An evaluation of two traps and sets for trapping the plains pocket gopher

We investigated the efficiency of DK-1 and Macabee® pocket gopher (Geomys bursarius) traps placed in lateral tunnels in both open and closed tunnel sets in rangeland and nonirrigated alfalfa fields in Nebraska. We observed no statistical difference between the traps in capture efficiency when used in open, versus closed, tunnel sets. Trapping of pocket gophers was more effective in rangeland (probability of capture in a single tunnel system using 3 traps; 63%) than nonirrigated alfalfa fields (26%). We did not determine whether this variance was due to behavioral differences between Geomys bursarius and Geomys lutescens. We found that trapping pocket gophers was species specific with only 1 nontarget animal harmed. We suggest modifications to the traps to improve gopher capture rate and lethality

Probabilistic movement model with emigration simulates movements of deer in Nebraska, 1990–2006

Movements of deer can affect population dynamics, spatial redistribution, and transmission and spread of diseases. Our goal was to model the movement of deer in Nebraska in an attempt to predict the potential for spread of chronic wasting disease (CWD) into eastern Nebraska. We collared and radio-tracked \u3e600 white-tailed deer (Odocoileus virginianus) and mule deer (Odocoileus hemionus) in Nebraska during 1990–2006.We observed large displacements (\u3e10 km) for both species and sexes of deer, including migrations up to 100 km and dispersals up to 50 km. Average distance traveled between successive daily locations was 166m for male and 173 for female deer in eastern Nebraska, and 427m for male and 459 for female deer in western Nebraska. Average daily displacement from initial capture point was 10m for male and 14m for female deer in eastern Nebraska, and 27m for male and 28m for female deer in western Nebraska.We used these data on naturally occurring movements to create and test 6 individual-based models of movement for white-tailed deer and mule deer in Nebraska, including models that incorporated sampling from empirical distributions of movement lengths and turn angles (DIST), correlated random walks (CRW), home point fidelity (FOCUS), shifting home point (SHIFT), probabilistic movement acceptance (MOVE), and probabilistic movement with emigration (MOVEwEMI). We created models in sequence in an attempt to account for the shortcomings of the previous model(s). We used the Kolmogrov–Smirnov goodness-of-fit test to verify improvement of simulated annual displacement distributions to empirical displacement distributions. The best-fit model (D = 0.07 and 0.08 for eastern and western Nebraska, respectively) included a probabilistic-movement chance with emigration (MOVEwEMI) and resulted in an optimal daily movement length of 350m (maximum daily movement length of 2800m for emigrators) for eastern Nebraska and 370m (maximum of 2960m) for western Nebraska. The proportion of deer that moved as emigrators was 0.10 and 0.13 for eastern and western Nebraska, respectively. We propose that the observed spread of CWD may be driven by large movements of a small proportion of deer that help to establish a low prevalence of the disease in areas east of the current endemic area. Our movement models will be used in a larger individual-based simulation of movement, survival, and transmission of CWD to help determine future surveillance and management actions

A proposed framework for the development and qualitative evaluation of West Nile virus models and their application to local public health decision-making

West Nile virus(WNV) is a globally distributed mosquito-borne virus of great public health concern. The number of WNV human cases and mosquito infection patterns vary in space and time. Many statistical models have been developed to understand and predict WNV geographic and temporal dynamics. However, these modeling efforts have been disjointed with little model comparison and inconsistent validation. In this paper, we describe a framework to unify and standardize WNV modeling efforts nationwide. WNV risk, detection, or warning models for this review were solicited from active research groups working in different regions of the United States. A total of 13 models were selected and described. The spatial and temporal scales of each model were compared to guide the timing and the locations for mosquito and virus surveillance, to support mosquito vector control decisions, and to assist in conducting public health outreach campaigns at multiple scales of decision-making. Our overarching goal is to bridge the existing gap between model development, which is usually conducted as an academic exercise, and practical model applications, which occur at state, tribal, local, or territorial public health and mosquito control agency levels. The proposed model assessment and comparison framework helps clarify the value of individual models for decision-making and identifies the appropriate temporal and spatial scope of each model. This qualitative evaluation clearly identifies gaps in linking models to applied decisions and sets the stage for a quantitative comparison of models. Specifically, whereas many coarse-grained models (county resolution or greater) have been developed, the greatest need is for fine-grained, short-term planning models (m–km, days–weeks) that remain scarce. We further recommend quantifying the value of information for each decision to identify decisions that would benefit most from model input

Are We Predicting the Actual or Apparent Distribution of Temperate Marine Fishes?

