Towards the Development of a More Accurate Monitoring Procedure for Invertebrate Populations, in the Presence of an Unknown Spatial Pattern of Population Distribution in the Field

Abstract

Studies addressing many ecological problems require accurate evaluation of the total population size. In this paper, we revisit a sampling procedure used for the evaluation of the abundance of an invertebrate population from assessment data collected on a spatial grid of sampling locations. We first discuss how insufficient information about the spatial population density obtained on a coarse sampling grid may affect the accuracy of an evaluation of total population size. Such information deficit in field data can arise because of inadequate spatial resolution of the population distribution (spatially variable population density) when coarse grids are used, which is especially true when a strongly heterogeneous spatial population density is sampled. We then argue that the average trap count (the quantity routinely used to quantify abundance), if obtained from a sampling grid that is too coarse, is a random variable because of the uncertainty in sampling spatial data. Finally, we show that a probabilistic approach similar to bootstrapping techniques can be an efficient tool to quantify the uncertainty in the evaluation procedure in the presence of a spatial pattern reflecting a patchy distribution of invertebrates within the sampling grid.

Effect of density-dependent individual movement on emerging spatial population distribution: Brownian motion vs Levy flights

“…Spatial distribution of ecological populations is often distinctly heterogeneous [18,45,44] and this is known to have profound implications for the population dynamics as well as for ecological monitoring and population management [16,39,64,67,75,81,90,92,93]. Whilst considerable progress has been done over the last two decades in the understanding of this phenomenon [45,51,52,59], the effect of many relevant factors on the ecological pattern formation remains obscure and many questions yet wait to be answered, so that the problem remains to be a focus of research and discussion [65].…”

“…Our investigation is partially motivated by a recent study on the distribution and movement of grey slug Deroceras reticulatum in agricultural fields [20,64]. Spatial distribution of slugs was shown to be remarkably patchy, with some of the patches being stable throughout the season but not necessarily between the seasons.…”

“…Distinctly heterogeneous or even 'patchy' distributions are ubiquitous in different ecosystems and are seen at different spatial and temporal scales [44,45]. This phenomenon-also referred to as aggregation or patchiness [18,44] or, more generally, ecological pattern formation [59]-is known to have important implications for population dynamics [55,66,87], nature conservation and renewable resource management [16,92,93], agriculture and forestry [1,39,75,81,90], monitoring and pest control [62,64,67], etc. Correspondingly, the factors and processes resulting in ecological pattern formation have been a focus of substantial empirical and theoretical research for a few decades.…”

Stability of Patches of Higher Population Density within the Heterogenous Distribution of the Gray Field Slug Deroceras reticulatum in Arable Fields in the UK

“…The design of a sampling technique that accurately locates slug patches without prior knowledge of the spatial pattern of population distribution, is problematic. This study used the monitoring approach developed by Petrovskaya et al [ 31 ]. In each field, an area of 1 ha was sampled using a 10 × 10 grid of refuge traps (10 m inter-node distance) to assess slug abundance/activity on the soil surface.…”

Movement patterns of the grey field slug (Deroceras reticulatum) in an arable field

“…Size and area of the patch. It is known that in agricultural environments (e.g arable fields), the spatial distribution of the grey field slug is heterogeneous, forming patches of high population density separated by areas with low population density 28,48 . In applications, e.g.…”