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Large Spatial Extent (large + spatial_extent)
Selected AbstractsSpatial scale affects bioclimate model projections of climate change impacts on mountain plantsGLOBAL CHANGE BIOLOGY, Issue 5 2008MANDAR R. TRIVEDI Abstract Plant species have responded to recent increases in global temperatures by shifting their geographical ranges poleward and to higher altitudes. Bioclimate models project future range contractions of montane species as suitable climate space shifts uphill. The species,climate relationships underlying such models are calibrated using data at either ,macro' scales (coarse resolution, e.g. 50 km × 50 km, and large spatial extent) or ,local' scales (fine resolution, e.g. 50 m × 50 m, and small spatial extent), but the two approaches have not been compared. This study projected macro (European) and local models for vascular plants at a mountain range in Scotland, UK, under low (+1.7 °C) and high (+3.3 °C) climate change scenarios for the 2080s. Depending on scenario, the local models projected that seven or eight out of 10 focal montane species would lose all suitable climate space at the site. However, the European models projected such a loss for only one species. The cause of this divergence was investigated by cross-scale comparisons of estimated temperatures at montane species' warm range edges. The results indicate that European models overestimated species' thermal tolerances because the input coarse resolution climate data were biased against the cold, high-altitude habitats of montane plants. Although tests at other mountain ranges are required, these results indicate that recent large-scale modelling studies may have overestimated montane species' ability to cope with increasing temperatures, thereby underestimating the potential impacts of climate change. Furthermore, the results suggest that montane species persistence in microclimatic refugia might not be as widespread as previously speculated. [source] Using habitat distribution models to evaluate large-scale landscape priorities for spatially dynamic speciesJOURNAL OF APPLIED ECOLOGY, Issue 1 2008Regan Early Summary 1Large-scale conservation planning requires the identification of priority areas in which species have a high likelihood of long-term persistence. This typically requires high spatial resolution data on species and their habitat. Such data are rarely available at a large geographical scale, so distribution modelling is often required to identify the locations of priority areas. However, distribution modelling may be difficult when a species is either not recorded, or not present, at many of the locations that are actually suitable for it. This is an inherent problem for species that exhibit metapopulation dynamics. 2Rather than basing species distribution models on species locations, we investigated the consequences of predicting the distribution of suitable habitat, and thus inferring species presence/absence. We used habitat surveys to define a vegetation category which is suitable for a threatened species that has spatially dynamic populations (the butterfly Euphydryas aurinia), and used this as the response variable in distribution models. Thus, we developed a practical strategy to obtain high resolution (1 ha) large scale conservation solutions for E. aurinia in Wales, UK. 3Habitat-based distribution models had high discriminatory power. They could generalize over a large spatial extent and on average predicted 86% of the current distribution of E. aurinia in Wales. Models based on species locations had lower discriminatory power and were poorer at generalizing throughout Wales. 4Surfaces depicting the connectivity of each grid cell were calculated for the predicted distribution of E. aurinia habitat. Connectivity surfaces provided a distance-weighted measure of the concentration of habitat in the surrounding landscape, and helped identify areas where the persistence of E. aurinia populations is expected to be highest. These identified successfully known areas of high conservation priority for E. aurinia. These connectivity surfaces allow conservation planning to take into account long-term spatial population dynamics, which would be impossible without being able to predict the species' distribution over a large spatial extent. 5Synthesis and applications. Where species location data are unsuitable for building high resolution predictive habitat distribution models, habitat data of sufficient quality can be easier to collect. We show that they can perform as well as or better than species data as a response variable. When coupled with a technique to translate distribution model predictions into landscape priority (such as connectivity calculations), we believe this approach will be a powerful tool for large-scale conservation planning. [source] Using GIS to relate small mammal abundance and landscape structure at multiple spatial extents: the northern flying squirrel in Alberta, CanadaJOURNAL OF APPLIED ECOLOGY, Issue 3 2005MATTHEW WHEATLEY Summary 1It is common practice to evaluate the potential effects of management scenarios on animal populations using geographical information systems (GIS) that relate proximate landscape structure or general habitat types to indices of animal abundance. Implicit in this approach is that the animal population responds to landscape features at the spatial grain and extent represented in available digital map inventories. 