Spatial versus temporal variation in precipitation in a semiarid ecosystem

Spatial and temporal variations in precipitation are central features of semiarid ecosystems, influencing patterns of plant productivity and the distribution of native fauna. Although temporal variation in precipitation has been studied extensively, far less is known about the spatial scale and pattern of precipitation variability in semiarid regions. I used long-term precipitation records to examine spatial variation across the 63 km² Central Plains Experimental Range in northeastern Colorado, and across the 117,000 km² region of shortgrass steppe in eastern Colorado. Relative to temporal variation, spatial variation was low at scales <10 km, increased linearly across scales of 40–120 km, and was nearly equal in magnitude to temporal variation across distances of 120–160 km. Although I hypothesized that most spatial variation would be generated by early-summer convective thunderstorms in June, I found that the magnitude and spatial pattern of variation was similar for precipitation received in June compared to cumulative precipitation received during the full growing season. The degree of spatial autocorrelation in precipitation across all distances that I evaluated was similar for drought, dry, above-average and wet years. Across distances of 10–120 km, spatial variation within a single growing season was approximately two times greater than spatial variation in long-term mean growing-season precipitation, indicating spatial shifting in the locations of patches of high and low precipitation over multiple years. Overall, these findings suggest spatial variation at scales of 10–160 km may have been an important factor influencing vegetation patterns and migratory fauna of the shortgrass steppe, and have implications for livestock producers and future assessments of climate change.     

Response of an aridland ecosystem to interannual climate variability and prolonged drought

Water is a key driver of ecosystem processes in aridland ecosystems. Thus, changes in climate could have significant impacts on ecosystem structure and function. In the southwestern US, interactions among regional climate drivers (e.g., El Niño Southern Oscillation) and topographically controlled convective storms create a spatially and temporally variable precipitation regime that governs the rate and magnitude of ecosystem processes. We quantified the spatial and temporal distribution of reduced grassland greenness in response to seasonal and annual variation in precipitation at two scales at the Sevilleta Long Term Ecological Research site in central New Mexico, using Normalized Difference Vegetation Index (NDVI) values from bi-weekly AVHRR data and seasonal ETM data from 1989 to 2005. We used spatially explicit NDVI Z-scores to identify times and places of significantly reduced greenness and related those to interactions between plant functional type, seasonal climate variation, and topography. Seasonal greenness was bimodal with a small peak in spring and a stronger peak following the summer monsoon. Greenness was generally spatially homogeneous in spring and more spatially variable in summer. From 2001 through spring 2002, drought effects were evidenced by a 4-fold increase in the number of pixels showing significantly low greenness. Spatial distribution of low greenness was initially modulated by topographic position, but as the drought intensified spread throughout the study area. Vegetation green up occurred rapidly when drought conditions ceased. We conclude that drought effects vary spatially over time, pervasive drought reduces broad-scale spatial heterogeneity, and greenness patterns recover rapidly when drought conditions end.     

Climatic and topographic controls on patterns of fire in the southern and central Appalachian Mountains,USA

Climate and topography are two important controls on spatial patterns of fire disturbance in forests globally, via their influence on fuel moisture and fuel production. To assess the influences of climate and topography on fire disturbance patterns in a temperate forest region, we analyzed the mapped perimeters of fires that burned during 1930–2003 in two national parks in the eastern United States. These were Great Smoky Mountains National Park (GSMNP) in the southern Appalachian Mountains and Shenandoah National Park (SNP) in the central Appalachian Mountains. We conducted GIS analyses to assess trends in area burned under differing climatic conditions and across topographic gradients (elevation, slope position, and aspect). We developed a Classification and Regression Tree model in order to further explore the interactions between topography, climate, and fire. The results demonstrate that climate is a strong driver of both spatial and temporal patterns of wildfire. Fire was most prevalent in the drier SNP than the wetter GSMNP, and during drought years in both parks. Topography also influenced fire occurrence, with relatively dry south-facing aspects, ridges, and lower elevations burning most frequently. However, the strength of topographic trends varied according to the climatic context. Weaker topographic trends emerged in the drier SNP than GSMNP, and during low-PDSI (dry) years than high-PDSI (wet) years in both parks. The apparent influence of climate on the spatial patterning of fire suggests a more general concept, that disturbance-prone landscapes exhibit weaker fine-scale spatial patterning of disturbance than do less disturbance-prone landscapes.     

