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1.
Hierarchical relationships between landscape structure and temperature in a managed forest landscape 总被引：10，自引：1，他引：9
Saunders Sari C. Chen Jiquan Crow Thomas R. Brosofske Kimberley D. 《Landscape Ecology》1998,13(6):381-395
Management may influence abiotic environments differently across time and spatial scale, greatly influencing perceptions of fragmentation of the landscape. It is vital to consider a priori the spatial scales that are most relevant to an investigation, and to reflect on the influence that scale may have on conclusions. While the importance of scale in understanding ecological patterns and processes has been widely recognized, few researchers have investigated how the relationships between pattern and process change across spatial and temporal scales. We used wavelet analysis to examine the multiscale structure of surface and soil temperature, measured every 5 m across a 3820 m transect within a national forest in northern Wisconsin. Temperature functioned as an indicator – or end product – of processes associated with energy budget dynamics, such as radiative inputs, evapotranspiration and convective losses across the landscape. We hoped to determine whether functional relationships between landscape structure and temperature could be generalized, by examining patterns and relationships at multiple spatial scales and time periods during the day. The pattern of temperature varied between surface and soil temperature and among daily time periods. Wavelet variances indicated that no single scale dominated the pattern in temperature at any time, though values were highest at finest scales and at midday. Using general linear models, we explained 38% to 60% of the variation in temperature along the transect. Broad categorical variables describing the vegetation patch in which a point was located and the closest vegetation patch of a different type (landscape context) were important in models of both surface and soil temperature across time periods. Variables associated with slope and microtopography were more commonly incorporated into models explaining variation in soil temperature, whereas variables associated with vegetation or ground cover explained more variation in surface temperature. We examined correlations between wavelet transforms of temperature and vegetation (i.e., structural) pattern to determine whether these associations occurred at predictable scales or were consistent across time. Correlations between transforms characteristically had two peaks; one at finer scales of 100 to 150 m and one at broader scales of >300 m. These scales differed among times of day and between surface and soil temperatures. Our results indicate that temperature structure is distinct from vegetation structure and is spatially and temporally dynamic. There did not appear to be any single scale at which it was more relevant to study temperature or this pattern-process relationship, although the strongest relationships between vegetation structure and temperature occurred within a predictable range of scales. Forest managers and conservation biologists must recognize the dynamic relationship between temperature and structure across landscapes and incorporate the landscape elements created by temperature-structure interactions into management decisions. 相似文献
2.
Can landscape indices predict ecological processes consistently? 总被引：36，自引：0，他引：36
The ecological interpretation of landscape patterns is one of the major objectives in landscape ecology. Both landscape patterns and ecological processes need to be quantified before statistical relationships between these variables can be examined. Landscape indices provide quantitative information about landscape pattern. Response variables or process rates quantify the outcome of ecological processes (e.g., dispersal success for landscape connectivity or Morisita's index for the spatial distribution of individuals). While the principal potential of this approach has been demonstrated in several studies, the robustness of the statistical relationships against variations in landscape structure or against variations of the ecological process itself has never been explicitly investigated. This paper investigates the consistency of correlations between a set of landscape indices (calculated with Fragstats) and three response variables from a simulated dispersal process across heterogeneous landscapes (cell immigration, dispersal success and search time) against variation in three experimental treatments (control variables): habitat amount, habitat fragmentation and dispersal behavior. I found strong correlations between some landscape indices and all three response variables. However, 68% of the statistical relationships were highly inconsistent and sometimes ambiguous for different landscape structures and for differences in dispersal behavior. Correlations between one landscape index and one response variable could range from highly positive to highly negative when derived from different spatial patterns. I furthermore compared correlation coefficients obtained from artificially generated (neutral) landscape models with those obtained from Landsat TM images. Both landscape representations produced equally strong and weak statistical relationships between landscape indices and response variables. This result supports the use of neutral landscape models in theoretical analyses of pattern-process relationships. 相似文献
3.
