Spatial Structure of Soil Macrofauna Diversity and Tree Canopy in Riparian Forest of Maroon River

Introduction: Sustainability and maintenance of riparian vegetation or restoring of degraded sites is critical to sustain inherent ecosystem function and values. Description of patterns in species assemblages and diversity is an essential step before generating hypotheses in functional ecology. If we want to have information about ecosystem function, soil biodiversity is best considered by focusing on the groups of soil organisms that play major roles in ecosystem functioning when exploring links with provision of ecosystem services. Information about the spatial pattern of soil biodiversity at the regional scale is limited though required, e.g. for understanding regional scale effects of biodiversity on ecosystem processes. The practical consequences of these findings are useful for sustainable management of soils and in monitoring soil quality. Soil macrofauna play significant, but largely ignored roles in the delivery of ecosystem services by soils at plot and landscape scales. One main reason responsible for the absence of information about biodiversity at regional scale is the lack of adequate methods for sampling and analyzing data at this dimension. An adequate approach for the analysis of spatial patterns is a transect study in which samples are taken in a certain order and with a certain distance between samples. Geostatistics provide descriptive tools such as variogram to characterize the spatial pattern of continuous and categorical soil attributes. This method allows assessment of consistency of spatial patterns as well as the scale at which they are expressed. This study was conducted to analyze spatial patterns of soil macrofauna in relation to tree canopy in the riparian forest landscape of Maroon. Materilas and Methods: The study was carried out in the Maroon riparian forest of the southeasternIran (30o 38/- 30 o 39/ N and 50 o 9/- 50 o 10/ E). The climate of the study area is semi-arid. Average yearly rainfall is about 350.04 mm with a mean temperature of 24.5oc. Plant cover, mainly comprises Populus euphratica Olivie and Tamarix arceuthoides Bge and Lycium shawii Roemer & Schultes. Soil macrofauna were sampled using 175 sampling point along parallel transects (perpendicular to the river). The distance between transects was 100m. We considered distance between samples as 50 m. tree canopy were measured in 5* 5 plots. soil macrofauna were extracted from 50 cm×50 cm×10 cm soil monolith by hand-sorting procedure. All soil macrofauna were identified to family level. Evenness (Sheldon index), richness (Menhinich index) and diversity (Shannon H’ index) by using PAST version 1.39, were determined in each sample. Classical statistical parameters, i.e. mean, standard deviation, coefficient of variation, minimum and maximum, were calculated using SPSS17 software. For analysis of the relationship between Soil macrofauna diversity indices and tree canopy (Total canopy, Populous canopy, Tamarix canopy and Serim canopy) we calculated the correlation among soil properties and macrofauna using the Pearson correlation coefficient. Next, to determining the spatial structure, we calculated the semivariances. Semivariance quantifies the spatial dependence of spatially ordered variable values. In order to gather information about the spatial connection between any two variables, and to compare the similarity of their spatial structure patterns, cross-variograms were constructed. Cross-variograms are plots of cross-semivariance against the lag distance. Results and Discussion: Soil macrofauna communities were dominated by earthworm, diplopods, coleoptera, gastropoda, araneae, and insect larvae. Correlation analysis of soil macrofauna and tree canopy indicated weak relationships between them. Weak, but significant relationships were found between macrofauna diversity, evenness, richness and total canopy, Populous canopy and Tamarix canopy (positive). Macrofauna indices and tree canopy(excepted Tamarix canopy) were spatially structured; the variograms revealed the presence of spatial autocorrelation. The variograms of variables especially tree canopy, were characterized by relatively large nugget values, which can be explained by sampling error, short range variability, random and inherent variability.Soil macrofauna diversity indices and tree canopy were moderately spatially dependent. Spatial similarity between variables, indicating potential relationships between macrofauna and tree canopy, was evaluated by cross-variograms for pairs of macrofauna indices and measured tree canopy. According to the cross-variograms, using RSS as criterion for model performance, macrofauna diversity were spatially closely related to total tree canopy, Populus canopy. Spatial distribution of soil macrofauna may be influenced by factors like gradients in soil properties and vegetation cover structure. These factors together with intrinsic population processes constitute proximate controlling factors of population structure. Conclusion: The relationship between macrofauna indices and tree canopy was further explored by means of spatial analyses. Macrofauna indices and tree canopy (excepted Tamarix canopy) were spatially structured. Tree canopy distribution is important for the spatial variability and structure of Soil macrofauna diversity.