All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices

Borcard, Daniel; Legendre, Pierre

doi:10.1016/s0304-3800(01)00501-4

Cited by 1,694 publications

(1,454 citation statements)

References 11 publications

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“…We used this correction to avoid a bias in the significance test, given that several tests were performed with the same dataset. When ANOVA residuals showed significant spatial structure, we added spatial filters (Diniz-Filho & Bini 2005) by the principal coordinates of neighbor matrices method (Borcard & Legendre 2002). The use of spatial filters is an interesting strategy for modeling the spatial structure, the filters acting as additional predictors and helping to meet the assumption of independence of the residuals (Diniz-Filho & Bini 2005).…”

Section: Resultsmentioning

confidence: 99%

Tree species composition in areas of Atlantic Forest in southeastern Brazil is consistent with a new system for classifying the vegetation of South America

Eisenlohr

Oliveira‐Filho

2014

Acta Bot. Bras.

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Rigorous and well-defined criteria for the classification of vegetation constitute a prerequisite for effective biodiversity conservation strategies. In 2009, a new classification system was proposed for vegetation types in extra-Andean tropical and subtropical South America. The new system expanded upon the criteria established in the existing Brazilian Institute of Geography and Statistics classification system. Here, we attempted to determine whether the tree species composition of the formations within the Atlantic Forest Biome of Brazil is consistent with this new classification system. We compiled floristic surveys of 394 sites in southeastern Brazil (between 15° and 25°S; and between the Atlantic coast and 55°W). To assess the floristic consistency of the vegetation types, we performed non-metric multidimensional scaling (NMDS) ordination analysis, followed by multifactorial ANOVA. The vegetation types, especially in terms of their thermal regimes, elevational belts and top-tier vegetation categories, were consistently discriminated in the first NMDS axis, and all assessed attributes showed at least one significant difference in the second axis. As was expected on the basis of the theoretical background, we found that tree species composition, in the areas of Atlantic Forest studied, was highly consistent with the new system of classification. Our findings not only help solidify the position of this new classification system but also contribute to expanding the knowledge of the patterns and underlying driving forces of the distribution of vegetation in the region.

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Section: Resultsmentioning

confidence: 99%

Tree species composition in areas of Atlantic Forest in southeastern Brazil is consistent with a new system for classifying the vegetation of South America

Eisenlohr

Oliveira‐Filho

2014

Acta Bot. Bras.

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“…MEM and AEM analyses are recognized as a relevant way to capture the spatial structure in data (Legendre, Borcard, & Peres‐Neto, 2005) while accounting for different scales of spatial dependence (Borcard & Legendre, 2002). However, MEM and AEM analyses sometimes overestimate the importance of spatial variables when the eigenvectors account for random spatial variations (Gilbert & Bennett, 2010).…”

Section: Discussionmentioning

confidence: 99%

“…The Euclidian distances were decomposed into a set of independent spatial variables (db‐MEMs) using a PCA and eigenvector computations. We used a truncation distance of 4 times the largest distance between sites, as advised in Borcard and Legendre (2002). More details on the calculations of db‐MEMs are provided in Appendix S1.…”

Section: Methodsmentioning

confidence: 99%

“…The db‐MEMs and AEMs associated with the largest eigenvalues represent the large‐scale spatial structure in the data, while those associated with smaller eigenvalues reflect finer‐scale variations (Borcard & Legendre, 2002; Dray et al., 2006). The spatial scale represented by each db‐MEM can be broadly estimated using the method described in Figure 3a.…”

Section: Methodsmentioning

confidence: 99%

“…Distance‐based Moran's eigenvector maps (db‐ MEM s) were used to calculate node‐based predictors of geographic isolation. See Borcard and Legendre (2002) for more detailed explanation on the construction of db‐ MEM s. Similarly, asymmetric eigenvector maps ( AEM s) were used to calculate node‐based predictors of larval dispersal; construction of AEM s is detailed in Blanchet et al. (2008a).…”

