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Climate change is increasing the proportion of river networks experiencing flow intermittence, which in turn reduces local diversity (i.e., α-diversity) but enhances variation in species composition among sites (i.e., ß-diversity), with potential consequences on ecosystem stability. Indeed, the multiscale theory of stability proposes that regional stability can be attained not only by local processes but also by spatial asynchrony among sites. However, it is still unknown whether and how scale-dependent changes in biodiversity associated with river flow intermittence influence stability across spatial scales. To elucidate this, we here focus on multiple metacommunities of French rivers experiencing contrasting levels of flow intermittence. We clearly show that the relative contribution of spatial asynchrony to regional stability was higher for metacommunities of intermittent than perennial rivers. Surprisingly, spatial asynchrony was mainly linked to asynchronous population dynamics among sites, but not to ß-diversity. This finding was robust for both truly aquatic macroinvertebrates and for taxa that disperse aerially during their adult stages, implying the need to conserve multiple sites across the landscape to attain regional stability in intermittent rivers. By contrast, metacommunities of truly aquatic macroinvertebrates inhabiting perennial rivers were mainly stabilized by local processes. Our study provides novel evidence that metacommunities of perennial and intermittent rivers are stabilized by contrasting processes operating at different spatial scales. We demonstrate that flow intermittence enhances spatial asynchrony among sites, thus resulting in a regional stabilizing effect on intermittent river networks. Considering that climate change is increasing the proportion of intermittent rivers worldwide, our results suggest that managers need to focus on the spatial dynamics of metacommunities more than on local-scale processes to monitor, restore, and conserve freshwater biodiversity.

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Rocky shore communities are shaped by complex interactions among environmental drivers and a range of biological processes. Here, we investigated the importance of abiotic and biotic drivers on the population structure of key rocky intertidal species at 62 sites, spanning ∼50% of the Brazilian rocky shoreline (i.e., ∼500 km). Large-scale population patterns were generally explained by differences in ocean temperature and wave exposure. For the gastropod species Lottia subrugosa, differences at smaller scales (i.e., 0.1-1 km) were better explained by other abiotic influences such as freshwater discharge and substrate roughness. Based on the general population patterns of intertidal species identified, three main oceanographic groups were observed: a cold-oligotrophic grouping at northern sites (Lakes sub-region), a eutrophic group associated with large estuaries and urban zones (Santos and Guanabara bays); and a transitional warm-water group found between the two more productive areas. Larger individuals of Stramonita brasiliensis, L. subrugosa and Echinolittorina lineolata were generally found in the cold-oligotrophic system (i.e., upwelling region), while small suspension feeders dominate the warm-eutrophic systems. Evidence of bottom-up regulation was not observed, and top-down regulation effects were only observed between the whelk S. brasiliensis and its mussel prey Pernaperna. Environmental drivers as compared to biotic interactions, therefore, play a key role determining the population structure of multiple intertidal species, across a range of spatial scales along the SW Atlantic shores.

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Investigating the effects of spatial scales on the uncertainty and sensitivity analysis of the social vulnerability index (SoVI) model output is critical, especially for spatial scales finer than the census block group or census block. This study applied the intelligent dasymetric mapping approach to spatially disaggregate the census tract scale SoVI model into a 300-m grids resolution SoVI map in Davidson County, Nashville. Then, uncertainty analysis and variance-based global sensitivity analysis were conducted on two scales of SoVI models: (a) census tract scale; (b) 300-m grids scale. Uncertainty analysis results indicate that the SoVI model has better confidence in identifying places with a higher socially vulnerable status, no matter the spatial scales in which the SoVI is constructed. However, the spatial scale of SoVI does affect the sensitivity analysis results. The sensitivity analysis suggests that for census tract scale SoVI, the indicator transformation and weighting scheme are the two major uncertainty contributors in the SoVI index modeling stages. While for finer spatial scales like the 300-m grid's resolution, the weighting scheme becomes the uttermost dominant uncertainty contributor, absorbing uncertainty contributions from indicator transformation.