J. Luis Hernández-Stefanoni Juan Manuel Dupuy Fernando Tun-Dzul Filogonio May-Pat 《Landscape Ecology》2011,26(3):355-370
Three central related issues in ecology are to identify spatial variation of ecological processes, to understand the relative
influence of environmental and spatial variables, and to investigate the response of environmental variables at different
spatial scales. These issues are particularly important for tropical dry forests, which have been comparatively less studied
and are more threatened than other terrestrial ecosystems. This study aims to characterize relationships between community
structure and landscape configuration and habitat type (stand age) considering different spatial scales for a tropical dry
forest in Yucatan. Species density and above ground biomass were calculated from 276 sampling sites, while land cover classes
were obtained from multi-spectral classification of a Spot 5 satellite imagery. Species density and biomass were related to
stand age, landscape metrics of patch types (area, edge, shape, similarity and contrast) and principal coordinate of neighbor
matrices (PCNM) variables using regression analysis. PCNM analysis was performed to interpret results in terms of spatial
scales as well as to decompose variation into spatial, stand age and landscape structure components. Stand age was the most
important variable for biomass, whereas landscape structure and spatial dependence had a comparable or even stronger influence
on species density than stand age. At the very broad scale (8,000–10,500 m), stand age contributed most to biomass and landscape
structure to species density. At the broad scale (2,000–8,000 m), stand age was the most important variable predicting both
species density and biomass. Our results shed light on which landscape configurations could enhance plant diversity and above
ground biomass. 相似文献
4.
Multiscale sources of variation in ecological variables: modeling spatial dispersion,elaborating sampling designs 总被引：6，自引：0，他引：6
Detection of structured spatial variation and identification of spatial scales are important aspects of ecological studies. Spatial structures can correspond to physical features of the environment or to intrinsic characteristics of ecological processes and phenomena. Spatial variability has been approached through several techniques such as classical analysis of variance, or the calculation of fractal dimensions, correlograms or variograms. Under certain assumptions, these techniques are all closely related to one another and represent equivalent tools to characterize spatial structures.Our perception of ecological variables and processes depends on the scale at which variables are measured. We propose simple nested sampling designs enabling the detection of a wide range of spatial structures that show the relationships among nested spatial scales. When it is known that the phenomenon under study is structured as a nested series of spatial scales, this provides useful information to estimate suitable sampling intervals, which are essential to establish the relationships between spatial patterns and ecological phenomena. The use of nested sampling designs helps in choosing the most suitable solutions to reduce the amount of random variation resulting from a survey. These designs are obtained by increasing the sampling intensity to detect a wider spectrum of frequencies, or by revisiting the sampling technique to select more representative sampling units. 相似文献
5.
Blake E. Feist E. Ashley Steel David W. Jensen Damon N. D. Sather 《Landscape Ecology》2010,25(5):727-743
Differences in the strength of species-habitat relationships across scales provide insights into the mechanisms that drive these relationships and guidance for designing in situ monitoring programs, conservation efforts and mechanistic studies. The scale of our observation can also impact the strength of perceived relationships between animals and habitat conditions. We examined the relationship between geographic information system (GIS)-based landscape data and Endangered Species Act-listed anadromous Pacific salmon (Oncorhynchus spp.) populations in three subbasins of the Columbia River basin, USA. We characterized the landscape data and ran our models at three spatial scales: local (stream reach), intermediate (6th field hydrologic units directly in contact with a given reach) and catchment (entire drainage basin). We addressed three questions about the effect of scale on relationships between salmon and GIS representations of landscape conditions: (1) at which scale does each predictor best correlate with salmon redd density, (2) at which scale is overall model fit maximized, and (3) how does a mixed-scale model compare with single scale models (mixed-scale meaning models that contain variables characterized at different spatial scales)? We developed mixed models to identify relationships between redd density and candidate explanatory variables at each of these spatial scales. Predictor variables had the strongest relationships with redd density when they were summarized over the catchment scale. Meanwhile strong models could be developed using landscape variables summarized at only the local scale. Model performance did not improve when we used suites of potential predictors summarized over multiple scales. Relationships between species abundance and land use or intrinsic habitat suitability detected at one scale cannot necessarily be extrapolated to other scales. Therefore, habitat restoration efforts should take place in the context of conditions found in the associated watershed or landscape. 相似文献
6.
