canonical correspondence analysis (CCA) and variance partitioning are used to assess the relative influence of silvicultural, geographic and edaphic factors on ground flora composition. While geographic (e.g. previous land-use, underlying geology, proximity to old woodland and elevation) and edaphic (e.g. soil pH, organic matter content and extractable Mg and P) factors are important influences, our results demonstrate considerable scope for manipulating ground flora communities through silvicultural operations. We show, in particular, the opportunity for managing stand structure as a means of enhancing ground flora diversity and composition at the plantation scale. [Copyright &y& Elsevier]

Abstract: The morphological plasticity of tree seedlings is considered to be an important factor in shade tolerance and plant succession dynamics. However, recent studies comparing temperate deciduous species have not found the expected relationship between plasticity and shade tolerance or successional status. We measured morphological plasticity in seedlings of three temperate deciduous species of north-eastern North America, using 13 parameters associated with growth, crown geometry, branching, and leaf arrangement, as a function of a steep light gradient (0.5–43%) in young transition forests under shelterwood management. The effects of light and seedling height were investigated using variance partitioning. We studied naturally occurring seedlings of the very shade tolerant sugar maple (Acer saccharum), and planted seedlings of shade intolerant black cherry (Prunus serotina) and red oak (Quercus rubra), a species of intermediate shade tolerance. Contrary to expectations, sugar maple had the lowest light-induced plasticity and did not modify its morphology except as a function of height. It also produced relatively good growth. Moreover, black cherry displayed several unexpected characteristics, such as weak growth in response to increasing light and strong plasticity at several levels, mostly light-induced. Although red oak had a low level of overall plasticity, it produced the largest height increments under these shelterwoods. The morphological plasticity we observed lends support to models of shade tolerance which include resistance to pathogens and herbivory, and the capacity to store reserves, but still need to be supported with larger, integrated studies. Our results lead us to question how useful classic shade tolerance models based on morphological plasticity are for regeneration management and silviculture. At least under the pioneer stands we studied, both black cherry and sugar maple behaved in ways opposite to what was predicted. [Copyright &y& Elsevier]

Abstract: The variance in survival of Sclerotinia sclerotiorum''s sclerotia, carpogenic germination (apothecia) as well as Sclerotinia stem rot (SSR) severity (Disease Severity Index (DSI)) on soybean was partitioned among canopy, soil physico-chemistry and microbiology, cultural practices (2 or 3-y-corn rotation/soybean monoculture and mineral fertilization/urban compost), and spatial matrices in two soils. Partial multiple regression was used to partition the individual SSR variables variance while partial canonical redundancy analysis partitioned the DSI–apothecia and apothecia–survival variance. In clay loam, the sclerotial survival and apothecia variance were mainly explained by the spatial structure of soil physico-chemistry while the DSI did not share this spatial structure and was largely explained by the effects of 3-y-corn rotation on canopy and soil, i.e. lower weed biomass, enhanced soybean yield and fewer apothecia were correlated with disease suppressiveness. In sandy loam, the DSI variance was mostly explained by the spatial structure of canopy and physico-chemistry. Disease suppressiveness, by the interaction of 3-y-corn rotation with urban compost, was largely explained by the enhancement of soil properties, i.e. higher aggregate stability, microbial activity and soil solution concentration in exchangeable ions correlated negatively with carpogenic germination. Partitioning the SSR variance among four matrices of spatial and environmental factors allowed for the first time to interpret and quantify the variance of disease development explained by cultural practices in interaction with the main characteristics of this agroecosystem. [Copyright &y& Elsevier]

[Display omitted] • eDNA was more effective in detecting fish taxa and traits than traditional methods. • Among-method congruency in community structure was moderate. • Importance of environmental and spatial variables varied among methods. • eDNA can be more powerful for metacommunity analyses than other methods. Recent developments in environmental DNA (eDNA) metabarcoding suggest that eDNA-based representation of ecological communities can be a promising tool in both fundamental ecological research and environmental assessment. However, it is less known, how eDNA performs in characterising ecological communities and community-environment relationships at the regional scale compared with traditional sampling methods. Here, we used electrofishing (EF), gillnetting (GN) and eDNA-based surveys to compare their congruency in characterising the taxonomic and trait-based structure of (oxbow) lake fish communities and their structuring mechanisms. eDNA proved to be more effective in detecting taxa in the total samples and by traits than EF and GN. Principal coordinate analysis and multiple factor analysis showed a moderate separation of communities according to sampling methods for the taxon and the trait-based structures, respectively, but eDNA samples were always located in intermediate position in the ordination plots. Procrustes analyses indicated significant among-method congruency in community structure. However, in general, eDNA-based community patterns always showed higher correlation with either the EF or the GN-based community patterns, than the two traditional methods to each other. Variance partitioning in redundancy analyses indicated large differences among the sampling methods in the importance of environmental and spatial variables in shaping metacommunity structure. These results thus suggest that the sampling method can largely influence the identified mechanisms which govern fish metacommunity organisation. Our results suggest, that eDNA metabarcoding can be the best universal method for understanding the taxonomic and trait-based organisation of lake fish metacommunities. [ABSTRACT FROM AUTHOR]

