Representation of animal distributions in space: how geostatistical estimates impact simulation modeling of foot-and-mouth disease spread

Modeling potential disease spread in wildlife populations is important for predicting, responding to and recovering from a foreign animal disease incursion. To make spatial epidemic predictions, the target animal species of interest must first be represented in space. We conducted a series of simulation experiments to determine how estimates of the spatial distribution of white-tailed deer impact the predicted magnitude and distribution of foot-and-mouth disease (FMD) outbreaks. Outbreaks were simulated using a susceptible-infected-recovered geographic automata model. The study region was a 9-county area (24 000 km$^{2})$ of southern Texas. Methods used for creating deer distributions included dasymetric mapping, kriging and remotely sensed image analysis. The magnitudes and distributions of the predicted outbreaks were evaluated by comparing the median number of deer infected and median area affected (km$^{2})$, respectively. The methods were further evaluated for similar predictive power by comparing the model predicted outputs with unweighted pair group method with arithmetic mean (UPGMA) clustering. There were significant differences in the estimated number of deer in the study region, based on the geostatistical estimation procedure used (range: 385 939–768 493). There were also substantial differences in the predicted magnitude of the FMD outbreaks (range: 1 563–8 896) and land area affected (range: 56–447 km$^{2})$ for the different estimated animal distributions. UPGMA clustering indicated there were two main groups of distributions, and one outlier. We recommend that one distribution from each of these two groups be used to model the range of possible outbreaks. Methods included in cluster 1 (such as county-level disaggregation) could be used in conjunction with any of the methods in cluster 2, which included kriging, NDVI split by ecoregion, or disaggregation at the regional level, to represent the variability in the model predicted outbreak distributions. How animal populations are represented needs to be considered in all spatial disease spread models

The impact of seasonal variability in wildlife populations on the predicted spread of foot and mouth disease

Modeling potential disease spread in wildlife populations is important for predicting, responding to and recovering from a foreign animal disease incursion such as foot and mouth disease (FMD). We conducted a series of simulation experiments to determine how seasonal estimates of the spatial distribution of white-tailed deer impact the predicted magnitude and distribution of potential FMD outbreaks. Outbreaks were simulated in a study area comprising two distinct ecoregions in South Texas, USA, using a susceptible-latent-infectious-resistant geographic automata model (Sirca). Seasonal deer distributions were estimated by spatial autoregressive lag models and the normalized difference vegetation index. Significant (P < 0.0001) differences in both the median predicted number of deer infected and number of herds infected were found both between seasons and between ecoregions. Larger outbreaks occurred in winter within the higher deer-density ecoregion, whereas larger outbreaks occurred in summer and fall within the lower deer-density ecoregion. Results of this simulation study suggest that the outcome of an FMD incursion in a population of wildlife would depend on the density of the population infected and when during the year the incursion occurs. It is likely that such effects would be seen for FMD incursions in other regions and countries, and for other diseases, in cases in which a potential wildlife reservoir exists. Study findings indicate that the design of a mitigation strategy needs to take into account population and seasonal characteristics

Phylogenetic diversity and conservation of crop wild relatives in Colombia

Crop wild relatives (CWR) are an important agricultural resource as they contain genetic traits not found in cultivated species due to localized adaptation to unique environmental and climatic conditions. Phylogenetic diversity (PD) measures the evolutionary relationship of species using the tree of life. Our knowledge of CWR PD in neotropical regions is in its infancy. We analysed the distribution of CWR PD across Colombia and assessed its conservation status. The areas with the largest concentration of PD were identified as being in the northern part of the central and western Andean mountain ranges and the Pacific region. These centres of high PD were comprised of predominantly short and closely related branches, mostly of species of wild tomatoes and black peppers. In contrast, the CWR PD in the lowland ecosystems of the Amazon and Orinoquia regions had deeply diverging clades predominantly represented by long and distantly related branches (i.e. tuberous roots, grains and cacao). We categorized 50 (52.6%) of the CWR species as 'high priority', 36 as 'medium priority' and nine as 'low priority' for further ex-situ and in situ conservation actions. New areas of high PD and richness with large ex-situ gap collections were identified mainly in the northern part of the Andes of Colombia. We found that 56% of the grid cells with the highest PD values were unprotected. These baseline data could be used to create a comprehensive national strategy of CWR conservation in Colombia

Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology

Infectious wildlife diseases have enormous global impacts, leading to human pandemics, global biodiversity declines and socio-economic hardship. Understanding how infection persists and is transmitted in wildlife is critical for managing diseases, but our understanding is limited. Our study aim was to better understand how infectious disease persists in wildlife populations by integrating genetics, ecology and epidemiology approaches. Specifically, we aimed to determine whether environmental or host factors were stronger drivers of Salmonella persistence or transmission within a remote and isolated wild pig (Sus scrofa) population. We determined the Salmonella infection status of wild pigs. Salmonella isolates were genotyped and a range of data was collected on putative risk factors for Salmonella transmission. We a priori identified several plausible biological hypotheses for Salmonella prevalence (cross sectional study design) versus transmission (molecular case series study design) and fit the data to these models. There were 543 wild pig Salmonella observations, sampled at 93 unique locations. Salmonella prevalence was 41% (95% confidence interval [CI]: 37-45%). The median Salmonella DICE coefficient (or Salmonella genetic similarity) was 52% (interquartile range [IQR]: 42-62%). Using the traditional cross sectional prevalence study design, the only supported model was based on the hypothesis that abundance of available ecological resources determines Salmonella prevalence in wild pigs. In the molecular study design, spatial proximity and herd membership as well as some individual risk factors (sex, condition score and relative density) determined transmission between pigs. Traditional cross sectional surveys and molecular epidemiological approaches are complementary and together can enhance understanding of disease ecology: abundance of ecological resources critical for wildlife influences Salmonella prevalence, whereas Salmonella transmission is driven by local spatial, social, density and individual factors, rather than resources. This enhanced understanding has implications for the control of diseases in wildlife populations. Attempts to manage wildlife disease using simplistic density approaches do not acknowledge the complexity of disease ecology

Continental scale patterns and predictors of fern richness and phylogenetic diversity

Because ferns have a wide range of habitat preferences and are widely distributed, they are an ideal group for understanding how diversity is distributed. Here we examine fern diversity on a broad-scale using standard and corrected richness measures as well as phylogenetic indices; in addition we determine the environmental predictors of each diversity metric. Using the combined records of Australian herbaria, a dataset of over 60,000 records was obtained for 89 genera to infer richness. A molecular phylogeny of all the genera was constructed and combined with the herbarium records to obtain phylogenetic diversity patterns. A hotspot of both taxic and phylogenetic diversity occurs in the Wet Tropics of northeastern Australia. Although considerable diversity is distributed along the eastern coast, some important regions of diversity are identified only after sample-standardization of richness and through the phylogenetic metric. Of all of the metrics, annual precipitation was identified as the most explanatory variable, in part, in agreement with global and regional fern studies. However, precipitation was combined with a different variable for each different metric. For corrected richness, precipitation was combined with temperature seasonality, while correlation of phylogenetic diversity to precipitation plus radiation indicated support for the species-energy hypothesis. Significantly high and significantly low phylogenetic diversity were found in geographically separate areas. These separate areas correlated with different climatic conditions such as seasonality in precipitation. The phylogenetic metrics identified additional areas of significant diversity, some of which have not been revealed using traditional taxonomic analyses, suggesting that different ecological and evolutionary processes have operated over the continent. Our study demonstrates that it is possible and vital to incorporate evolutionary metrics when inferring biodiversity hotspots from large compilations of data

Assessing biodiversity and endemism using phylogenetic methods across multiple taxonomic groups

Identifying geographical areas with the greatest representation of the tree of life is an important goal for the management and conservation of biodiversity. While there are methods available for using a single phylogenetic tree to assess spatial patterns of biodiversity, there has been limited exploration of how separate phylogenies from multiple taxonomic groups can be used jointly to map diversity and endemism. Here, we demonstrate how to apply different phylogenetic approaches to assess biodiversity across multiple taxonomic groups. We map spatial patterns of phylogenetic diversity/endemism to identify concordant areas with the greatest representation of biodiversity across multiple taxa and demonstrate the approach by applying it to the Murray–Darling basin region of southeastern Australia. The areas with significant centers of phylogenetic diversity and endemism were distributed differently for the five taxonomic groups studied (plant genera, fish, tree frogs, acacias, and eucalypts); no strong shared patterns across all five groups emerged. However, congruence was apparent between some groups in some parts of the basin. The northern region of the basin emerges from the analysis as a priority area for future conservation initiatives focused on eucalypts and tree frogs. The southern region is particularly important for conservation of the evolutionary heritage of plants and fishes

