At which scales does landscape structure influence the spatial distribution of elephants in the Western Ghats (India)?

Gaucherel, Cédric; Balasubramanian, M.; Karunakaran, P. V.; Ramesh, B. R.; Muthusankar, G.; Hély, Christelle; Couteron, Pierre

doi:10.1111/j.1469-7998.2009.00652.x

Cited by 10 publications

(7 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…During the past three decades, there were many attempts to elucidate the relationships between spatial pattern, as captured in landscape metrics, and species distributions, with varying levels of success. Recent examples include characterizing the occurrence of avian species (Cushman and McGarigal 2004, Zuckerberg and Porter 2010), avian species richness (Tavernia and Reed 2010), plant community composition (Goslee and Sanderson 2010), and the occurrence of large mammals (Gaucherel et al 2010).…”

mentioning

confidence: 99%

Complex effects of scale on the relationships of landscape pattern versus avian species richness and community structure in a woodland savanna mosaic

Bar‐Massada¹,

Wood²,

Pidgeon³

et al. 2011

Ecography

View full text Add to dashboard Cite

Landscape pattern metrics are widely used for predicting habitat and species diversity. However, the relationship between landscape pattern and species diversity is typically measured at a single spatial scale, even though both landscape pattern, and species occurrence and community composition are scale‐dependent. While the effects of scale on landscape pattern are well documented, the effects of scale on the relationships between spatial pattern and species richness and composition are not well known. Here, our main goal was to quantify the effects of cartographic scale (spatial resolution and extent) on the relationships between spatial pattern and avian richness and community structure in a mosaic of grassland, woodland, and savanna in central Wisconsin. Our secondary goal was to evaluate the effectiveness of a newly developed tool for spatial pattern analysis, multiscale contextual spatial pattern analysis (MCSPA), compared to existing landscape metrics. Landscape metrics and avian species richness had quadratic, exponential, or logarithmic relationships, and these patterns were generally consistent across two spatial resolutions and six spatial extents. However, the magnitude of the relationships was affected by both resolution and extent. At the finer resolution (10‐m), edge density was consistently the best predictor of species richness, followed by an MCSPA metric that measures the standard deviation of woody cover across extents. At the coarser resolution (30‐m), NDVI was the best predictor of species richness by far, regardless of spatial extent. Another MCSPA metric that denotes the average woody cover across extents, together with percent of woody cover, were always the best predictors of variation in avian community structure. Spatial resolution and extent had varying effects on the relationships between spatial pattern and avian community structure. We therefore conclude that cartographic scale not only affects measures of landscape pattern per se, but also the relationships among spatial pattern, species richness, and community structure, often in complex ways, which reduces the efficacy of landscape metrics for predicting the richness and diversity of organisms.

show abstract

mentioning

confidence: 99%

Complex effects of scale on the relationships of landscape pattern versus avian species richness and community structure in a woodland savanna mosaic

Bar‐Massada¹,

Wood²,

Pidgeon³

et al. 2011

Ecography

View full text Add to dashboard Cite

show abstract

“…In particular, both the agroforestry matrix and forest fragments influence the presence of nests, although the scale and direction of the interactions vary across the two land covers and are not uniform across the study zone. This implies that robust multiscale approaches are needed to understand the distribution of social bees in complex landscape (Gaucherel et al., ; Graf et al., ).…”

Section: Discussionmentioning

confidence: 99%

“…It then produces a map of the mean value of the index at successive scales, and thus a distance‐weighted density estimate (Dormann et al., ). This method overcomes the problem of scale sensitivity of local spatial variables such as density or heterogeneity indices (Gaucherel, ; Gaucherel et al., ). Here, we calculated the multiscale density of nests and three landscape metrics: (1) the multiscale density of agroforests; (2) the multiscale density of forest fragments; (3) a multiscale heterogeneity map with five land cover categories.…”

