D. Borcard

Nature and Landscape Conservation · 2002–2018

A researcher in the Science corpus: 8 papers; trusts 17 researchers and is trusted by 121 researchers here, as inferred from the citation graph.

Subfields

• Nature and Landscape Conservation — 27 citations into it; #471 of 6,941 by trust here, #721 by citations
• Ecology, Evolution, Behavior and Systematics — 13 citations into it; #338 of 6,648 by trust here, #547 by citations
• Ecological Modeling — 11 citations into it; #176 of 2,530 by trust here, #307 by citations
• Statistics and Probability — 11 citations into it; #6,183 of 12,932 by trust here, #2,477 by citations
• Ecology — 10 citations into it
• Economics and Econometrics — 8 citations into it; #1,032 of 23,481 by trust here, #3,156 by citations
• Global and Planetary Change — 7 citations into it; #77 of 10,225 by trust here, #962 by citations
• Food Science — 5 citations into it; #458 of 1,700 by trust here, #325 by citations

Whom D. Borcard trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Pierre Legendre
2. Calyampudi R. Rao
3. P. Peres‐Neto
4. Stéphane Dray
5. K. Ohtani
6. Selçuk Korkmaz
7. R. Telford
8. Jari Oksanen
9. Gilles Guillot
10. M. de Cáceres

Who trusts D. Borcard overall

1. Pierre Legendre
2. Stéphane Dray
3. Daniel A. Griffith
4. Daniel García
5. J. Diniz-Filho
6. B. Gilbert
7. Marie-Josée Fortin
8. J. Heino
9. P. Peres‐Neto
10. J. Alahuhta

Papers from D. Borcard's perspective

Ordered by how strongly the researchers D. Borcard trusts endorse each paper. Same corpus, a different order for every researcher.

1. All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices
2. Variation partitioning of species data matrices: estimation and comparison of fractions. (Ecology)
3. Spatial modelling: a comprehensive framework for principal coordinate analysis of neighbour matrices (PCNM)
4. Identifying spatial relationships at multiple scales: principal coordinates of neighbour matrices (PCNM) and geostatistical approaches
5. DISSECTING THE SPATIAL STRUCTURE OF ECOLOGICAL DATA AT MULTIPLE SCALES
6. Gene Flow in Complex Landscapes: Testing Multiple Hypotheses with Causal Modeling (American Naturalist)
7. Estimating and controlling for spatial structure in the study of ecological communities
8. Dismantling the Mantel tests
9. The Design of Experiments
10. GIVING MEANINGFUL INTERPRETATION TO ORDINATION AXES: ASSESSING LOADING SIGNIFICANCE IN PRINCIPAL COMPONENT ANALYSIS

Their papers

• All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices (2002) — 1,925 citations
• Forward selection of explanatory variables. (2008) — 2,034 citations
• Should the Mantel test be used in spatial analysis? (2015) — 351 citations
• Box–Cox‐chord transformations for community composition data prior to beta diversity analysis (2018) — 93 citations
• Numerical Ecology with R (2011) — 3,279 citations
• Variation partitioning of species data matrices: estimation and comparison of fractions. (2006) — 2,233 citations
• ANALYZING BETA DIVERSITY: PARTITIONING THE SPATIAL VARIATION OF COMMUNITY COMPOSITION DATA (2005) — 1,291 citations
• DISSECTING THE SPATIAL STRUCTURE OF ECOLOGICAL DATA AT MULTIPLE SCALES (2004) — 940 citations