Spatial variation in adult sex ratio across multiple scales in the invasive golden apple snail, Pomacea canaliculata

Adult sex ratio (ASR) has critical effects on behavior and life history and has implications for population demography, including the invasiveness of introduced species. ASR exhibits immense variation in nature, yet the scale dependence of this variation is rarely analyzed. In this study, using the generalized multilevel models, we investigated the variation in ASR across multiple nested spatial scales and analyzed the underlying causes for an invasive species, the golden apple snail Pomacea canaliculata. We partitioned the variance in ASR to describe the variations at different scales and then included the explanatory variables at the individual and group levels to analyze the potential causes driving the variation in ASR. We firstly determined there is a significant female-biased ASR for this species when accounting for the spatial and temporal autocorrelations of sampling. We found that, counter to nearly equal distributed variation at plot, habitat and region levels, ASR showed little variation at the town level. Temperature and precipitation at the region level were significantly positively associated with ASR, whereas the individual weight, the density characteristic, and sampling time were not significant factors influencing ASR. Our study suggests that offspring sex ratio of this species may shape the general pattern of ASR in the population level while the environmental variables at the region level translate the unbiased offspring sex ratio to the female-biased ASR. Future research should consider the implications of climate warming on the female-biased ASR of this invasive species and thus on invasion pattern.

The Representative Soil Sampling Scheme of England and Wales: the spatial variation of topsoil nutrient status and pH between 1971 and 2001

The Representative Soil Sampling Scheme (RSSS) has monitored the soil of agricultural land in England and Wales since 1969. Here we describe the first spatial analysis of the data from these surveys using geostatistics. Four years of data (1971, 1981, 1991 and 2001) were chosen to examine the nutrient (available K, Mg and P) and pH status of the soil. At each farm, four fields were sampled; however, for the earlier years, coordinates were available for the farm only and not for each field. The averaged data for each farm were used for spatial analysis and the variograms showed spatial structure even with the smaller sample size. These variograms provide a reasonable summary of the larger scale of variation identified from the data of the more intensively sampled National Soil Inventory. Maps of kriged predictions of K generally show larger values in the central and southeastern areas (above 200 mg L-1) and an increase in values in the west over time, whereas Mg is fairly stable over time. The kriged predictions of P show a decline over time, particularly in the east, and those of pH show an increase in the east over time. Disjunctive kriging was used to examine temporal changes in available P using probabilities less than given thresholds of this element. The RSSS was not designed for spatial analysis, but the results show that the data from these surveys are suitable for this purpose. The results of the spatial analysis, together with those of the statistical analyses, provide a comprehensive view of the RSSS database as a basis for monitoring the soil. These data should be taken into account when future national soil monitoring schemes are designed.

A geostatistical analysis of the spatial variation of soil mineral nitrogen and potentially available nitrogen within an arable field.

The technology for site-specific applications of nitrogen (N) fertilizer has exposed a gap in our knowledge about the spatial variation of soil mineral N, and that which will become available during the growing season within arable fields. Spring mineral N and potentially available N were measured in an arable field together with gravimetric water content, loss on ignition, crop yield, percentages of sand, silt, and clay, and elevation to describe their spatial variation geostatistically. The areas with a larger clay content had larger values of mineral N, potentially available N, loss on ignition and gravimetric water content, and the converse was true for the areas with more sandy soil. The results suggest that the spatial relations between mineral N and loss on ignition, gravimetric water content, soil texture, elevation and crop yield, and between potentially available N and loss on ignition and silt content could be used to indicate their spatial patterns. Variable-rate nitrogen fertilizer application would be feasible in this field because of the spatial structure and the magnitude of variation of mineral N and potentially available N.

Simulating the spatial variation of soil mineral N within fields using the model SUNDIAL

Variable rate applications of nitrogen (N) are of environmental and economic interest. Regular measurements of soil N supply are difficult to achieve practically. Therefore accurate model simulations of soil N supply might provide a practical solution for site-specific management of N. Mineral N, an estimate of N supply, was simulated by the model SUNDIAL (Simulation of Nitrogen Dynamics In Arable Land) at more than 100 locations within three arable fields in Bedfordshire, UK. The results were compared with actual measurements. The outcomes showed that the spatial patterns of the simulations of mineral N corresponded to the measurements but the range of values was underestimated.