2The northern flying squirrel Glaucomys sabrinus is of particular interest in North American forest management because it is known from the Pacific North-West as a habitat specialist, a keystone species of old-growth coniferous forest and an important disperser of hypogeous, mycorrhizal fungal spores. Using a GIS approach we tested whether the relative abundance of flying squirrel in northern Alberta, Canada, is related to old forest, conifer forest and relevant landscape features as quantified from management-based digital forest inventories. 3We related squirrel abundance, estimated through live trapping, to habitat type (forest composition: conifer, mixed-wood and deciduous) and landscape structure (stand height, stand age, stand heterogeneity and anthropogenic disturbance) at three spatial extents (50 m, 150 m and 300 m) around each site. 4Relative abundances of northern flying squirrel populations in northern and western Alberta were similar to those previously reported from other regions of North America. Capture rates were variable among sites, but showed no trends with respect to year or provincial natural region (foothills vs. boreal). 5Average flying squirrel abundance was similar in all habitats, with increased values within mixed-wood stands at large spatial extents (300 m) and within deciduous-dominated stands at smaller spatial extents (50 m). No relationship was found between squirrel abundance and conifer composition or stand age at any spatial extent. 6None of the landscape variables calculated from GIS forest inventories predicted squirrel abundance at the 50-m or 150-m spatial extents. However, at the 300-m spatial extent we found a negative, significant relationship between average stand height and squirrel abundance. 7Synthesis and applications. Boreal and foothill populations of northern flying squirrel in Canada appear unrelated to landscape composition at the relatively large spatial resolutions characteristic of resource inventory data commonly used for management and planning in these regions. Flying squirrel populations do not appear clearly associated with old-aged or conifer forests; rather, they appear as habitat generalists. This study suggests that northern, interior populations of northern flying squirrel are probably more related to stand-level components of forest structure, such as food, microclimate (e.g. moisture) and understorey complexity, variables not commonly available in large-scale digital map inventories. We conclude that the available digital habitat data potentially exclude relevant, spatially dependent information and could be used inappropriately for predicting the abundance of some species in management decision making. [source] Modeling landscape patterns of understory tree regeneration in the Pacific Northwest, USAAPPLIED VEGETATION SCIENCE, Issue 2 2001Michael C. Wimberly Abstract. Vegetation maps serve as the basis for spatial analysis of forest ecosystems and provide initial information for simulations of forest landscape change. Because of the limitations of current remote sensing technology, it is not possible to directly measure forest understory attributes across large spatial extents. Instead we used a predictive vegetation mapping approach to model Tsuga heterophylla and Picea sitchensis seedling patterns in a 3900-ha landscape in the Oregon Coast Range, USA, as a function of Landsat TM imagery, aerial photographs, digital elevation models, and stream maps. Because the models explained only moderate amounts of variability (R2 values of 0.24,0.56), we interpreted the predicted patterns as qualitative spatial trends rather than precise maps. P. sitchensis seedling patterns were tightly linked to the riparian network, with highest densities in coastal riparian areas. T. heterophylla seedlings exhibited complex patterns related to topography and overstory forest cover, and were also spatially clustered around patches of old-growth forest. We hypothesize that the old growth served as refugia for this fire-sensitive species following wildfires in the late 19th and early 20th centuries. Low levels of T. heterophylla regeneration in hardwood-dominated forests suggest that these patches may succeed to shrublands rather than to conifer forest. Predictive models of seedling patterns could be developed for other landscapes where georeferenced inventory plots, remote sensing data, digital elevation models, and climate maps are available. [source] | ||||||||||