Testing for Network and Spatial Autocorrelation

Testing for dependence has been a well-established component of spatial statistical analyses for decades. In particular, several popular test statistics have desirable properties for testing for the presence of spatial autocorrelation in continuous variables. In this paper we propose two contributions to the literature on tests for autocorrelation. First, we propose a new test for autocorrelation in categorical variables. While some methods currently exist for assessing spatial autocorrelation in categorical variables, the most popular method is unwieldy, somewhat ad hoc, and fails to provide grounds for a single omnibus test. Second, we discuss the importance of testing for autocorrelation in data sampled from the nodes of a network, motivated by social network applications. We demonstrate that our proposed statistic for categorical variables can both be used in the spatial and network setting

Prioritising surveillance for alien organisms transported as stowaways on ships travelling to South Africa

The global shipping network facilitates the transportation and introduction of marine and terrestrial organisms to regions where they are not native, and some of these organisms become invasive. South Africa was used as a case study to evaluate the potential for shipping to contribute to the introduction and establishment of marine and terrestrial alien species (i.e. establishment debt) and to assess how this varies across shipping routes and seasons. As a proxy for the number of species introduced (i.e. 'colonisation pressure') shipping movement data were used to determine, for each season, the number of ships that visited South African ports from foreign ports and the number of days travelled between ports. Seasonal marine and terrestrial environmental similarity between South African and foreign ports was then used to estimate the likelihood that introduced species would establish. These data were used to determine the seasonal relative contribution of shipping routes to South Africa's marine and terrestrial establishment debt. Additionally, distribution data were used to identify marine and terrestrial species that are known to be invasive elsewhere and which might be introduced to each South African port through shipping routes that have a high relative contribution to establishment debt. Shipping routes from Asian ports, especially Singapore, have a particularly high relative contribution to South Africa's establishment debt, while among South African ports, Durban has the highest risk of being invaded. There was seasonal variation in the shipping routes that have a high relative contribution to the establishment debt of the South African ports. The presented method provides a simple way to prioritise surveillance effort and our results indicate that, for South Africa, port-specific prevention strategies should be developed, a large portion of the available resources should be allocated to Durban, and seasonal variations and their consequences for prevention strategies should be explored further. (Résumé d'auteur

From descriptive to predictive distribution models: a working example with Iberian amphibians and reptiles

BACKGROUND: Aim of the study was to identify the conditions under which spatial-environmental models can be used for the improved understanding of species distributions, under the explicit criterion of model predictive performance. I constructed distribution models for 17 amphibian and 21 reptile species in Portugal from atlas data and 13 selected ecological variables with stepwise logistic regression and a geographic information system. Models constructed for Portugal were extrapolated over Spain and tested against range maps and atlas data. RESULTS: Descriptive model precision ranged from 'fair' to 'very good' for 12 species showing a range border inside Portugal ('edge species', kappa (k) 0.35–0.89, average 0.57) and was at best 'moderate' for 26 species with a countrywide Portuguese distribution ('non-edge species', k = 0.03–0.54, average 0.29). The accuracy of the prediction for Spain was significantly related to the precision of the descriptive model for the group of edge species and not for the countrywide species. In the latter group data were consistently better captured with the single variable search-effort than by the panel of environmental data. CONCLUSION: Atlas data in presence-absence format are often inadequate to model the distribution of species if the considered area does not include part of the range border. Conversely, distribution models for edge-species, especially those displaying high precision, may help in the correct identification of parameters underlying the species range and assist with the informed choice of conservation measures

The influence of habitat structure on genetic differentiation in red fox populations in north-eastern Poland

The red fox (Vulpes vulpes) has the widest global distribution among terrestrial carnivore species, occupying most of the Northern Hemisphere in its native range. Because it carries diseases that can be transmitted to humans and domestic animals, it is important to gather information about their movements and dispersal in their natural habitat but it is difficult to do so at a broad scale with trapping and telemetry. In this study, we have described the genetic diversity and structure of red fox populations in six areas of north-eastern Poland, based on samples collected from 2002–2003. We tested 22 microsatellite loci isolated from the dog and the red fox genome to select a panel of nine polymorphic loci suitable for this study. Genetic differentiation between the six studied populations was low to moderate and analysis in Structure revealed a panmictic population in the region. Spatial autocorrelation among all individuals showed a pattern of decreasing relatedness with increasing distance and this was not significantly negative until 93 km, indicating a pattern of isolation-by-distance over a large area. However, there was no correlation between genetic distance and either Euclidean distance or least-cost path distance at the population level. There was a significant relationship between genetic distance and the proportion of large forests and water along the Euclidean distances. These types of habitats may influence dispersal paths taken by red foxes, which is useful information in terms of wildlife disease management