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Urban areas are increasingly vulnerable to sudden flooding disasters caused by intense rainfall and high imperviousness degree, resulting in great economic losses and human casualties. Interactions between rainfall data and urban catchment characteristics highlight the urgent need of accurate and effective precipitation data to apply in reliable hydrological simulations. However, it remains a challenge to obtain accurate rainfall datasets on such small scales in urban areas. As satellite remote sensing is the only method that can achieve global observation, it is important to evaluate satellite precipitation products in their ability to accurately capture intense precipitation on urban flood scales. This study evaluates the performance of the latest version 06B (V06B) Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) in North China Plain, with using the Radar-Gauge merged precipitation estimates as reference data. First, it could be concluded that IMERG fails to accurately estimate precipitation in the whole study area, having the problem of overestimating light precipitation and underestimating heavy precipitation. Second, results show that IMERG has poor ability to capture heavy precipitation on small scales, with the percentage of Hit nearly 0 and the percentage of Miss higher than 40 % for all the precipitation cases. Third, with the expansion of heavy precipitation centers' coverage, the problem of IMERG not to detect heavy precipitation gets mitigated, with the percentage of Miss decreasing by 14 % (19 %). However, the ability to capture both spatial location and precipitation intensity is still not good, the percentage of Hit ranging from 0.05 % to 7 %, without obvious improvement. When IMERG is able to capture the center of strong precipitation, it also tends to overestimate the weak precipitation around the center of strong precipitation. Results of this study provide an improved understanding of how well the V06B IMERG products capture the heavy precipitation center at small scales in urban areas, which will be useful for both developers and users of IMERG.

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The metacommunity theory enhances our understanding of how ecological processes regulate community structure. Yet, unraveling the complexities of soil nematode metacommunity structures across various spatial scales and determining the factors influencing these patterns remains challenging. Therefore, we conducted an investigation on soil nematode metacommunities spanning from north to south in the Northeastern China. Our aim was to test whether nematode metacommunities were structured by different drivers under three land covers (i.e., farmland, grassland and woodland) at the local and regional scales. The results revealed that the Clementsian, Gleasonian and their quasi-structures of soil nematodes collectively accounted for 93% of the variation across the three land covers at the local and regional scales. These structures suggest that the soil nematode metacommunities in the Northeast China responded to fluctuations in environmental gradients. At the local scale, metacommunities were primarily shaped by biological interactions. At the regional scale, environmental heterogeneity, dispersal limitation and biological interactions all contributed to nematode metacommunities. Meanwhile, biological interactions under three land covers were represented within different trophic groups, with plant parasites predominant in farmlands and bacterivores in grasslands and woodlands. In conclusion, the metacommunity structures of soil nematodes remain stable at different spatial scales and land covers. Biological interactions are widespread among nematodes regardless of changes in spatial scales and land covers. This study reveals the importance of nematode sensitivity to the environment and biological interactions in shaping the nematode metacommunities, potentially enhancing our understanding of the spatial patterns of nematode metacommunities.