Models of local small-scale ecological processes can be used to describe related processes at larger spatial scales if the influences of increased scale and heterogeneity are carefully considered. In this paper we consider the changes in the functional representation of an ecological process that can occur as one moves from a local small-scale model to a model of the aggregate expression of that process for a larger spatial extent. We call these changes spatial transmutation. We specifically examine landscape heterogeneity as a cause of transmutation. Spatial transmutation as a consequence of landscape heterogeneity is a source of error in the prediction of aggregate landscape behavior from smaller scale models. However, we also demonstrate a procedure for taking advantage of spatial transmutation to develop appropriately scaled landscape functions. First a mathematical function describing the process of interest as a local function of local variables is defined. The spatial heterogeneity of the local variables is described by their statistical distribution in the landscape. The aggregate landscape expression of the local process is then predicted by calculating the expected value of the local function, explicitly integrating landscape heterogeneity. Monte Carlo simulation is used to repeat the local-to-landscape extrapolation for a variety of landscape patterns. Finally, the extrapolated landscape results are regressed on landscape variables to define response functions that explain a useful fraction of the total variation in landscape behavior. The response functions are hypotheses about the functional representation of the local process at the larger spatial scale. 相似文献
7.
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9.
We explored the ways in which environmental variation at multiple spatial scales influences the organization of ant species
into local communities. Ground-dwelling ants were sampled in sandhill habitat at 33 locations throughout northern Florida,
USA. Variance partitioning of local, landscape, and regional datasets using partial redundancy analysis indicates that ant
community composition is significantly influenced by environmental variability across all scales of analysis. Habitat generalists
appear to replace habitat specialists at sites with high proportions of matrix habitat in the surrounding landscape. Conversely,
habitat specialists appear to replace habitat generalists at sites with more sandhill habitat in the surrounding landscape
and greater amounts of bare ground locally. Local niche differentiation leading to species-sorting, combined with the effects
of spatially structured dispersal dynamics at landscape scales, may explain this pattern of community structure. Regional
influences on local ant communities were correlated with geographical and environmental gradients at distinct regional scales.
Therefore, local ant communities appear to be simultaneously structured by different processes that occur at separate spatial
scales: local, landscape, and regional scales defined by spatial extent. Our results illustrate the importance of considering
multiscale influences on patterns of organization in ecological communities.
Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users. 相似文献
10.
11.
We argue that studies at multiple scales must necessarilychange the extent of measurements, not just the spacing, in order toeffectivelycapture information regarding processes at multiple scales. We have implementeda multi-scale sampling scheme using transects of 10 cm, 1m, 10 m, 100 m, and 1 km ateach of four sites along an elevational gradient from dry foothills forest toalpine tundra in the Front Range of Colorado; these four sites form anadditional transect of 22 km. Along each of these transects wetookten equally spaced soil cores and measured variables important in determiningboth microbial and plant community structure: soil water content, organicmattercontent, pH, and total soil biomass. With this sampling scheme we are able totreat scale as an independent variable in our analyses, and our data show thatboth particular sites and particular variables can determine whether estimatesof mean values are scale-dependent or not. A geostatistical analysis using allof our data shows common relationships between scales across ecologicallydiverse sites; biomass shows the most complex pattern of distribution acrossscales, as measured by fractal dimension. Our analyses also reveal theinadequacy of several standard geostatistical models when applied to data frommultiple scales of measurement – we recommend the use of the boundedpowerlaw model in such cases. We hypothesize that because biological communitiesmustrespond simultaneously to multiple variables with differing patterns of spatialvariation, the spatial variation of biological communities will be at least ascomplex as the most complex environmental variable at any given site.This revised version was published online in May 2005 with corrections to the Cover Date. 相似文献
12.
Context
Point based measurements provide only a limited overview of landscape variation in measured properties. Upscaling of measurements from point to landscape comes with challenges particularly considering error propagation.Objectives
We investigated the impact of using proximal derived measurements of soil total carbon taken at point locations on upscaling to landscape levels.Methods
1087 soil samples across Florida, USA were collected, laboratory (LAB) analysed for total carbon (TC), and then measured using visible-/near-infrared (VNIR) spectroscopy. Proximal TC values were generated through chemometric modelling using random forest (RF) and partial least squares (PLS) regression. These three datasets were then upscaled to the State of Florida, USA using ordinary kriging and compared.Results
R2 (RPD) values for the PLS and RF chemometric models were 88% (2.96) and 91% (3.23), respectively. All 3 spatial models had an accuracy of 54% on an independent validation dataset, with greater than 70% accuracy if predicted values were considered within the interpolation variance range. When comparing spatial interpolations derived from the proximally measured samples, only 18% of the PLS versus 51% of the RF fell within a range of 0.05 logTC (g kg?1) of the LAB measured interpolations.Conclusions
Using proximal sampling and modelling provides comparable output to laboratory measured soil TC measurements at point level, but when upscaled to landscape level the selection of proximal modelling method will impact the spatial interpolations derived. The error propagation within sequential modelling must be considered particularly when one wishes to use sequential modelling to analyse change in environmental properties.13.