Search for rare quark-annihilation decays, B --> Ds(*) Phi

We report on searches for B- --> Ds- Phi and B- --> Ds*- Phi. In the context of the Standard Model, these decays are expected to be highly suppressed since they proceed through annihilation of the b and u-bar quarks in the B- meson. Our results are based on 234 million Upsilon(4S) --> B Bbar decays collected with the BABAR detector at SLAC. We find no evidence for these decays, and we set Bayesian 90% confidence level upper limits on the branching fractions BF(B- --> Ds- Phi) Ds*- Phi)<1.2x10^(-5). These results are consistent with Standard Model expectations.Comment: 8 pages, 3 postscript figues, submitted to Phys. Rev. D (Rapid Communications

The biogeography of abundant and rare bacterioplankton in the lakes and reservoirs of China.

Bacteria play key roles in the ecology of both aquatic and terrestrial ecosystems; however, little is known about their diversity and biogeography, especially in the rare microbial biosphere of inland freshwater ecosystems. Here we investigated aspects of the community ecology and geographical distribution of abundant and rare bacterioplankton using high-throughput sequencing and examined the relative influence of local environmental variables and regional (spatial) factors on their geographical distribution patterns in 42 lakes and reservoirs across China. Our results showed that the geographical patterns of abundant and rare bacterial subcommunities were generally similar, and both of them showed a significant distance-decay relationship. This suggests that the rare bacterial biosphere is not a random assembly, as some authors have assumed, and that its distribution is most likely subject to the same ecological processes that control abundant taxa. However, we identified some differences between the abundant and rare groups as both groups of bacteria showed a significant positive relationship between sites occupancy and abundance, but the abundant bacteria exhibited a weaker distance-decay relationship than the rare bacteria. Our results implied that rare subcommunities were mostly governed by local environmental variables, whereas the abundant subcommunities were mainly affected by regional factors. In addition, both local and regional variables that were significantly related to the spatial variation of abundant bacterial community composition were different to those of rare ones, suggesting that abundant and rare bacteria may have discrepant ecological niches and may play different roles in natural ecosystems

A review of techniques for spatial modeling in geographical, conservation and landscape genetics

Most evolutionary processes occur in a spatial context and several spatial analysis techniques have been employed in an exploratory context. However, the existence of autocorrelation can also perturb significance tests when data is analyzed using standard correlation and regression techniques on modeling genetic data as a function of explanatory variables. In this case, more complex models incorporating the effects of autocorrelation must be used. Here we review those models and compared their relative performances in a simple simulation, in which spatial patterns in allele frequencies were generated by a balance between random variation within populations and spatially-structured gene flow. Notwithstanding the somewhat idiosyncratic behavior of the techniques evaluated, it is clear that spatial autocorrelation affects Type I errors and that standard linear regression does not provide minimum variance estimators. Due to its flexibility, we stress that principal coordinate of neighbor matrices (PCNM) and related eigenvector mapping techniques seem to be the best approaches to spatial regression. In general, we hope that our review of commonly used spatial regression techniques in biology and ecology may aid population geneticists towards providing better explanations for population structures dealing with more complex regression problems throughout geographic space

Soil–strain compatibility: the key to effective use of arbuscular mycorrhizal inoculants?

Consistency of response to arbuscular mycorrhizal (AM) inoculation is required for efficient use of AM fungi in plant production. Here, we found that the response triggered in plants by an AM strain depends on the properties of the soil where it is introduced. Two data sets from 130 different experiments assessing the outcome of a total of 548 replicated single inoculation trials conducted either in soils with a history of (1) high input agriculture (HIA; 343 replicated trials) or (2) in more pristine soils from coffee plantations (CA; 205 replicated trials) were examined. Plant response to inoculation with different AM strains in CA soils planted with coffee was related to soil properties associated with soil types. The strains Glomus fasciculatum-like and Glomus etunicatum-like were particularly performant in soil relatively rich in nutrients and organic matter. Paraglomus occultum and Glomus mosseae-like performed best in relatively poor soils, and G. mosseae and Glomus manihotis did best in soils of medium fertility. Acaulospora scrobiculata, Diversispora spurca, G. mosseae-like, G. mosseae and P. occultum stimulated coffee growth best in Chromic, Eutric Alluvial Cambisol, G. fasciculatum-like and G. etunicatum-like in Calcaric Cambisol and G. manihotis, in Chromic, Eutric Cambisols. Acaulospora scrobiculata and Diversispora spurca strains performed best in Chromic Alisols and Rodic Ferralsols. There was no significant relationship between plant response to AM fungal strains and soil properties in the HIA soil data set, may be due to variation induced by the use of different host plant species and to modification of soil properties by a history of intensive production. Consideration of the performance of AM fungal strains in target soil environments may well be the key for efficient management of the AM symbiosis in plant production