Plant and animal diversity in a region of the Southern Alps: the role of environmental and spatial processes

Different organisms respond to landscape configuration and spatial structure in different terms and across different spatial scales. Here, regression models with variation partitioning were applied to determine relative influence of the three groups of variables (climate, land use and environmental heterogeneity) and spatial structure variables on plant, bird, orthopteran and butterfly species richness in a region of the Southern Alps, ranging in elevation from the sea level to 2,780 m. Grassland and forest cover were positively correlated with species richness in both taxonomic groups, whilst species richness decreased with increasing urban elements and arable land. The variation was mainly explained by the shared component between the three groups in plants and between landscape and environmental heterogeneity in birds. The variation was related to independent land use effect in insects. The distribution in species richness was spatially structured for plants, birds and orthopterans, whilst in butterflies, no spatial structure was detected. Plant richness was associated with linear trend variation and broad-scale spatial structure in the northern part of the region, whilst bird richness with broad-scale variation which occurs on the external Alpine ridge. Orthopteran diversity was strongly related to fine-scale spatial structure, generated by dynamic processes or by unmeasured spatially structured abiotic factors. Although the study was carried out in relatively small area, the four taxonomic groups seem to respond to biodiversity drivers in a surprisingly different way. This has considerable implications for conservation planning as it restricts the usefulness of simple indicators in prioritizing areas for conservation purposes.     

Influence of landscape structure and stand age on species density and biomass of a tropical dry forest across spatial scales

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.     

Plant-pest interactions in time and space: A Douglas-fir bark beetle outbreak as a case study

A conceptual model of Douglas-fir bark beetle (Dendroctonus pseudotsugae) dynamics and associated host tree mortality across multiple spatial and temporal scales was developed, then used to guide a study of the association between the occurrence of beetle- killed trees and factors that might render trees more susceptible to attack. Long-term records of beetle kill showed that beetle epidemics were associated with windstorms and drought at statewide and local spatial scales. At the landscape scale, beetle kill was associated with (i) portions of the landscape that were potentially drier (southern aspects, lower elevations) and (ii) portions of the landscape that had more mature and old-growth conifer vegetation. The patches of beetle-killed trees were aggregated with respect to other patches at scales of approximately 1 and 4 km. At the scale of the individual tree, there was not a strong relationship between beetle kill and resistance to attack measured by tree growth rate prior to attack. Our results show that landscape-scale phenomena and temporal patterns were more strongly correlated with beetle-kill events than was recent growth history at the scale of individual trees. We suggest that the multi-scale approach we employed is useful for elucidating the relative roles of fine- versus coarse-scale constraints on ecological processes.     

Escaping the flames: large termitaria as refugia from fire in miombo woodland

At finer scales, spatial heterogeneity can influence fire intensity and severity. To test whether Macrotermes termite mounds act as fire refugia for woody plants, we assessed effects of fire on individual plants, woody plant structure and composition in a miombo woodland in Zimbabwe, where elephants have decreased tree cover, leading to increased grass cover, fuelling greater intensity fires. We compared exposure to fire on 47 paired mound-matrix plots at three sites. Mound-based woody plants were less exposed to fire than those in matrix positions. Woody species composition differed between mound and matrix, and there were more tall trees on mounds. We assessed grass cover, elephant damage, fire damage and resprouting response for all woody plants found on 10 paired mound-matrix plots that had been equally exposed to severe late dry season fires. Grass cover was three times greater for matrix sites, where 85 % of woody species experienced heavy fire damage, compared to 29 % for mounds. Matrix species were nearly 31 times more likely than mound species to exhibit a vigorous resprouting response after fire damage, all else being equal. The distinct composition of termitaria vegetation has been attributed to edaphic factors. To this should be added the fire-retardant properties of mounds, allowing woody species that might otherwise have been excluded, to persist in a fire-prone system. Thus, spatial pattern created by termitaria is reinforced through exclusion of fire, allowing different species composition and structure. Since termitaria are important for productivity and biodiversity, the refuge effect is significant for the system.     