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Understanding how habitat attributes (e.g., patch area and sizes, connectivity) control recruitment and how this is modified by processes operating at larger spatial scales is fundamental to understanding population sustainability and developing successful long-term restoration strategies for marine foundation species-including for globally threatened reef-forming oysters. In two experiments, we assessed the recruitment and energy reserves of oyster recruits onto remnant reefs of the oyster Saccostrea glomerata in estuaries spanning 550 km of coastline in southeastern Australia. In the first experiment, we determined whether recruitment of oysters to settlement plates in three estuaries was correlated with reef attributes within patches (distances to patch edges and surface elevation), whole-patch attributes (shape and size of patches), and landscape attributes (connectivity). We also determined whether environmental factors (e.g., sedimentation and water temperature) explained the differences among recruitment plates. We also tested whether differences in energy reserves of recruits could explain the differences between two of the estuaries (one high- and one low-sedimentation estuary). In the second experiment, across six estuaries (three with nominally high and three with nominally low sedimentation rates), we tested the hypothesis that, at the estuary scale, recruitment and survival were negatively correlated to sedimentation. Overall, total oyster recruitment varied mostly at the scale of estuaries rather than with reef attributes and was negatively correlated with sedimentation. Percentage recruit survival was, however, similar among estuaries, although energy reserves and condition of recruits were lower at a high- compared to a low-sediment estuary. Within each estuary, total oyster recruitment increased with patch area and decreased with increasing tidal height. Our results showed that differences among estuaries have the largest influence on oyster recruitment and recruit health and this may be explained by environmental processes operating at the same scale. While survival was high across all estuaries, growth and reproduction of oysters on remnant reefs may be affected by sublethal effects on the health of recruits in high-sediment estuaries. Thus, restoration programs should consider lethal and sublethal effects of whole-estuary environmental processes when selecting sites and include environmental mitigation actions to maximize recruitment success.

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[This corrects the article DOI: 10.3389/fmicb.2023.1284864.].

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The amounts and pathways of reactive nitrogen (Nr) losses in Austria into the surface water, soil, and atmosphere were determined under four climate change scenarios for the period 2041-2070. Two nutrient models were used to undertake the analysis at two different scales. Firstly, a semi-empirical, conceptual model (MONERIS) was setup for Austria to calculate the overall annual Nr surpluses, categorise flows of Nr, and identify regional hotspots of Nr losses. Secondly, a physically based eco-hydrological model (SWAT) was setup in three agricultural catchments to determine the hydrological processes related to Nr transport and quantify the amounts transported by various pathways in cropland at a detailed spatial and temporal resolution. The agricultural N surplus calculations for Austria were revised and used as input data for both models. The MONERIS and SWAT simulated inorganic N loads transported into waterbodies are overall similar, with average differences for the subsurface inorganic N loads of ±3 kg ha-1 yr-1 and for surface inorganic N loads of +0.4 to -0.03 kg ha-1 yr-1. Crop level N losses under future climate scenarios was contingent upon the fertilizer type, the crop grown and its accumulated biomass, as well as the type of climate scenario (wet or dry). In the SWAT model, an examination of the sensitivity of the input data (climate data and parameter values) found the dominant contribution to the sensitivity of simulated monthly discharge was from the climate data (69 % to 98 %). For simulating N loads, the climate scenarios contributed 30 % to 89 % of the sensitivity. Simulating Nr flows under climate scenarios is policy relevant to assess critical areas of N losses and identify future N transport pathways. Using a dual-model approach saves on resources required to set up a complex, data intensive model at a large scale, and can focus on critical catchments in detail.

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While the health benefits of exposure to urban greenspace have been widely discussed at different spatial scales, the comprehensive health effects of multiscale greenspace exposure are far from understood. There is a lack of quantified evidence when conducting cost-effective greenspace management practices for promoting human health and well-being. This study proposed a conceptual model that links objective and subjective greenspace exposure metrics at different spatial scales with self-rated health of residents. The model attempted to deconstruct and explore the associations between multiscale greenspace exposure and human health, and a cross-sectional study was conducted to examine the model. Taking urban parks in the central city of Beijing as case study area, the objective greenspace exposure metrics at both the site and subdistrict scales were spatial explicitly assessed, and the subjective exposure metrics and self-rated health status of 1017 respondents were obtained through questionnaire survey and spatial positioning. The results of multiple regression analyses and path analyses suggested that greenspace exposure metrics at both site and subdistrict scales were significantly associated with the respondents' self-rated health status, with the exposure metrics at the site scale being more important than those at the subdistrict scale in affecting human health. The contribution of urban parks to self-rated physical and mental health of respondents varied across spatial scales. Specifically, the aesthetic value of urban parks at site scale contributed the most to mental health by promoting respondents' resting behaviors in urban parks, and the density of urban parks at subdistrict scale had the most significant effects on self-rated physical health by increasing the usage frequency of urban parks. Findings of this study can contribute to understanding the complex associations between urban greenspace and human health from a multiscale perspective, and are also expected to provide quantified information for health-oriented urban greenspace planning and management practices.