Analysis of fine-scale spatial pattern of a grassland from remotely-sensed imagery and field collected data 总被引：6，自引：0，他引：6
An important practical problem in the analysis of spatial pattern in ecological systems is that requires spatially-intensive data, with both fine resolution and large extent. Such information is often difficult to obtain from field-measured variables. Digital imagery can offer a valuable, alternative source of information in the analysis of ecological pattern. In the present paper, we use remotely-sensed imagery to provide a link between field-based information and spatially-explicit modeling of ecological processes. We analyzed one digitized color infrared aerial photograph of a serpentine grassland to develop a detailed digital map of land cover categories (31.24 m × 50.04 m of extent and 135 mm of resolution), and an image of vegetation index (proportional to the amount of green biomass cover in the field). We conducted a variogram analysis of the spatial pattern of both field-measured (microtopography, soil depth) and image-derived (land cover map, vegetation index, gopher disturbance) landscape variables, and used a statistical simulation method to produce random realizations of the image of vegetation index based upon our characterization of its spatial structure. The analysis revealed strong relationships in the spatial distribution of the ecological variables (e.g., gopher mounds and perennial grasses are found primarily on deeper soils) and a non-fractal nested spatial pattern in the distribution of green biomass as measured by the vegetation index. The spatial pattern of the vegetation index was composed of three basic components: an exponential trend from 0 m to 4 m, which is related to local ecological processes, a linear trend at broader scales, which is related to a general change in topography across the study site, and a superimposed periodic structure, which is related to the regular spacing of deeper soils within the study site. Simulations of the image of vegetation index confirmed our interpretation of the variograms. The simulations also illustrated the limits of statistical analysis and interpolations based solely on the semivariogram, because they cannot adequately characterize spatial discontinuities. 相似文献
14.
Small-scale effects of historical land use and topography on post-cultural tree species composition in an Alpine valley in southern Switzerland 总被引：1，自引：0，他引：1
Investigations of spatial patterns in forest tree species composition are essential in the understanding of landscape dynamics,
especially in areas of land-use change. The specific environmental factors controlling the present patterns, however, vary
with the scale of observation. In this study we estimated abundance of adult trees and tree regeneration in a Southern Alpine
valley in Ticino, Switzerland. We hypothesized that, at the present scale, spatial pattern of post-cultural tree species does
not primarily depend on topographic features but responds instead to small-scale variation in historical land use. We used
multivariate regression trees to relate species abundances to environmental variables. Species matrices were comprised of
single tree species abundance as well as species groups. Groups were formed according to common ecological species requirements
with respect to shade tolerance, soil moisture and soil nutrients. Though species variance could only be partially explained,
a clear ranking in the relative importance of environmental variables emerged. Tree basal area of formerly cultivated Castanea sativa (Mill.) was the most important factor accounting for up to 50% of species’ variation. Influence of topographic attributes
was minor, restricted to profile curvature, and partly contradictory in response. Our results suggest the importance of biotic
factors and soil properties for small-scale variation in tree species composition and need for further investigations in the
study area on the ecological requirements of tree species in the early growing stage. 相似文献
15.
The degree to which habitat fragmentation affects bird incidence is species specific and may depend on varying spatial scales.