Spatial scale influence on longterm temporal patterns of a semi-arid grassland

Longterm (45 years) temporal data were used to assess the influence of spatial scale on temporal patterns of a semi-arid west Texas grassland. Temporal basal area dynamics of common curlymesquite (Hilaria belangeri (Steud.) Nash) collected from permanent plots within two areas that were released from disturbance (longterm overgrazing and drought), were evaluated at two spatial scales (quadrat, site). Wiens (1989) proposed hypotheses to characterize the influence of scale on variability, predictability, and equilibrium. These hypotheses were tested for this grassland and temporal patterns observed were different for each spatial scale. The large scale (site) was characterized by low variation between units, high variation within units, high potential predictability, and possible movement toward a fluctuating but relatively stable or equilibrial state. At the small scale (quadrat), variation between units was high, predictability low, and there was no indication of movement toward a stable state; chaotic behavior may be expressed at this scale although the length of the temporal record may not be sufficient to evaluate this phenomenon.     

Climatic, landform, microtopographic, and overstory canopy controls of tree invasion in a subalpine meadow landscape, Oregon Cascades, USA

Tree invasions have been documented throughout Northern Hemisphere high elevation meadows, as well as globally in many grass and forb-dominated ecosystems. Tree invasions are often associated with large-scale changes in climate or disturbance regimes, but are fundamentally driven by regeneration processes influenced by interactions between climatic, topographic, and biotic factors at multiple spatial scales. The purpose of this research was to quantify spatiotemporal patterns of meadow invasion; and how climate, larger landforms, topography, and overstory trees have interactively influenced tree invasion. We combined airborne Light Detection and Ranging (LiDAR) characterizations of landforms, topography, and overstory vegetation with historical climate, field measurements of snow depth, tree abundance, and tree ages to reconstruct spatial and temporal patterns of tree invasion over five decades in a subalpine meadow complex in the Oregon Cascade Range, USA. Proportion of meadow occupied by trees increased from 8?% in 1950 to 35?% in 2007. Larger landforms, topography, and tree canopies interactively mediated regional climatic controls of tree invasion by modifying depth and persistence of snow pack, while tree canopies also influenced seed source availability. Landscape context played an important role mediating snow depth and tree invasion; on glacial landforms tree invasion was negatively associated with spring snowfall, but on debris flows tree invasion was not associated with snow fall. The importance of snow, uncertain climate change impacts on snow, and mediation of snow by interacting and context dependent factors in complex mountain terrain poses substantial hurdles for understanding how these ecotones may respond to future climate conditions.     

Hierarchical relationships between landscape structure and temperature in a managed forest landscape

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.     

What multiscale environmental drivers can best be discriminated from a habitat index derived from a remotely sensed vegetation time series?