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Habitat loss (HL) is a major cause of species extinctions. Although the effects of HL beyond the directly impacted area have been previously observed, they have not been modelled explicitly, especially in an eco-evolutionary context. To start filling this gap, we study a two-patch deterministic consumer-resource model, with one of the patches experiencing loss of resources as a special case of HL. Our model allows foraging and mating within a patch as well as between patches. We then introduce heritable variation in consumer traits related to resource utilization and patch use to investigate eco-evolutionary dynamics and compare results with constant and no trait variation scenarios. Our results show that HL in one patch can indeed reduce consumer densities in the neighbouring patch but can also increase consumer densities in the neighbouring patch when the resources are overexploited. Yet at the landscape scale, the effect of HL on consumer densities is consistently negative. Patch isolation increases consumer density in the patch experiencing HL but has generally negative effects on the neighbouring patch, with context-dependent results at the landscape scale. With high cross-patch dependence and coupled foraging and mating preferences, local HL can sometimes even lead to landscape-level consumer extinction. Eco-evolutionary dynamics can rescue consumers from such extinction in some cases if their death rates are sufficiently small. More generally, trait evolution had positive or negative effects on equilibrium consumer densities after HL, depending on the evolving trait and the spatial scale considered. In summary, our findings show that HL at a local scale can affect the neighbouring patch and the landscape as a whole, where heritable trait variation can, in some cases, alleviate the impact of HL. We thus suggest joint consideration of multiple spatial scales and trait variation when assessing and predicting the impacts of HL.

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Common reed (Phragmites australis) is a widespread grass species that exhibits a high degree of intraspecific variation for functional traits along environmental gradients. However, the mechanisms underlying intraspecific variation and adaptation strategies in response to environmental gradients on a regional scale remain poorly understood. In this study, we measured leaf, stem, and root traits of common reed in the lakeshore wetlands of the arid and semi-arid regions of the Inner Mongolia Plateau aiming to reveal the regional-scale variation for functional traits in this species, and the corresponding potentially influencing factors. Additionally, we aimed to reveal the ecological adaptation strategies of common reed in different regions using the plant economics spectrum (PES) theory. The results showed that functional-trait variation followed significant latitudinal and longitudinal patterns. Furthermore, we found that these variations are primarily driven by temperature-mediated climatic differences, such as aridity, induced by geographical distance. In contrast, soil properties and the combined effects of climate and soil had relatively minor effects on such properties. In the case of common reed, the PES theory applies to the functional traits at the organ, as well as at the whole-plant level, and different ecological adaptation strategies across arid and semi-arid regions were confirmed. The extent of utilization and assimilation of resources by this species in arid regions was a conservative one, whereas in semi-arid regions, an acquisition strategy prevailed. This study provides new insights into intraspecific variations for functional traits in common reed on a regional scale, the driving factors involved, and the ecological adaptation strategies used by the species. Moreover, it provided a theoretical foundation for wetland biodiversity conservation and ecological restoration.

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Introduction: Biodiversity maintenance and its underlying mechanisms are central issues of ecology. However, predicting the composition turnovers of microbial communities at multiple spatial scales remains greatly challenging because they are obscured by the inconsistent impacts of climatic and local edaphic conditions on the assembly process. Methods: Based on the Illumina MeSeq 16S/18S rRNA sequencing technology, we investigated soil bacterial and eukaryotic communities in biocrusts with different successional levels at a subcontinental scale of Northern China. Results: Results showed that irrespective of spatial scale, bacterial α diversity increased but eukaryotic diversity decreased with the primary succession, whereas both ß diversities decreased at the subcontinental scale compared with smaller scales, indicating that the biogeographic pattern of soil microorganisms was balanced by successional convergence and distance decay effect. We found that the convergence of bacterial and eukaryotic communities was attributed to the turnovers of generalist and specialist species, respectively. In this process, edaphic and climatic factors showed unique roles in the changes of diversity at local/subcontinental scales. Moreover, the taxonomic diversity tended to be more susceptible to climatic and edaphic conditions, while biotic factors (photosynthesis and pigments) were more important to phylogenetic diversity. Conclusion: Taken together, our study provided comprehensive insights into understanding the pattern of microbial diversity at multiple spatial scales of drylands.

