Biodiversity indices - grazing land

One of the impacts of land desertification is loss in biodiversity. If an ecosystem is overexploited, the consequence is the loss of biodiversity expressed by direct loss of plant species and the animals associated with them. Biodiversity indices are used to express the change in biodiversity.
In rangeland ecosystems, grazing can have a significant effect on plant species diversity. Commonly, biological diversity is associated with the efficient use of resources and ecosystem resilience. Herbivores can affect the habitat and influence species distributions by increasing or decreasing heterogeneity, which depends on the pre-existing spatial pattern of vegetation and the spatial distribution of grazing. The additive partitioning of species diversity is a way to quantify the components of diversity among scales and measure the contribution of local communities to regional diversity (Lande 1996).

Aim of the method/technique	The proposed technique aims to characterized change in biodiversity at different spatial scales.
Scale – spatial and temporal
Brief description	The Proportional diversity H’ index integrates richness and evenness using the Shannon information index (Shannon 1948),  where pi is the probability that a given species occurs. Gamma, γ, diversity is the total species diversity in a set of samples, and is partitioned into the average diversity within samples (α) and among samples (ß); i.e.  Υ=α+ß, (Wagner 2000). Beta, ß, diversity is the variation in species composition among sites within a region (Whittaker 1972). Beta diversity can be calculated by one of the following methods: Randomization routine (Crist et al. 2003). In each randomization, the frequency distribution of each species and the distribution of sampling effort of the empirical data are maintained (Freestone and Inouye 2006). Randomization are performed at two levels: sample-based randomizations (samples are randomized at each hierarchical level) and individual-based randomizations (randomization occurs at individual level, only, and each randomized data set is partitioned into a and  ß components at each hierarchical level (Crist et al. 2003). Individual-sample randomizations are useful for determining the effect of individual aggregation on the partitioning of diversity, whereas sample-based randomizations reveal how different patches contribute to regional diversity. Variance in community composition (Legendre et al. 2005). This method allows calculating the spatial variation in community composition with respect to environmental variables and spatial components by applying canonical partitioning (Legendre et al. 2005). The variance observed is decomposed in the response variable Y (community composition data) as a function of a set of environmental variables X1 (proportion of bare soil, grazing pressure, and exposure) and a set of spatial variables X2 (X and Y geographical coordinates). To calculate the partitioning of the spatial and environmental components of the variation in community composition, we can use canonical redundancy, RDA (Legendre 2005) Dissimilarities among sites (Kluth 2004). To generate the dissimilarity matrix among sites, the Euclidean distances are calculated. In addition, the distance between data samples are calculated based on GPS coordinates. A Mantel Test is used to calculate the correlation between the species dissimilarities of communities and the distance between them. (Legendre and Legendre 1998).
Data requirements	The required data are field data samples (randomly or stratified distributed) in the landscape
Main applications in grazing regions	The partitioning of plant species diversity across landscapes and regions has been investigated in grazing lands ecosystems (Komac et al. 2011). Description of biodiversity indices of a grassland ecosystem can be useful in assessing the impacts of various LEDD drivers.
Strengths and weaknesses	Defining biodiversity requires expertise in biology with the ability. Strengths are referred to the capability to apply very efficient statistical analysis of the defining plant species distribution. A weakness is the complete spatial and temporal availability of data.

• < Prev
• Next >