Effect of Site Level Environmental Variables, Spatial Autocorrelation and Sampling Intensity on Arthropod Communities in an Ancient Temperate Lowland Woodland Area

Abstract

The interaction of arthropods with the environment and the management of their populations is a focus of the ecological agenda. Spatial autocorrelation and under-sampling may generate bias and, when they are ignored, it is hard to determine if results can in any way be trusted. Arthropod communities were studied during two seasons and using two methods: window and panel traps, in an area of ancient temperate lowland woodland of Zebracka (Czech Republic). The composition of arthropod communities was studied focusing on four site level variables (canopy openness, diameter in the breast height and height of tree, and water distance) and finally analysed using two approaches: with and without effects of spatial autocorrelation. I found that the proportion of variance explained by space cannot be ignored (≈20% in both years). Potential bias in analyses of the response of arthropods to site level variables without including spatial co-variables is well illustrated by redundancy analyses. Inclusion of space led to more accurate results, as water distance and tree diameter were significant, showing approximately the same ratio of explained variance and direction in both seasons. Results without spatial co-variables were much more disordered and were difficult to explain. This study showed that neglecting the effects of spatial autocorrelation could lead to wrong conclusions in site level studies and, furthermore, that inclusion of space may lead to more accurate and unambiguous outcomes. Rarefactions showed that lower sampling intensity, when appropriately designed, can produce sufficient results without exploitation of the environment.

Restoration of invaded Cape Floristic Region riparian systems leads to a recovery in foliage-active arthropod alpha- and beta-diversity

“…Possible reasons for significantly higher β1-diversity for arthropods in near pristine as compared to heavily invaded sites are numerous, but may include: (i) higher heterogeneity in both plant species composition and structure (Walz 2011); there is current evidence that diverse habitats support higher biological diversity than monotypic ones, thus allowing more species to coexist (Mlambo et al 2011), (ii) spatial autocorrelation i.e. sites that are further apart have a tendency to differ drastically in arthropod species composition (Horak 2013).…”

Suitability of biodiversity-area and biodiversity-perimeter relationships in ecology: a case study of urban ecosystems

“…2 and 4). The problem of spatial autocorrelation (i.e., that everything is related to everything else and that objects close to each other are more related than those that are further apart; Tobler 1970) is a common problem of ecological research (Horak 2013). A method of spatial autoregression, the Simultaneous autoregressive model as implemented in SAM v4.0 (spatial error model; Rangel et al 2010), was used for the analyses: C=σ 2 [(I -ρW) T ] −1 [I -ρW] −1 .…”

The influence of mature oak stands and spruce plantations on soil-dwelling click beetles in lowland plantation forests

“…coordinates and their crossed and square products (x, y, xy, x 2 , y 2 ; e.g. Horák, 2013 ). Spatial partitioning of the studied patches helped with the selection of the best spatial extent (i.e.…”