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Environmental circumstances shaping soil microbial communities have been studied extensively. However, due to disparate study designs, it has been difficult to resolve whether a globally consistent set of predictors exists, or context-dependency prevails. Here, we used a network of 18 grassland sites (11 of those containing regional plant productivity gradients) to examine (i) if similar abiotic or biotic factors predict both large-scale (across sites) and regional-scale (within sites) patterns in bacterial and fungal community composition, and (ii) if microbial community composition differs consistently at two levels of regional plant productivity (low vs. high). Our results revealed that bacteria were associated with particular soil properties (such as base saturation) and both bacteria and fungi were associated with plant community composition across sites and within the majority of sites. Moreover, a discernible microbial community signal emerged, clearly distinguishing high and low-productivity soils across different grasslands independent of their location in the world. Hence, regional productivity differences may be typified by characteristic soil microbial communities across the grassland biome. These results could encourage future research aiming to predict the general effects of global changes on soil microbial community composition in grasslands and to discriminate fertile from infertile systems using generally applicable microbial indicators.

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In this study, visual-near infrared(VNIR), short-wave infrared(SWIR), and VNIR + SWIR fusion hyperspectral data of Polygonatum cyrtonema from different geographical origins were collected and preprocessed by first derivative(FD), second derivative(SD), Savitzky-Golay smoothing(S-G), standard normalized variate(SNV), multiplicative scatter correction(MSC), FD+S-G, and SD+S-G. Three algorithms, namely random forest(RF), linear support vector classification(LinearSVC), and partial least squares discriminant analysis(PLS-DA), were used to establish the identification models of P. cyrtonema origin from three spatial scales, i.e., province, county, and township, respectively. Successive projection algorithm(SPA) and competitive adaptive reweighted sampling(CARS) were used to screen the characteristic bands, and the P. cyrtonema origin identification models were established according to the selected characteristic bands. The results showed that(1)after FD preprocessing of VNIR+SWIR fusion hyperspectral data, the accuracy of recognition models established using LinearSVC was the highest, reaching 99.97% and 99.82% in the province origin identification model, 100.00% and 99.46% in the county origin identification model, and 99.62% and 98.39% in the township origin identification model. The accuracy of province, county, and township origin identification models reached more than 98.00%.(2)Among the 26 characteristic bands selected by CARS, after FD pretreatment, the accuracy of origin identification models of different spatial scales was the highest using LinearSVC, reaching 98.59% and 97.05% in the province origin identification model, 97.79% and 94.75% in the county origin identification model, and 90.13% and 87.95% in the township origin identification model. The accuracy of identification models of different spatial scales established by 26 characteristic bands reached more than 87.00%. The results show that hyperspectral imaging technology can realize accurate identification of P. cyrtonema origin from different spatial scales.