Selecting the correct scale of measurement is essential to appropriately assess the effects of habitat fragmentation on bird
occurrence. Our objective was to determine which spatial scale of landscape measurement best describes the incidence of three
bird species (Pyriglena leucoptera, Xiphorhynchus fuscus and Chiroxiphia caudata) in the fragmented Brazilian Atlantic forest and test if multi-scalar models perform better than single-scalar ones. Bird
incidence was assessed in 80 forest fragments. The surrounding landscape structure was described with four indices measured
at four spatial scales (400-, 600-, 800- and 1,000-m buffers around the sample points). The explanatory power of each scale
in predicting bird incidence was assessed using logistic regression, bootstrapped with 1,000 repetitions. The best results
varied between species (1,000-m radius for P. leucoptera; 800-m for X. fuscus and 600-m for C. caudata), probably due to their distinct feeding habits and foraging strategies. Multi-scale models always resulted in better predictions
than single-scale models, suggesting that different aspects of the landscape structure are related to different ecological
processes influencing bird incidence. In particular, our results suggest that local extinction and (re)colonisation processes
might simultaneously act at different scales. Thus, single-scale models may not be good enough to properly describe complex
pattern–process relationships. Selecting variables at multiple ecologically relevant scales is a reasonable procedure to optimise
the accuracy of species incidence models. 相似文献
16.
Robert L. HopkinsII 《Landscape Ecology》2009,24(7):943-955
The distributions of freshwater mussels are controlled by landscape factors operating at multiple spatial scales. Changes
in land use/land cover (LULC) have been implicated in severe population declines and range contractions of freshwater mussels
across North America. Despite widespread recognition of multiscale influences few studies have addressed these issues when
developing distribution models. Furthermore, most studies have disregarded the role of landscape pattern in regulating aquatic
species distributions, focusing only on landscape composition. In this study, the distribution of Rabbitsfoot (Quadrula cylindrica) in the upper Green River system (Ohio River drainage) is modeled with environmental variables from multiple scales: subcatchment,
riparian buffer, and reach buffer. Four types of landscape environment metrics are used, including: LULC pattern, LULC composition,
soil composition, and geology composition. The study shows that LULC pattern metrics are very useful in modeling the distribution
of Rabbitsfoot. Together with LULC compositional metrics, pattern metrics permit a more detailed analysis of functional linkages
between aquatic species distributions and landscape structure. Moreover, the inclusion of multiple spatial scales is necessary
to accurately model the hierarchical processes in stream systems. Geomorphic features play important roles in regulating species
distributions at intermediate and large scales while LULC variables appear more influential at proximal scales. 相似文献
17.
Jin Yao Debra P. C. Peters Kris M. Havstad Robert P. Gibbens Jeffrey E. Herrick 《Landscape Ecology》2006,21(8):1217-1231
Factors with variation at broad (e.g., climate) and fine scales (e.g., soil texture) that influence local processes at the
plant scale (e.g., competition) have often been used to infer controls on spatial patterns and temporal trends in vegetation.
However, these factors can be insufficient to explain spatial and temporal variation in grass cover for arid and semiarid
grasslands during an extreme drought that promotes woody plant encroachment. Transport of materials among patches may also
be important to this variation. We used long-term cover data (1915–2001) combined with recently collected field data and spatial
databases from a site in the northern Chihuahuan Desert to assess temporal trends in cover and the relative importance of
factors at three scales (plant, patch, landscape unit) in explaining spatial variation in grass cover. We examined cover of
five important grass species from two topographic positions before, during, and after the extreme drought of the 1950s. Our
results show that dynamics before, during, and after the drought varied by species rather than by topographic position. Different
factors were related to cover of each species in each time period. Factors at the landscape unit scale (rainfall, stocking
rate) were related to grass cover in the pre- and post-drought periods whereas only the plant-scale factor of soil texture
was significantly related to cover of two upland species during the drought. Patch-scale factors associated with the redistribution
of water (microtopography) were important for different species in the pre- and post-drought period. Another patch-scale factor,
distance from historic shrub populations, was important to the persistence of the dominant grass in uplands (Bouteloua eriopoda) through time. Our results suggest the importance of local processes during the drought, and transport processes before and
after the drought with different relationships for different species. Disentangling the relative importance of factors at
different spatial scales to spatial patterns and long-term trends in grass cover can provide new insights into the key processes
driving these historic patterns, and can be used to improve forecasts of vegetation change in arid and semiarid areas. 相似文献
18.
