Martín-Queller, E. (corresponding author, firstname.lastname@example.org) & Gil-Tena, A. (email@example.com): Departament d'Enginyeria Agroforestal, ETSEA, Universitat de Lleida, Av. Alcalde Rovira Roure 191, 25198 Lleida, Spain Centre Tecnològic Forestal de Catalunya, Crta. Sant Llorenç de Morunys, km 2, 25280 Solsona, Spain. Saura, S. (firstname.lastname@example.org): Departamento de Economía y Gestión Forestal, ETSI Montes, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid, Spain.
Species richness of woody plants in the landscapes of Central Spain: the role of management disturbances, environment and non-stationarity
Article first published online: 16 DEC 2010
© 2010 International Association for Vegetation Science
Journal of Vegetation Science
Volume 22, Issue 2, pages 238–250, April 2011
How to Cite
Martín-Queller, E., Gil-Tena, A. and Saura, S. (2011), Species richness of woody plants in the landscapes of Central Spain: the role of management disturbances, environment and non-stationarity. Journal of Vegetation Science, 22: 238–250. doi: 10.1111/j.1654-1103.2010.01242.x
Co-ordinating Editor: Alessandro Chiarucci
- Issue published online: 2 MAR 2011
- Article first published online: 16 DEC 2010
- Received 11 December 2009, Accepted 8 November 2010.
- Climatic gradients;
- Gamma species richness;
- Geographically weighted regression;
- Intermediate disturbance hypothesis;
- Rural abandonment;
- Silvicultural treatments;
- Spatial scale
Questions: How important is management disturbance on gamma species richness of woody plants at intermediate landscape scales? How is species richness related to other climatic and biotic factors in the study area? How does the assumption of spatial stationarity affect assessment of relationships among species richness and explanatory variables (e.g. management, biotic and climatic factors) across extensive study areas?
Location: Central Spain (regions of Castilla y León, Madrid and Castilla-La Mancha).
Scale: Extent: 150 000 km2. Grain: 25 km2 (5 × 5-km cells).
Methods: Information from 21 064 plots from the 3SNFI was used to evaluate richness of tree and shrub species at intermediate landscape scales. In addition to variables well known to explain biodiversity, e.g. environmental and biotic factors, effect of management treatments was evaluated by assessing clearcutting, selection cutting, stand improvement treatments and agrosilvopastoral systems (dehesas). Results from GWR techniques were compared with those from OLS regression.
Results: Patterns of gamma species richness, although strongly affected by both environmental and biotic variables, were also significantly modified by management factors. Species richness increased with percentage of selection cutting stands and improvement treatments but decreased with percentage of clearcutting stands. Reduced species richness of woody plants was associated with agrosilvopastoral practices. Species richness for trees was closely related to basal area, annual precipitation and topographic complexity; species richness for shrubs was closely related to topographic complexity and agrosilvopastoral systems. Most relationships between species richness and environmental or biotic factors were non-stationary. Relationships between species richness and management effects tended to be stationary, with a few exceptions.
Conclusions: Landscape models of biodiversity in Central Spain were more informative when they accounted for effects of management practices, at least at intermediate scales. In the context of current rural abandonment, silvicultural disturbances of intermediate intensity increased gamma species richness of woody plants. Exclusion of factors such as agrosilvopastoral systems from models could have led to spurious relationships with other spatially co-varying factors (e.g. summer precipitation). Patterns of spatial variation in relationships, provided by GWR models, allowed formulating hypotheses about potential ecological processes underlying them, beyond generalizations resulting from global (OLS) models.