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Changes in biodiversity often affect ecosystem functioning. However, most previous biodiversity and ecosystem functioning (BEF) studies have generally been limited to very small spatial grains. Thus, knowledge regarding the biodiversity-ecosystem functioning relationships across spatial scales is lacking. Moreover, the multiscale nature of biodiversity, and specifically ß diversity (i.e., spatial heterogeneity in species composition) was still largely missing in BEF studies. Here, using the vegetation and functional trait data collected from four 6-ha forest dynamics plots (FDPs) in temperate and tropical forests in China, we examine the scale-dependent relationships between tree diversity and the aboveground biomass (AGB), as well as the roles of species spatial heterogeneity in determining the AGB. In tropical forests, the effect of species richness on AGB decreased with spatial grains, while functional dominance played a stronger role at larger spatial grains. In temperate forests, positive relationship between diversity and AGB occurred at all spatial grains, especially on smaller scales. In both temperate and tropical forests, ß diversity was positively correlated with AGB, but weaker than α diversity in determining AGB. Overall, complementarity and selection hypothesis play dominant role in determining AGB in temperate and tropical forests, respectively. The roles of these underlying mechanisms are more pronounced with increasing spatial scales. ß diversity, a hitherto underexplored facet of biodiversity, is likely to increase ecosystem functions by species spatial turnover and should not be neglected in BEF explorations. Our findings have practical implications for forest management and demonstrate that biotic heterogeneity plays an important positive role in ecosystem functioning.

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Phenotypic plasticity is a main mechanism for sessile organisms to cope with changing environments. Plasticity is genetically based and can evolve under natural selection so that populations within a species show distinct phenotypic responses to environment. An important question that remains elusive is whether the intraspecific variation in plasticity at different spatial scales is independent from each other. To test whether variation in plasticity to macro- and micro-environmental variation is related among each other, we used growth data of 25 Pinus pinaster populations established in seven field common gardens in NW Spain. Phenotypic plasticity to macro-environmental variation was estimated across test sites while plasticity to micro-environmental variation was estimated by using semivariography and kriging for modeling within-site heterogeneity. We provide empirical evidence of among-population variation in the magnitude of plastic responses to both micro- and macro-environmental variation. Importantly, we found that such responses were positively correlated across spatial scales. Selection for plasticity at one scale of environmental variation may impact the expression of plasticity at other scales, having important consequences on the ability of populations to buffer climate change. These results improve our understanding of the ecological drivers underlying the expression of phenotypic plasticity.

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Assessing spatial variability in biodiversity and its relationships with potential drivers is necessary for understanding and predicting changes in ecosystems. Here, we evaluated spatial patterns in sessile macrobenthic communities in rocky intertidal habitats along the southwestern Atlantic (SE Brazil), spanning over 500 km of coastline. We applied a rapid-survey approach focusing on the main space occupiers and habitat-forming taxa. We partitioned community variance into spatial scales ranging from metres to hundreds of kilometres and assessed whether community patterns were associated with variation in shore topography, nearshore ocean, and human influence. The communities from the mid-midlittoral level exhibited equivalent variation (31-35%) at the scales of quadrats (metres), sites (kilometres), and sub-regions (tens of kilometres). For the communities from the low-midlittoral and infralittoral fringe levels, most variability occurred at the scales of quadrats and sites (30-42%), followed by sub-regions (22%). Wave fetch, sea surface temperature (SST), and shore inclination were the variables that best explained community structure at the mid-midlittoral. At the low-midlittoral and infralittoral fringe, the most influential variables were related to oceanic forcing (SST, total suspended solids, particulate organic carbon, chlorophyll-a concentration) and human influence. Univariate analyses also revealed strong associations between the abundance of the main components of the communities and the predictor variables evaluated. Our results suggest that urbanised estuarine bays and coastal upwelling regimes have a strong influence on adjacent benthic communities, driving macroecological patterns in the study area. This study advances the knowledge in macroecology and biogeography of rocky shores in an understudied coastline and globally and provides valuable insights for future assessments of ecological changes resulting from unfolding human impacts.

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Spatial heterogeneity affects plant community composition and diversity. It is particularly noticeable in annual plant communities, which vary in space and time over short distances and periods, forming meta-communities at the regional scale. This study was conducted at the coastal dune ecosystem in Nizzanim nature reserve, Israel. This study aimed to analyze the effect of the spatial heterogeneity, which is expressed in differences in the fixation levels of the dunes and patches outside and beneath the dominant Artemisia monosperma shrubs, on the characteristics of the annual plant meta-community and its temporal stability, considering the mechanisms that may affect it. Thirteen dunes were studied: three mobile, seven semi-fixed, and three fixed dunes. Data on the annual plants were collected during the spring seasons of 2006, 2007, 2009, 2014, 2015, and 2016. For each dune, 72 quadrats of 40×40 cm were sampled yearly, with 24 quadrats per slope aspect (windward, leeward, and crest), 12 under the shrub, and 12 in the open. The results indicate that the transition from mobile dunes through semi-fixed to fixed dunes is characterized by an increase in annual plant cover, species richness, species diversity, changes in plant communities, and stability driven by the asynchrony of species population fluctuations. Asynchrony affected the stability of the meta-community of this ecosystem in patches beneath the shrubs but not in the open patches.