Sampling the soil in long-term forest plots: The implications of spatial variation

Long-term monitoring of forest soils as part of a pan-European network to detect environmental change depends on an accurate determination of the mean of the soil properties at each monitoring event. Forest soil is known to be very variable spatially, however. A study was undertaken to explore and quantify this variability at three forest monitoring plots in Britain. Detailed soil sampling was carried out, and the data from the chemical analyses were analysed by classical statistics and geostatistics. An analysis of variance showed that there were no consistent effects from the sample sites in relation to the position of the trees. The variogram analysis showed that there was spatial dependence at each site for several variables and some varied in an apparently periodic way. An optimal sampling analysis based on the multivariate variogram for each site suggested that a bulked sample from 36 cores would reduce error to an acceptable level. Future sampling should be designed so that it neither targets nor avoids trees and disturbed ground. This can be achieved best by using a stratified random sampling design.

Exploring the spatial variation of take-all (Gaeumannomyces graminis var. tritici) for site-specific management

The fungus Gaeumannomyces graminis var. tritici (Ggt), commonly known as the take-all fungus, causes damage to roots of wheat and barley that limits crop growth and causes loss of yield. There was little knowledge on the within-field spatial variation of take-all and relations with features in the growing crop, selected soil properties and spectral information from remotely sensed imagery. Geostatistical analyses showed that take-all, chlorosis and leaf area index had similar patchy distributions. Many of the spectral bands from a hyperspectral image also had similar spatial patterns to take-all and chlorosis. Relations between take-all and mineral nitrogen, elevation and pH were generally weaker.

An integrated study of the temporal and spatial variation in the supply of propagules, recruitment and assemblages of intertidal macroalgae on a wave-exposed rocky coast, Victoria, Australia

Recruitment is known to influence distributions and abundances of benthic marine organisms. It is therefore important to document patterns of variability in recruitment and how these relate to patterns in established assemblages. This study provides an integrated assessment of the temporal and spatial variation in supply and recruitment of propagules and established populations of several macroalgae. Propagules in water samples from two stages of the incoming tide, recruitment to artificial substrata and percentage cover of species established on the shore were recorded every 2 months from December 1994 to October 1995, in two zones of an intertidal, wave-exposed rocky shore. Variability in recruitment was measured at three spatial scales: 10s cm, 100s cm and 100s m. Availability and recruitment of most taxa were greatest between April and August, although many species had available propagules and recruited throughout the year. Temporal variation in the established assemblages was, however, more species-specific. Differences in established assemblages between zones were reflected in differences in availability and recruitment of propagules between zones. Recruitment could not be predicted directly from supply of propagules, but the two processes were linked. For most species, the greatest variation in recruitment occurred at the smallest spatial scale of 10s cm, although there was also considerable large-scale (between site) variation in recruitment of several species. Results indicate that while pre-and post-settlement mortality are likely to influence macroalgal distribution and abundance, the temporal and spatial variability in supply and recruitment of propagules can explain much of the patchiness in macroalgal assemblages.

Spatial variation in tuber depletion by swans explained by differences in net intake rates

We tested whether the spatial variation in resource depletion by Tundra Swans (Cygnus columbianus) foraging on belowground tubers of sago pondweed (Potamogeton pectinatus) was caused by differences in net energy intake rates. The variation in giving-up densities within the confines of one lake was nearly eightfold, the giving-up density being positively related to water depth and, to a lesser extent, the silt content of the sediment. The swans' preference (measured as cumulative foraging pressure) was negatively related to these variables. We adjusted a model developed for diving birds to predict changes in the time allocation of foraging swans with changes in power requirements and harvest rate. First, we compared the behavior of free-living swans foraging in shallow and deep water, where they feed by head-dipping and up-ending, respectively. Up-ending swans had 1.3-2.1 times longer feeding times than head-dipping swans. This was contrary to our expectation, since the model predicted a decrease in feeding time with an increase in feeding power. However, up-ending swans also had 1.9 times longer trampling times than headdipping swans. The model predicted a strong positive correlation between trampling time and feeding time, and the longer trampling times may thus have masked any effect of an increase in feeding power. Heart rate measurements showed that trampling was the most energetically costly part of foraging. However, because the feeding time and trampling time changed concurrently, the rate of energy expenditure was only slightly higher in deep water (1.03-1.06 times). This is a conservative estimate since it does not take into account that the feeding costs of up-ending are possibly higher than that of head-dipping. Second, we compared captive swans foraging on sandy and clayey sediments. We found that the harvest rate on clayey sediment was only 0.6 times that on sandy sediment and that the power requirements for foraging were 1.2-1.4 times greater. Our results are in qualitative agreement with the hypothesis that the large spatial variation in giving-up densities was caused by differences in net rates of energy intake. This potentially has important implications for the prey dynamics, because plant regrowth has been shown to be related to the same habitat factors (water depth and sediment type).