Habitat use at fine spatial scale: how does patch clustering criteria explain the use of meadows by red deer?
- 251 Downloads
Large mammalian herbivores are keystone species in different ecosystems. To mediate the effects of large mammalian herbivores on ecosystems, it is crucial to understand their habitat selection pattern. At finer scales, herbivore patch selection depends strongly on plant community traits and therefore its understanding is constrained by patch definition criteria. Our aim was to assess which criteria for patch definition best explained use of meadows by wild, free-ranging, red deer (Cervus elaphus) in a study area in Northeast Portugal. We used two clustering criteria types based on floristic composition and gross forage classes, respectively. For the floristic criteria, phytosociological approach was used to classify plant communities, and its objectivity evaluated with a mathematical clustering of the floristic relevés. Cover of dominant plant species was tested as a proxy for the phytosociological method. For the gross forage classes, the graminoids/forbs ratio and the percentage cover of legumes were used. For assessing deer relative use of meadows we used faecal accumulation rates. Patches clustered according to floristic classification better explained selection of patches by deer. Plant community classifications based on phytosociology, or proxies of this, used for characterizing meadow patches resulted useful to understand herbivore selection pattern at fine scales and thus potentially suitable to assist wildlife management decisions.
KeywordsPatch definition Cervus elaphus Faecal accumulation rate Foraging habitat use Hay meadows
Annalisa Bellu was financed by a PhD grant from Fundação para a Ciência e a Tecnologia (SRFH/BD/24134/2005), within the programme of National funds of the Ministério da Ciência, Tecnologia e Ensino Superior (MCTES). The authors would like to thank two anonymous reviewers for their valuable comments on a previous draft of the manuscript.
- Aguiar CFG (2001) Flora e vegetação da Serra de Nogueira e do Parque Natural de Montesinho. PhD Thesis, Technical University of LisbonGoogle Scholar
- Braun-Blanquet J (1932) Plant sociology—the study of plant communities. McGraw-Hill, New YorkGoogle Scholar
- Clauss M, Kaiser T, Hummel J (2007) The morphophysiological adaptations of browsing and grazing mammals. In: Gordon P (ed) The ecology of browsing and grazing. Springer, Berlin, pp 47–88Google Scholar
- Clutton-Brock TH, Guinness FE, Albon SD (1982) Red deer behavior and ecology of two sexes. The University of Chicago Press, ChicagoGoogle Scholar
- Dufrêne M, Legendre P (1997) Species assemblages and indicator species: the need for a flexible asymmetrical approach. Ecol Monogr 67(3):345–366Google Scholar
- European Commission (2007) Interpretation manual of European Union Habitats—EUR 27. European Commission DG EnvironmentGoogle Scholar
- Fales SL, Fritz JO (2007) Factors affecting forage quality. In: Barnes RF, Miller DA, Nelson CJ (eds) Forages: the Science of Grassland Agriculture. Blackwell Publishing, pp 569–580Google Scholar
- Fisher RA (1990) Statistical methods, experimental design, and scientific inference: a re-issue of statistical methods for research workers, the design of experiments, and statistical methods and scientific inference. Oxford University Press, USAGoogle Scholar
- Hartigan JA, Wong MA (1979) Algorithm AS 136: a k-means clustering algorithm. J R Stat Soc Ser C Appl Stat 28(1):100–108Google Scholar
- Monteiro-Henriques T (2010) Landscape and phytosociology of the Paiva River’s hydrographical basin. PhD Thesis, Technical University of LisbonGoogle Scholar
- Mueller-Dombois D, Ellenberg H (1974) Aims and methods of vegetation ecology. Wiley, New YorkGoogle Scholar
- Noor A, Habib B, Kumar S (2010) Effects of plot size and shape on the encounter rate of ungulate faecal pellet groups and abundance estimate precision. Curr Sci 99(6):800–804Google Scholar
- Paiva J (2004). Estimating red and roe deer population densities in Parque Natural de Montesinho. First degree thesis, University of CoimbraGoogle Scholar
- R Development Core Team (2010) R: a language and environment for statistical computing. R Foundation for Statistical Computing, ViennaGoogle Scholar
- Rivas-Martínez S (2007) Mapa de series, geoseries y geopermaseries de vegetación de España. Itinera Geobot 17:5–436Google Scholar
- Roberts DW (2007) labdsv: ordination and multivariate analysis for ecology. R package version 1.3–1. http://ecology.msu.montana.edu/labdsv/R
- Shipley LA (1999) Grazers and browsers: how digestive morphology affects diet selection. In: Launchbaugh KL, Sanders KD, Mosley JC (eds) Grazing behaviour of livestock and wildlife. Univ. of Idaho, Moscow, pp 20–27Google Scholar
- van der Maarel E (2005) Vegetation ecology—an overview. In: van der Maarel E (ed) Vegetation ecology. Blackwell, Oxford, pp 1–51Google Scholar
- van Soest PJ (ed) (1994) Nutritional ecology of the ruminant. Cornell University Press, IthacaGoogle Scholar