Effects of interactive scale-dependent variables on beetle diversity patterns in a semi-arid agricultural landscape 总被引：3，自引：0，他引：3
Understanding species-diversity patterns in heterogeneous landscapes invites comprehensive research on how scale-dependent
processes interact across scales. We used two common beetle families (Tenebrionidae, detrivores; Carabidae, predators) to
conduct such a study in the heterogeneous semi-arid landscape of the Southern Judean Lowland (SJL) of Israel, currently undergoing
intensive fragmentation. Beetles were censused in 25 different-sized patches (500–40,000 m2). We used Fisher’s α and non-parametric extrapolators to estimate species diversity from 11,125 individuals belonging to
56 species. Patch characteristics (plant species diversity and cover, soil cover and degree of stoniness) were measured by
field transects. Spatial variables (patch size, shape, physiognomy and connectivity) and landscape characteristics were analyzed
by GIS and remote-sensing applications. Both patch-scale and landscape-scale variables affected beetle species diversity.
Path-analysis models showed that landscape-scale variables had the strongest effect on carabid diversity in all patches. The
tenebrionids responded differently: both patch-scale and landscape-scale variables affected species diversity in small patches,
while mainly patch-scale variables affected species diversity in large patches. Most of the paths affected species diversity
both directly and indirectly, combining the effects of both patch-scale and landscape-scale variables. These results match
the biology of the two beetle families: Tenebrionidae, the less mobile and more site-attached family, responded to the environment
in a fine-grained manner, while the highly dispersed Carabidae responded to the environment in a coarse-grained manner. We
suggest that understanding abiotic and biotic variable interactions across scales has important consequences for our knowledge
of community structure and species diversity patterns at large spatial scales. 相似文献
19.
To further our understanding of invasive species?? novel distributions, knowledge of invasive species?? relationships with environmental variables at multiple spatial scales is paramount. Here, we investigate which environmental variables and which spatial scales best explain the invasive mute swan??s (Cygnus olor) distribution in southern Ontario (Canada). Specifically we model mute swan distribution changes according to ecologically-relevant spatial scales: average territory size radius, 140?m; median dispersal distance of cygnets, 3,000?m; and average activity distance of males, 8,000?m. For individual spatial scales, global models using variables measured at each particular scale result in the highest Akaike weights, AUC, and Cohen??s Kappa values. Yet composite models (models combining variables measured at different scales) elicit the best models, as determined by higher Akaike weights and high AUC and Cohen??s Kappa values. Overall, percent water, waterbody perimeter density, temperature, precipitation, and road density are positively correlated with mute swan distribution, while percent forest and elevation are negatively correlated at all scales of analysis. Only percent water and annual precipitation are more influential in determining mute swan distribution at the 3,000 and 8,000?m zone scales than the territory scale. While most species distribution models are performed at a single scale, the results of our study suggest that composite models reflecting a species?? ecological needs provide models of better fit with similar, if not better, predictive accuracy. When analyzing species distributions, we also recommend that ecologists consider the scale of the underlying landscape processes and the effect that this may have on their modelling outcomes. 相似文献
20.
Environmental factors at different spatial scales governing soil fauna community patterns in fragmented forests 总被引：1，自引：0，他引：1
Pedro Martins da Silva Matty P. Berg Artur R. M. Serrano Florence Dubs José Paulo Sousa 《Landscape Ecology》2012,27(9):1337-1349
Spatial and temporal changes in community structure of soil organisms may result from a myriad of processes operating at a hierarchy of spatial scales, from small-scale habitat conditions to species movements among patches and large-sale landscape features. To disentangle the relative importance of spatial and environmental factors at different scales (plot, patch and landscape), we analyzed changes in Collembola community structure along a gradient of forest fragmentation, testing predictions of the Hierarchical Patch Dynamics Paradigm (HPDP) in different European biogeographic regions (Boreal, Continental, Atlantic, Mediterranean, Alpine). Using variance partitioning methods, based on partial CCAs, we observed that the independent effect of environmental processes was significantly explaining Collembola community variance in all regions, while the relative effect of spatial variables was not significant, due to the observed high levels of landscape heterogeneity along the gradient. Environmental factors at the patch and plot scales were generally significant and explained the larger part of community changes. Landscape variables were not significant across all study sites. Yet, at the landscape level, an increase in forest habitat and proximity of forest patches were showed to have an indirect influence on local community changes, by influencing microhabitat heterogeneity at lower spatial scales in all studied regions. In line with HPDP, large-scale landscape features influenced spatio-temporal changes in soil fauna communities by constraining small-scale environmental processes. In turn, these provided mechanistic understanding for diversity patterns operating at the patch scale, via shifts in community weighted mean of Collembola life-forms occurring in local communities along the fragmentation gradient. 相似文献