1.Predicting the current and potential distributions of established invasive species is critical for evaluating management options, but methods for differentiating these distributions have received little attention. In particular, there is uncertainty among invasive species managers about the value of information from incidental sightings compared to data from designed field surveys. This study compares the two approaches, and develops a unifying framework, using the case of invasive sambar deer Cervus unicolor in Victoria, Australia.2.We first used 391 incidental sightings of sambar deer and 12 biophysical variables to construct a presence-only habitat suitability model using Maxent. We then used that model to stratify field sampling, with proportionately greater sampling of cells with high predicted habitat suitability. Field sampling, consisting of faecal pellet surveys, sign surveys and camera trapping, was conducted in 80 4-km2 grid cells. A Bayesian state-space occupancy model was used to predict probability of suitable habitat from the field data.3.The Maxent and occupancy models predicted similar spatial distributions of habitat suitability for sambar deer in Victoria and there was a strong positive correlation between the rankings of cells by the two approaches. The congruence of the two models suggests that any spatial and detection biases in the presence-only data were relatively unimportant in our study.4.We predicted the extent of suitable habitat from the occupancy model using a threshold that gave a false negative error rate of 0·05. The current distribution was the suitable habitat within a kernel that had a 99·5% chance of including the presence locations pooled from incidental sightings and field surveys: the potential distribution was suitable habitat outside that kernel. Several discrete areas of potential distribution were identified as priorities for surveillance monitoring with the aim of detecting and managing incursions of sambar deer.5.Synthesis and applications.Our framework enables managers to robustly estimate the current and potential distributions of established invasive species using either presence-only and/or presence–absence data. Managers can then focus control and/or containment actions within the current distribution and establish surveillance monitoring to detect incursions within the potential distribution.
Summary 1.A large proportion of the world's land surface is extensively managed for livestock production. In areas where livestock systems are becoming more intensive, a major challenge is to predict those plant species likely to decline, persist or increase as a result of agricultural intensification. 2. Most analyses develop inferences for frequent or abundant species, or rely on intensive studies of single species. A promising approach is to identify plant traits related to disturbance to enable inference to be made about changes in plant community composition. We used a Bayesian hierarchical model to analyse the response to agricultural intensification of 494 plant species of pastures and woodlands in southern Australia, and to identify how simple species' traits (life form, growth form and species origin) influence those responses. 3. The probability of occurrence of most species declined along the two intensification gradients, grazing intensity and soil phosphorous concentration, although the occurrence of a greater proportion of species was negatively correlated with soil phosphorous. Responses could be broadly predicted from both plant origin and plant traits, in particular growth form. 4. Native perennial geophytes, ferns and shrubs were most negatively affected by both gradients, while exotic annual grasses and forbs were more tolerant. Along the phosphorous gradient, 24 of the 30 most negatively affected plant species were native geophytes. Mean within-group responses masked considerable within-and between-species variation, particularly for the exotic species group which included species that responded both negatively and positively to intensification. 5. Synthesis and applications . The hierarchical model described here provides a powerful method for estimating individual plant responses and identifying how species' traits influence those responses. Plant species native to southern Australia are sensitive to grazing and phosphorous apparently due to a shared evolutionary history of low grazing intensity and low phosphorous soils. Invading exotic plants have faced strongly contrasting ecological filters, leading to a greater diversity of responses. Where grazing systems have been most intense, a small suite of exotics dominate. Maintaining native and functional plant diversity will necessitate limits being placed on intensive livestock management systems.
Aim Population viability analysis (PVA) is used to quantify the risks faced by species under alternative management regimes. Bayesian PVAs allow uncertainty in the parameters of the underlying population model to be easily propagated through to the predictions. We developed a Bayesian stochastic patch occupancy model (SPOM) and used this model to assess the viability of a metapopulation of the growling grass frog (Litoria raniformis) under different urbanization scenarios.Location Melbourne, Victoria, Australia. MethodsWe fitted a Bayesian model that accounted for imperfect detection to a multiseason occupancy dataset for L. raniformis collected across northern Melbourne. The probability of extinction was modelled as a function of effective wetland area, aquatic vegetation cover and connectivity, using logistic regression. The probability of colonization was modelled as a function of connectivity alone. We then simulated the dynamics of a metapopulation of L. raniformis subject to differing levels of urbanization and compensatory wetland creation. Uncertainty was propagated by conducting simulations for 5000 estimates of the parameters of the models for extinction and colonization.Results There was considerable uncertainty in both the probability of quasiextinction and the minimum number of occupied wetlands under most urbanization scenarios. Uncertainty around the change in quasi-extinction risk and minimum metapopulation size increased with increasing habitat loss. For our focal metapopulation, the analysis revealed that significant investment in new wetlands may be required to offset the impacts of urbanization.Main conclusions Bayesian approaches to PVA allow parametric uncertainty to be propagated and considered in management decisions. They also provide means of identifying parameters that represent critical uncertainties, and, through the use of informative priors, can easily assimilate new data to reduce parametric uncertainty. These advantages, and the ready availability of software to run Bayesian analyses, will ensure that Bayesian approaches are used increasingly for PVAs.
Metapopulation persistence in fragmented landscapes depends on habitat patches that can support resilient local populations and sufficient connectivity between patches. Yet epidemiological theory for metapopulations has largely overlooked the capacity of particular patches to act as refuges from disease, and has suggested that connectivity can undermine persistence. Here, we show that relatively warm and saline wetlands are environmental refuges from chytridiomycosis for an endangered Australian frog, and act jointly with connectivity to sustain frog metapopulations. We coupled models of microclimate and infection probability to map chytrid prevalence, and demonstrate a strong negative relationship between chytrid prevalence and the persistence of frog populations. Simulations confirm that frog metapopulations are likely to go extinct when they lack environmental refuges from disease and lose connectivity between patches. This study demonstrates that environmental heterogeneity can mediate host-pathogen interactions in fragmented landscapes, and provides evidence that connectivity principally supports host metapopulations afflicted by facultative pathogens.
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