Section: Introductionmentioning

confidence: 99%

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Geographic isolation and larval dispersal shape seascape genetic patterns differently according to spatial scale

Dalongeville

Andrello

Mouillot

et al. 2018

Evolutionary Applications

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Genetic variation, as a basis of evolutionary change, allows species to adapt and persist in different climates and environments. Yet, a comprehensive assessment of the drivers of genetic variation at different spatial scales is still missing in marine ecosystems. Here, we investigated the influence of environment, geographic isolation, and larval dispersal on the variation in allele frequencies, using an extensive spatial sampling (47 locations) of the striped red mullet (Mullus surmuletus) in the Mediterranean Sea. Univariate multiple regressions were used to test the influence of environment (salinity and temperature), geographic isolation, and larval dispersal on single nucleotide polymorphism (SNP) allele frequencies. We used Moran's eigenvector maps (db‐MEMs) and asymmetric eigenvector maps (AEMs) to decompose geographic and dispersal distances in predictors representing different spatial scales. We found that salinity and temperature had only a weak effect on the variation in allele frequencies. Our results revealed the predominance of geographic isolation to explain variation in allele frequencies at large spatial scale (>1,000 km), while larval dispersal was the major predictor at smaller spatial scale (<1,000 km). Our findings stress the importance of including spatial scales to understand the drivers of spatial genetic variation. We suggest that larval dispersal allows to maintain gene flows at small to intermediate scale, while at broad scale, genetic variation may be mostly shaped by adult mobility, demographic history, or multigenerational stepping‐stone dispersal. These findings bring out important spatial scale considerations to account for in the design of a protected area network that would efficiently enhance protection and persistence capacity of marine species.

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Roadside diversity in relation to age and surrounding source habitat: evidence for long time lags in valuable green infrastructure

Auffret

Lindgren

2020

Ecol Sol and Evidence

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1. The severe and ongoing decline in semi‐natural grassland habitat during the past two centuries means that it is important to consider how other, marginal grassland habitat elements can contribute to landscape‐level biodiversity, and under what circumstances. 2. To examine how habitat age and the amount of core grassland habitat in the surrounding landscape affect diversity in green infrastructure, we carried out inventories of 36 rural road verges that were either historical (pre‐1901) or modern (established post‐1901 and before 1975), and were surrounded by relatively high (>15%) or low (<5%) levels of grassland habitat. We recorded the number of plant species, grassland specialists, grassland conservation species and the fraction of the landscape's species and specialists found in the road verge. 3. Road verge communities were characterised by high levels of grassland specialist species (35% of the 161 species recorded), with road verge sites supporting 15–20% of the specialist species found in the surrounding 25 km2 landscape. 4. Richness of species and specialists were more closely related to road age than to the amount of surrounding habitat. Higher diversity in historical roads, despite the majority of modern roads being at least 60 years old, suggests a long time lag in the establishment of grassland communities in marginal grassland habitats. We identified no effect of historical surrounding land use on present day diversity in road verges. 5. Road verge richness was not affected by the amount of surrounding grassland. This could be due to the relatively low amounts of grassland remaining in all landscapes, together with dispersal limitation commonly found in grassland plant communities contributing to a potential time lag. 6. We identified road verges as potentially very important habitats for grassland communities. Because of the high levels of grassland specialists present, these and other marginal grasslands and grassland green infrastructure should be explicitly considered in landscape‐scale conservation management. Practitioners looking to identify the most species‐rich road verges should aim to find the oldest possible, while long time lags in community assembly suggests that seed sowing could be appropriate to enhance roadside diversity, even in decades‐old road verges.

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All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices

Cited by 1,694 publications

References 11 publications

Tree species composition in areas of Atlantic Forest in southeastern Brazil is consistent with a new system for classifying the vegetation of South America

Tree species composition in areas of Atlantic Forest in southeastern Brazil is consistent with a new system for classifying the vegetation of South America

Geographic isolation and larval dispersal shape seascape genetic patterns differently according to spatial scale

Roadside diversity in relation to age and surrounding source habitat: evidence for long time lags in valuable green infrastructure

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