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Spatial heterogeneity in plant-soil feedbacks (PSFs) has been evidenced to influence plant growth. However, it is unclear whether patch size and contrast of PSF heterogeneity influence plant growth. We first conditioned a background soil by seven species separately and then grew each of them in a homogeneous soil and three heterogeneous soils. The first heterogeneous soil (large patch and high contrast; LP-HC) consisted of two large patches, of which one was filled with the sterilized background soil and the other with the conditioned soil. The second heterogeneous soil (small patch and high contrast; SP-HC) consisted of four small patches, of which two were filled the sterilized background soil and the other two with the conditioned soil. The third heterogeneous soil (small patch and low contrast; SP-LC) also consisted of four patches, of which two were filled with a 1:3 (w:w) mixture and the other two with a 3:1 mixture of the sterilized background soil and the conditioned soil. In the homogeneous soil, all patches were filled with a 1:1 mixture of the two soils. Both shoot biomass and root biomass were equal in the homogeneous and heterogeneous soils. No significant growth difference was observed between the SP-HC and LP-HC heterogeneous soil. However, shoot biomass and root biomass of the legume Medicago sativa, and root biomass of the grass Lymus dahuricus were greater in the SP-HC heterogeneous soil than in the SP-LC heterogeneous soil, probably due to enhanced root growth in the conditioned soil. Moreover, plant growth in the heterogeneous soils was associated with plant growth but not soil nutrient availability at the end of the conditioning phase. Our results show for the first time that patch contrast of PSF heterogeneity can influence plant growth via changing root placement and highlight the importance of fundamentally different facets of PSF variability.

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River and stream conservation programs have historically focused on a single spatial scale, for example, a watershed or stream site. Recently, the use of landscape information (e.g., land use and land cover) at multiple spatial scales and over large spatial extents has highlighted the importance of incorporating a landscape perspective into stream protection and restoration activities. Previously, we developed a novel framework that links information about watershed-, catchment-, and reach-scale integrity with stream biological condition using scatterplots and a landscape integrity map. Here we examined an application of this approach for streams in urban and other settings in King County, Washington State, United States, where we related stream macroinvertebrate condition to two indices of landscape integrity, the US Environmental Protection Agency's (USEPA) nationally available Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI). We generated a scatterplot of IWI versus ICI for sample sites, where points represented site macroinvertebrate condition from poor to good. The same data were also visualized as a landscape integrity map that displayed catchments of King County according to the level of watershed and catchment integrity (high or low IWI/ICI). Almost three-quarters of poor-condition sites were associated with high-integrity watersheds and catchments (i.e., underperforming sites), which suggested that either one or both national indicators were insufficient for this area, and that sites underperformed because of local-scale factors. In response, we used a catchment-scale indicator related to forest condition (PctForestCat) after examining several GIS-based dispersal indicators from the National Hydrography Dataset and other candidates from the USEPA's StreamCat dataset. We then compared the results of the scatterplots and maps based on the current and original analyses and found that many of the sites previously classified as underperforming now performed as expected, that is, they were poor-condition sites in poor-condition catchments. This analysis demonstrates how results based on a national dataset can be improved by developing an alternative that represents regionally important stressors. The methods used to develop an effective landscape indicator based on StreamCat datasets, and the utility of the multiscale approach, could provide important tools for prioritizing, optimizing, and communicating stream conservation actions.