Cities in developing countries worldwide are facing severe fine particulate matter (PM 2.5) pollution. Numerous studies have been conducted to investigate how biophysical and socioeconomic factors affect PM 2.5 concentration. However, most of these studies have typically focused on biophysical and socioeconomic factors separately rather than taking an integrated social-ecological perspective. Cities are widely recognized social-ecological systems, and such an integrative perspective is crucially important for understanding the generation and mitigation of PM 2.5 pollutants. In this study, by considering socioeconomic, biophysical, and meteorological factors simultaneously, we took a comprehensive social-ecological perspective to assess the impacts of these factors on PM 2.5 concentrations. Correlation analysis and variance partitioning were used to quantify the impacts and relative importance of the factors. The analysis was conducted across mainland China focusing on 88 major cities based on socio-economic data, monitoring data of air quality and meteorological conditions, and land cover data. The statistical analysis results revealed that: (1) The biophysical structure and socio-economic factors significantly affect urban PM 2.5 levels year round, but the impacts of meteorological factors are significant only in winter. The biophysical structure factors and the socio-economic ones contribute equally to the variations in PM 2.5 concentration. (2) The effects of the factors vary by region. In northern China, the socio-economic factors together with meteorological factors contribute the most to the variation of PM 2.5 concentration. In southern China, however, the unique effect of meteorological factors is dominant in affecting the level of PM 2.5. (3) Air temperature has a positive relationship with the concentration of PM 2.5 in northern China, but a negative relationship in southern China, which might indicate the varied dominant precursors of PM 2.5 between the two regions. This study extends our understanding of the effects of social-ecological factors on urban PM 2.5 pollution and underscores the importance of differentiated strategies for air pollution mitigation in different regions, and in different seasons, which provides a scientific basis for sustainable development from the perspective of urban air pollution mitigation. [Display omitted] • Biophysical structure, socioeconomic and meteorological factors all affected PM 2.5 • In northern China, Social economy and meteorology together affected PM 2.5 • In southern China, the meteorological factors dominated the variation of PM 2.5 • Temperature had contradictory effects on PM 2.5 between Northern and Southern China. [ABSTRACT FROM AUTHOR]

Ecosystem functions are driven by abiotic and biotic factors, but due to high collinearity of both, it is often difficult to disentangle the drivers of these ecosystem functions. We studied sedimentological and faunal controls of benthic organic matter mineralization, a crucial ecosystem process provided for by sediments of shelf seas. Subtidal benthic habitats representative of the wide permeability gradient found in the Belgian Part of the North Sea (Northeast Atlantic Shelf) were characterized in terms of sediment descriptors, macrofauna, and sediment biogeochemistry was estimated. Our results confirmed a strong correlation between sediment characteristics and macrofauna, and estimated sediment biogeochemical process rates were clearly linked to both. Results of variance partitioning and statistical modelling showed that oxic mineralization and nitrification were mainly regulated by faunal activities whereas anoxic mineralization was regulated by sediment properties, with permeability as a decisive factor. Both biotic and abiotic factors were needed to explain variability in oxygen consumption and total mineralization estimates, suggesting that macrofaunal activities have different effects across habitats. The statistical models were a useful tool to interpret the impact of anthropogenic activities in the study area and represent a step towards predicting the effects of human activities on crucial ecosystem functions. Unlabelled Image • Strong correlation between sediment properties, fauna and biogeochemical cycling. • Benthic oxic mineralization and nitrification mainly regulated by faunal activities. • Benthic anoxic mineralization mainly regulated by sediment properties. • Macrofaunal activities have variable effects across habitats. • Regression models are a useful tool to predict/understand the impact of human activities. [ABSTRACT FROM AUTHOR]

• Drivers of tree growth were identified in South Asian moist tropical forests. • Tree-ring analysis, trait-based measurements and field observations were performed. • Mixed effect modelling and variance partitioning were used to separate pure and joint effects. • Competition and sapwood area were the main drivers of tree growth. • Results have implications for forest management and CDM. Tropical forests have been focused for mitigating climate change impact through carbon sequestration in plant biomass under clean development mechanism (CDM). Since trees represent more than 98% of the above ground plant biomass, variation in tree growth rate drives carbon dynamics in tropical forests. By using tree-ring analysis, trait-based measurements, and field observations, we aimed at understanding the drivers of growth rate variation in four South Asian tropical moist forest tree species varying in plant functional types. Principal component analysis (PCA) revealed that mainly demographic and wood traits represented the first axis explaining 37% of the variance, whereas the second axis was represented by the leaf traits. Stem growth rate (DI) showed a nonlinear negative relation with competition index (CI) and the ratio of crown surface area to basal area (CBR) in three out of four tree species (p < 0.001) except Lagerstroemia speciosa which showed no significant relationship with any of the studied variables. DI was linearly positively related with light interception index (LI) and the ratio of sapwood area to heartwood area (SHR) in the shade intolerant Magnolia champaca and Toona ciliata (p < 0.001). Sap wood area (SA) had a strong positive effect on DI in the three species (p < 0.001). Taking tree size as a random factor and thus accounting for ontogenetic effects on tree growth, linear mixed effect modelling revealed that CI, SA and SHR are the best predictors of DI in M. champaca (AIC = 25.81, R2 m = 0.81) and T. ciliata (AIC = 62.95, R2 m = 0.61). In C. tabularis , CI, SA and CBR included in the best model predicting DI (AIC = 94.62, R2 m = 0.55). Variance partitioning analysis showed that the highest pure effect was observed in C. tabularis contributed by CI (12%), while the highest joint effect was found in M. champaca contributed by CI, SA and SHR (40%). Our analyses suggest that competition by neighbouring trees especially for soil moisture and the amount of active xylem portion are the main drivers of tree growth in moist tropical forests. Since tree growth rates regulate forest carbon dynamics, the insights into the growth drivers of the four selected species revealed by the study have important implications for forest/plantation management with a focus on carbon storage under CDM. [ABSTRACT FROM AUTHOR]