Understanding which environmental conditions are critical for species survival is a critical, ongoing question in ecology. These conditions can range from climate, at the broadest scale, through to elevation and other local landscape conditions, to fine scale landscape patterns of land cover and use. Remote sensing is an ideal technology to monitor and assess changes in these environmental conditions at a variety of spatial and temporal scales, with many studies focusing on the physiological state of vegetation derived from time series of satellite measurements. As vegetation occurs within specific climatic zones, over certain soil, terrain, and land cover types, it can be difficult to decipher the influence of the underlying role of climate, topography, soil, and land cover on the observed vegetation signal. In this article, we specifically addressed this problem by asking the question: what is the relative impact and importance of these different scales of environmental drivers on the temporal and spatial patterns observed on a habitat index derived from remotely sensed data? To find the solution, we utilized a SPOT VEGETATION-normalized difference vegetation index time series of Europe to create a remote-sensing-derived habitat index, which incorporates aspects of productivity, seasonality, and cover. We then compared the observed temporal and spatial variations in the index to a pan-Europe terrestrial classification system, which explicitly incorporates variations in climate, terrain, soil parent material, land cover, and use. Results indicated that the most accurate level of discrimination from the habitat index was at the broadest level of the hierarchy, climate, while the poorest degree of discrimination was associated with elevation. In terms of similarity on the index across time and space, we found that arable and forest cover classes were more similar across elevation and parent materials than across other land cover types within them. Analyzing the remote-sensing index, at multiple scales, provides significant insights into the drivers of satellite-derived greenness indices, as well as highlights the benefit and cautions associated with linking satellite-derived indirect indicators to species distribution modeling and biodiversity.     

Use of landscape pattern metrics and multiscale data in aquatic species distribution models: a case study of a freshwater mussel

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.     

Associations of Bird Species Richness and Community Composition with Local and Landscape-scale Environmental Factors in Borneo

A comprehensive understanding of variables associated with spatial differences in community composition is essential to explain and predict biodiversity over landscape scales. In this study, spatial patterns of bird diversity in Central Kalimantan, Indonesia, were examined and associated with local-scale (habitat structure and heterogeneity) and landscape-scale (logging, slope position and elevation) environmental variables. Within the study area (c. 196 km²) local habitat structure and heterogeneity varied considerably, largely due to logging. In total 9747 individuals of 177 bird species were recorded. Akaike's information criterion (AIC) revealed that the best explanatory models of bird community similarity and species richness included both local- and landscape-scale environmental variables. Important local-scale variables included liana abundance, fern cover, sapling density, tree density, dead wood abundance and tree architecture, while important landscape-scale variables were elevation, logging and slope position. Geographic distance between sampling sites was not significantly associated with spatial variation in either species richness or similarity. These results indicate that deterministic environmental processes, as opposed to dispersal-driven stochastic processes, primarily structure bird assemblages within the spatial scale of this study and confirm that highly variable local habitat measures can be effective means of predicting landscape-scale community patterns.     

Environmental factors at different spatial scales governing soil fauna community patterns in fragmented forests

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.     

Ecosystem-scale spatial heterogeneity of stable isotopes of soil nitrogen in African savannas

Soil ¹⁵N is a natural tracer of nitrogen (N) cycling. Its spatial distribution is a good indicator of processes that are critical to N cycling and of their controlling factors integrated both in time and space. The spatial distribution of soil δ¹⁵N and its underlying drivers at sub-kilometer scales are rarely investigated. This study utilizes two sites (dry vs. wet) from a megatransect in southern Africa encompassing locations with similar soil substrate but different rainfall and vegetation, to explore the effects of soil moisture and vegetation distribution on ecosystem-scale patterns of soil δ¹⁵N. A 300-m long transect was set up at each site and surface soil samples were randomly collected for analyses of δ¹⁵N, %N and nitrate content. At each soil sampling location the presence of grasses, woody plants, Acacia species (potential N fixer) as well as soil moisture levels were recorded. A spatial pattern of soil δ¹⁵N existed at the dry site, but not at the wet site. Woody cover distribution determined the soil δ¹⁵N spatial pattern at ecosystem-scale; however, the two Acacia species did not contribute to the spatial pattern of soil δ¹⁵N. Grass cover was negatively correlated with soil δ¹⁵N at both sites owing to the lower foliar δ¹⁵N values of grasses. Soil moisture did not play a role in the spatial pattern of soil δ¹⁵N at either site. These results suggest that vegetation distribution, directly, and water availability, indirectly, affect the spatial patterns of soil δ¹⁵N through their effects on woody plant and grass distributions.     

