Grazing management or physiography? Factors controlling vegetation recovery in Mediterranean grasslands - Carmona, Carlos P.; Röder, Achim; Azcárate, Francisco M.; Peco, Begoña (Ecological Modelling, 2013)
Grazing intensification and abandonment are increasing the risk of degradation of Mediterranean grasslands. The development of techniques for monitoring grazing effects on herbaceous vegetation is an essential need for the management of these rangelands. However, the high variability of these systems make physiographical and management effects hard to disentangle and quantify. We present a methodology to support rangeland management and assess grazing effects on environmentally heterogeneous areas, and provide an example of its application in a Mediterranean rangeland in central Spain. We evaluated the difference in photosynthetically active vegetation cover between spring and summer using Spectral Mixture Analysis of very high spatial resolution (2.4 m) Quickbird images. To analyze this difference, we developed Boosted Regression Trees models using grazing management (accumulated cost distance to points of livestock concentration and water points) and physiographical variables (slope, wetness, proximity to the closest tree and orientation). Results show that the main factor determining changes in vegetation cover is habitat type. The magnitude of this change was maximized at intermediate grazing pressures for humid habitats, suggesting the existence of an optimal level of grazing in this zones, while in dry habitats differences in vegetation cover increased consistently along with grazing pressure. Our models provided a valuable insight into how different variables and its interactions affect the observed recovery capacity of vegetation. Moreover, by identifying areas in which grazing-induced land degradation could be taken place, our methodology can be used as a powerful tool in the management of highly heterogeneous rangelands.
Keywords: Boosted Regression Trees; Cost surfaces; Grazing gradients; Mediterranean; Rangeland management; Spectral Mixture Analysis

Economic and management characterization of dehesa farms: implications for their sustainability - Gaspar, P; Mesías, F J; Escribano, M; Rodriguez de Ledesma, A; Pulido, F (Agroforestry Systems, 2007)
Dehesa agroforestry systems occupy around 6 million ha in the Iberian Peninsula. Their economic and environmental sustainability depends on the maintenance of the extensive livestock farms which created this typical ecosystem. This work analyzes dehesa farms in the Extremadura region (SW Spain) using technical and economic indicators of 69 randomly selected holdings. Principal component analysis (PCA) allowed us to establish a valid model explaining 65.8% of the variance. The two principal components having most weight were Iberian pig production (explaining 20% of the variance of the model), and which ruminant species were raised on the farm (15% of the variance). A cluster analysis distinguished ﬁve types of farms: sheep farms at high and low stocking rates, beef cattle farms, wooded farms with mixed livestock, and farms with a high level of cropping activity. The most proﬁtable farms were those with either high overall livestock density or a high level of Iberian pig production. While high stocking density has historically attracted high levels of subsidy, production of Iberian pigs was proﬁtable because of the high value of the product. In the light of CAP reform, Iberian pig production seems the most readily sustainable type of farming for the dehesa system.
Keywords: cluster analysis; Farm typology; Livestock farming systems; Principal component analysis; Rangeland management

Economic and management characterization of dehesa farms: implications for their sustainability - Gaspar, P.; Mesías, F. J.; Escribano, M.; Rodríguez de Ledesma, A.; Pulido, F. (Agroforestry Systems, 2007)
Dehesa agroforestry systems occupy around 6 million ha in the Iberian Peninsula. Their economic and environmental sustainability depends on the maintenance of the extensive livestock farms which created this typical ecosystem. This work analyzes dehesa farms in the Extremadura region (SW Spain) using technical and economic indicators of 69 randomly selected holdings. Principal component analysis (PCA) allowed us to establish a valid model explaining 65.8% of the variance. The two principal components having most weight were Iberian pig production (explaining 20% of the variance of the model), and which ruminant species were raised on the farm (15% of the variance). A cluster analysis distinguished ﬁve types of farms: sheep farms at high and low stocking rates, beef cattle farms, wooded farms with mixed livestock, and farms with a high level of cropping activity. The most proﬁtable farms were those with either high overall livestock density or a high level of Iberian pig production. While high stocking density has historically attracted high levels of subsidy, production of Iberian pigs was proﬁtable because of the high value of the product. In the light of CAP reform, Iberian pig production seems the most readily sustainable type of farming for the dehesa system.
Keywords: cluster analysis; Farm typology; Livestock farming systems; Principal component analysis; Rangeland management