Section: Methodsmentioning

confidence: 99%

Nesting sites of giant honeybees modulated by landscape patterns

Pavageau

Gaucherel

García

et al. 2018

Journal of Applied Ecology

View full text Add to dashboard Cite

The composition of agro‐ecological landscapes is thought to have important implications for the production of major crops through its effects on pollinator abundance and behaviour. We explored the roles of land cover and land cover heterogeneity on bee nest distribution for the giant honeybee Apis dorsata, a key species for coffee pollination, in a complex agroforest landscape. We emphasized scaling and non‐uniform effects by combining two different approaches of spatial analysis, the point‐pattern analysis and surface‐pattern analysis. We found non‐exclusive, positive effects of agroforests, forest fragments and land‐cover heterogeneity on the presence and number of nests. The distribution of nests responded to habitat heterogeneity at small scale (<100 m), forest fragments at medium scale (<300 m) and to agroforest at larger scales (500 m to 2 km). Our multiple approaches highlight that the landscape effects were neither linear nor uniform within the study zone. Nests were consistently located in areas of medium agroforest density or medium to high forest density, but were absent where forest fragments are the most concentrated. The agroforest matrix was particularly important in shaping the size of nest aggregates. Nests tended to be few when there is low tree cover at broad scale, while nests were numerous when agroforest patches are abundant within the bees’ foraging range. Synthesis and applications. Our study revealed that structurally complex landscapes appear to support bee populations. The spatial arrangement of different land covers affected honeybee nest distributions by providing nesting and foraging resources across multiple scales. The results suggest that continued intensification of small forest fragments and expansion of large monospecies plantations will be deleterious to the populations of giant honeybees A. dorsata. Fragmentation of the agroforestry matrix at small scales (100s m) does not, however, appear detrimental for A. dorsata as long as sufficient diversified resources are available at the landscape scale (kms).

show abstract

“…These two statistics give an overall estimation of the accuracy of model projections but do not allow a localisation of model weaknesses [37]. For this reason, we also used the Comparison Map Profile method (CMP; [37,38]) to detect spatial similarity and difference patterns, as well as their spatial resolution, at the European scale using three indices:…”

Section: Methodsmentioning

confidence: 99%

“…These species have been selected as being major components of European’s temperate and boreal forests [36], spanning broad environmental conditions and for which the models’ required data are available. Simulations are compared by determination of their agreement with the species observed distribution and by testing the consistency of simulations using the comparison map profile method (CMP) [37,38]. …”

Section: Introductionmentioning

confidence: 99%

How Can Model Comparison Help Improving Species Distribution Models?

et al. 2013

View full text Add to dashboard Cite

Today, more than ever, robust projections of potential species range shifts are needed to anticipate and mitigate the impacts of climate change on biodiversity and ecosystem services. Such projections are so far provided almost exclusively by correlative species distribution models (correlative SDMs). However, concerns regarding the reliability of their predictive power are growing and several authors call for the development of process-based SDMs. Still, each of these methods presents strengths and weakness which have to be estimated if they are to be reliably used by decision makers. In this study we compare projections of three different SDMs (STASH, LPJ and PHENOFIT) that lie in the continuum between correlative models and process-based models for the current distribution of three major European tree species, Fagus sylvatica L., Quercus robur L. and Pinus sylvestris L. We compare the consistency of the model simulations using an innovative comparison map profile method, integrating local and multi-scale comparisons. The three models simulate relatively accurately the current distribution of the three species. The process-based model performs almost as well as the correlative model, although parameters of the former are not fitted to the observed species distributions. According to our simulations, species range limits are triggered, at the European scale, by establishment and survival through processes primarily related to phenology and resistance to abiotic stress rather than to growth efficiency. The accuracy of projections of the hybrid and process-based model could however be improved by integrating a more realistic representation of the species resistance to water stress for instance, advocating for pursuing efforts to understand and formulate explicitly the impact of climatic conditions and variations on these processes.

show abstract

At which scales does landscape structure influence the spatial distribution of elephants in the Western Ghats (India)?

Cited by 10 publications

References 30 publications

Complex effects of scale on the relationships of landscape pattern versus avian species richness and community structure in a woodland savanna mosaic

Complex effects of scale on the relationships of landscape pattern versus avian species richness and community structure in a woodland savanna mosaic

Nesting sites of giant honeybees modulated by landscape patterns

How Can Model Comparison Help Improving Species Distribution Models?

Contact Info

Product

Resources

About