Multi-scale use of lands providing anthropogenic resources by American Crows in an urbanizing landscape

The conversion of forests and farmlands to human settlements has negative impacts on many native species, but also provides resources that some species are able to exploit. American Crows (Corvus brachyrhynchos), one such exploiter, create concern due to their impact as nest predators, disease hosts, and cultural harbingers of evil. We used various measures of crow abundance and resource use to determine crows’ response to features of anthropogenic landscapes in the Puget Sound region of the United States. We examined land cover and land use composition at three spatial scales: study sites (up to 208 ha), crow home ranges within sites (18.1 ha), and local land cover (400 m²). At the study site and within-site scales crow abundance was strongly correlated with land cover providing anthropogenic resources. In particular, crows were associated with the amount of ‘maintained forest’ cover, and were more likely to use grass and shrub cover than forest or bare soil cover. Although crows did not show a generalized response to an edge variable, they exhibited greater use of patchy habitat created by human settlements than of native forests. Radio-tagged territorial adults used resources within their home ranges relatively evenly, suggesting resource selection had occurred at a larger spatial scale. The land conversion pattern of new suburban and exurban settlements creates the mix of impervious surfaces and maintained vegetation that crows use, and in our study area crow populations are expected to continue to increase. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Broad-scale heterogeneity influences nest selection by Brown-headed Cowbirds

Increasing habitat heterogeneity is widely considered to improve conditions for biodiversity. Yet benefits for native species depend on scale and the effect of heterogeneity on key processes influencing survival and reproduction. We examined the relationship between habitat heterogeneity and brood parasitism at multiple scales in a region characterized by (1) relatively high cowbird abundance, (2) high abundance of our focal species, the grassland obligate Grasshopper Sparrow (Ammodramus savannarum), (3) variation in the structure and composition of grassland habitats, and (4) a gradient of woodland cover in the landscape matrix. Tree cover at broad scales was found to have the greatest impact on parasitism while factors at finer scales were relatively unimportant. We found that for every 1 % increase in tree cover within 1 km of Grasshopper Sparrow nests, the probability of parasitism decreases by 3 %. Parasitism reduced clutch sizes and the number of Grasshopper Sparrows fledged, but survival rates were similar between non-parasitized and parasitized nests. Furthermore, simple population projection models indicated that parasitism has the greatest impact at moderate survival levels and can inhibit the resiliency of this population. Our results support the hypothesis that cowbirds prefer forest hosts, which may reduce parasitism rates on grassland birds in heterogeneous landscapes. Collectively, our findings suggest that the effect of cowbird parasitism may be greater for Grasshopper Sparrows than was previously thought.     

Spatial Patterns in European Rabbit Abundance After a Population Collapse

Assessing the associations between spatial patterns in population abundance and environmental heterogeneity is critical for understanding various population processes and for managing species and communities. This study evaluates responses in the abundance of the European rabbit (Oryctolagus cuniculus), an important prey for predators of conservation concern in Mediterranean ecosystems, to environmental heterogeneity at different spatial scales. Multi-scale habitat models of rabbit abundance in three areas of Doñana, south-western Spain, were developed using a spatially extensive dataset of faecal pellet counts as an abundance index. The best models included habitat variables at the three spatial scales examined: distance from lagoons (broad scale), mean landscape shrub coverage and interspersion of pastures (home-range scale), and shrub and pasture cover (microhabitat scale). These variables may well have been related to the availability of food and refuge for the species at the different scales. However, the models’ fit to data and their predictive accuracy for an independent sample varied among the study regions. Accurate predictions in some areas showed that the combination of variables at various spatial scales can provide a reliable method for assessing the abundance of ecologically complex species such as the European rabbit over large areas. On the other hand, the models failed to identify abundance patterns in a population that suffered the strongest demographic collapse after viral epidemics, underlining the difficulty of generalizing this approach. In the latter case, factors difficult to implement in static models such as disease history and prevalence, predator regulation and others may underlie the lack of association. Habitat models can provide useful guidelines for the management of landscape attributes relevant to rabbits and help improve the conservation of Mediterranean communities. However, other influential factors not obviously related to environmental heterogeneity should also be analyzed in more detail.