Lexical similarity and endemism in historical wordlists of Australian Aboriginal languages of the greater Sydney region

To reconstruct an indigenous language known solely from historical wordlists, the linguist needs to decide which source wordlists are most relevant, i.e. which sources are most likely to be attestations of the language to be reconstructed. There is little published research on methods appropriate to this task, and yet there is increasing attention to indigenous language reconstruction in support of language revival and revitalisation in education and community contexts. This paper describes a replicable and relatively objective method for comparing lexical similarity within a set of historical sources. The method described draws on the use of measures of lexical similarity in linguistics and the use of measures of endemism in biogeography. The method is illustrated via an analysis of historical sources for Aboriginal languages from the greater Sydney region, New South Wales, Australia. The sample is used to describe the overall similarity and difference between wordlists from this region, and to identify which wordlists are most similar to the wordlist recorded by the surveyor R. H. Mathews (e.g. 1903) as Darkinyung language

Data from: Fern and lycophyte diversity in the Pacific Northwest: patterns and predictors

Recent floristic efforts in the Pacific Northwest (PNW) have made it possible to characterize the broad-scale patterns of fern and lycophyte diversity across this geologically-complex region of western North America. The physiography of the PNW has been developing for over 200 million years, but Pleistocene glaciation-induced migrations and recolonizations have strongly influenced the assembly of the flora. With the high dispersal potential of spores, distribution patterns of pteridophytes may represent habitat suitability more than dispersal constraints. Our objective was to describe the biodiversity of pteridophytes in the PNW, determine the spatial distribution of that biodiversity in terms of phylogenetic diversity, identify centers of regional endemism, explore correlations between biodiversity and environmental variables, and infer influences of past glaciation on the pteridophyte flora. We obtained distribution data, constructed a phylogenetic tree using chloroplast data, and used the Biodiverse software package to estimate and map phylogenetic diversity and phylogenetic endemism across the PNW, identifying regions where diversity was higher or lower than expected in comparison to randomization models. Environmental correlates of diversity were identified using principal components analysis with bioclimatic data from WorldClim.org, and we used Maxent to predict habitat suitability for species under past and future climate conditions. We found evidence for the influence of glacial refugia on patterns of pteridophyte diversity, that moisture availability and cold temperatures are strongly correlated with patterns of richness, phylogenetic diversity, and phylogenetic endemism, and infer that topographic complexity may be driving the assembly of the pteridophyte flora indirectly by influencing climate and precipitation patterns

The Incidence of low phosphorus soils in Australia

Background: Low phosphorus (P) soils have been described as a widespread characteristic of the Australian continent and associated with sclerophyll leaf traits. In that context we ask: what proportion of the continent is low-P and how much does this vary between regions? Methods: 9234 locations sampled for soil total P from the Australian National Site Soil Data Collation were analysed. In order to make some adjustment for uneven spatial sampling we area-weighted the data using subregions from the Interim Bioregionalisation of Australia. Results: Topsoil total P concentrations ≤100 mg kg⁻¹ were widespread, but not a majority of the continent (estimated 25 %). The western Monsoon Tropics (65 %), southwestern Australia (50 %), and southeast South Australia (38 %) were estimated to have larger fractions of the sampled landscape ≤100 mg kg⁻¹ than eastern Australia (13.5 %), but not a lower range of values. Total P values across the continent included a large fraction (33 %) in the range 101–250 mg kg⁻¹. Conclusions: Continent-wide soil P levels low enough to favour long leaf lifespans for nutrient conservation and a variety of sclerophyll traits were widespread. It is time to move away from the qualitative dichotomies between low- and high-P that have characterised discussion of Australian vegetation, to a more quantitative view.8 page(s