Geostatistical analysis shows species-specific habitat preferences for parasitoids

Parasitoids are known to inhabit native vegetation on Australian farms but the extent to which they spill-over into nearby crops is not clear. Geostatistical analysis of parasitoid distribution data showed that vegetational preference and spill-over between native vegetation and cotton fields are highly variable, even between congenerics.     

Patterns of spatial autocorrelation of assemblages of birds, floristics, physiognomy, and primary productivity in the central Great Basin, USA

We fitted spatial autocorrelation functions to distance-based data for assemblages of birds and for three attributes of birds' habitats at 140 locations, separated by up to 65 km, in the Great Basin (Nevada, USA). The three habitat characteristics were taxonomic composition of the vegetation, physical structure of the vegetation, and a measure of primary productivity, the normalized difference vegetation index, estimated from satellite imagery. We found that a spherical model was the best fit to data for avifaunal composition, vegetation composition, and primary productivity, but the distance at which spatial correlation effectively was zero differed substantially among data sets ( c . 30 km for birds, 20 km for vegetation composition, and 60 km for primary productivity). A power-law function was the best fit to data for vegetation structure, indicating that the structure of vegetation differed by similar amounts irrespective of distance between locations (up to the maximum distance measured). Our results suggested that the spatial structure of bird assemblages is more similar to vegetation composition than to either vegetation structure or primary productivity, but is autocorrelated over larger distances. We believe that the greater mobility of birds compared with plants may be responsible for this difference.     

Distinguishing colonisation modes from spatial structures in populations of the cushion plant Azorella madreporica in the high‐Andes of central Chile

Abstract We developed multiple a priori hypotheses to link the observed spatial patterns with colonisation processes in the high alpine cushion plant, Azorella madreporica. We conducted this study in the Molina River basin (33°20′ S, 70°16′ W, 3600 m a.s.l.), in the Andes of central Chile, approximately 50 km east of Santiago. We mapped and measured size (as a surrogate for age) of individual cushions in two populations and used a standard spatial analytical tool (semivariograms) to test our alternative a priori hypotheses related to colonisation mode of the cushion species. In both populations, the size distribution of A. madreporica reflected a negative exponential or inverse‐J pattern, typical of uneven‐aged populations, where most of the cushions belonged to relatively smaller size classes, in effect, a regular success in the establishment of seedlings, where all size classes of cushions were represented in the population. The results were site‐specific, where best‐fit semivariograms for spatial cushion's size distribution suggested a gradual colonisation in one population and an episodic colonisation in the other population. Microsite distribution proved to be homogeneous at both sites. Thus, the study of the spatial explicit size‐age population distribution of an alpine species provides valuable information about the frequency, magnitude and site variation of the reproductive pulses in these harsh environments.     

Spatial Variability of Soil Properties in a Floodplain Forest in Northwest Spain

Floodplain forests are generally areas of high plant diversity compared with upland forests. Higher environmental heterogeneity, especially variation in belowground properties may help explain this high diversity. However, there is little information available on the spatial scale and pattern of belowground resources in floodplain forests. Geostatistics and coefficient of variation (CV) were used to describe the spatial variability of 20 soil properties ranging from essential plant nutrients, such as NH₄ or PO₄, to nonessential elements like Ti or V. The spatial variation of Si-to-(Al + Fe) ratio, an index of soil development, was also analyzed. Semivariograms and maps of selected properties were used to discriminate between the effect of flooding (and other mechanisms that may contribute to large scale trends in data) and local heterogeneity. The hypothesis that elements mainly cycled through biological processes (such as N) show different spatial properties than elements cycled through both biological and geological processes (such as P) or elements under strict geological control (such as Ti or V) is also presented. Redox potential was the most variable property (CV = 1.35) followed by mineral N, phosphate, organic matter, and carbon. Nonessential elements for organisms such as Si, Al, Ti, Rh, or V were less variable, supporting the hypothesis that biological control on soil properties leads to higher spatial variability. The range (the average distance within which the samples correlate spatially) varied between 3.89 m for water content to 18.5 m for the Si-to-(Al + Fe) ratio. The proportion of the total variance that can be modeled as spatial dependence (structural variance) was very variable, ranging between 0.34 for Fe and 0.96 for K. The addition of the large trend had a strong influence on the CV of most soil variables and created a gradient in C accumulation and the mineral weathering rate. The results suggest that flooding and other processes that are responsible for large spatial trends in the floodplain forest differentially affect biologically and geologically controlled variables with different turnover rates, thus providing a heterogeneous edaphic environment.