Planning for resilience is the focus of many marine conservation programs and initiatives. These efforts aim to inform conservation strategies for marine regions to ensure they have inbuilt capacity to retain biological diversity and ecological function in the face of global environmental change – particularly changes in climate and resource exploitation. In the absence of direct biological and ecological information for many marine species, scientists are increasingly using spatially-explicit, predictive-modeling approaches. Through the improved access to multibeam sonar and underwater video technology these models provide spatial predictions of the most suitable regions for an organism at resolutions previously not possible. However, sensible-looking, well-performing models can provide very different predictions of distribution depending on which occurrence dataset is used. To examine this, we construct species distribution models for nine temperate marine sedentary fishes for a 25.7 km2 study region off the coast of southeastern Australia. We use generalized linear model (GLM), generalized additive model (GAM) and maximum entropy (MAXENT) to build models based on co-located occurrence datasets derived from two underwater video methods (i.e. baited and towed video) and fine-scale multibeam sonar based seafloor habitat variables. Overall, this study found that the choice of modeling approach did not considerably influence the prediction of distributions based on the same occurrence dataset. However, greater dissimilarity between model predictions was observed across the nine fish taxa when the two occurrence datasets were compared (relative to models based on the same dataset). Based on these results it is difficult to draw any general trends in regards to which video method provides more reliable occurrence datasets. Nonetheless, we suggest predictions reflecting the species apparent distribution (i.e. a combination of species distribution and the probability of detecting it). Consequently, we also encourage researchers and marine managers to carefully interpret model predictions

Catastrophic Floods May Pave the Way for Increased Genetic Diversity in Endemic Artesian Spring Snail Populations

The role of disturbance in the promotion of biological heterogeneity is widely recognised and occurs at a variety of ecological and evolutionary scales. However, within species, the impact of disturbances that decimate populations are neither predicted nor known to result in conditions that promote genetic diversity. Directly examining the population genetic consequences of catastrophic disturbances however, is rarely possible, as it requires both longitudinal genetic data sets and serendipitous timing. Our long-term study of the endemic aquatic invertebrates of the artesian spring ecosystem of arid central Australia has presented such an opportunity. Here we show a catastrophic flood event, which caused a near total population crash in an aquatic snail species (Fonscochlea accepta) endemic to this ecosystem, may have led to enhanced levels of within species genetic diversity. Analyses of individuals sampled and genotyped from the same springs sampled both pre (1988–1990) and post (1995, 2002–2006) a devastating flood event in 1992, revealed significantly higher allelic richness, reduced temporal population structuring and greater effective population sizes in nearly all post flood populations. Our results suggest that the response of individual species to disturbance and severe population bottlenecks is likely to be highly idiosyncratic and may depend on both their ecology (whether they are resilient or resistant to disturbance) and the stability of the environmental conditions (i.e. frequency and intensity of disturbances) in which they have evolved

Adaptive Management of Riverine Socio-ecological Systems

If ongoing change in ecosystems and society can render inflexible policies obsolete, then management must dynamically adapt as a counter to perennial uncertainty. This chapter describes a general synthesis of how to make decision-making more adaptive and then explores the barriers to learning in management. We then describe how one such process, known as adaptive management (AM), has been applied in different river basins, on which basis we discuss AM’s strengths and limitations in various resource management contexts

Modelling Transmission of Vector-Borne Pathogens Shows Complex Dynamics When Vector Feeding Sites Are Limited

The relationship between species richness and the prevalence of vector-borne disease has been widely studied with a range of outcomes. Increasing the number of host species for a pathogen may decrease infection prevalence (dilution effect), increase it (amplification), or have no effect. We derive a general model, and a specific implementation, which show that when the number of vector feeding sites on each host is limiting, the effects on pathogen dynamics of host population size are more complex than previously thought. The model examines vector-borne disease in the presence of different host species that are either competent or incompetent (i.e. that cannot transmit the pathogen to vectors) as reservoirs for the pathogen. With a single host species present, the basic reproduction ratio R0 is a non-monotonic function of the population size of host individuals (H), i.e. a value exists that maximises R0. Surprisingly, if a reduction in host population size may actually increase R0. Extending this model to a two-host species system, incompetent individuals from the second host species can alter the value of which may reverse the effect on pathogen prevalence of host population reduction. We argue that when vector-feeding sites on hosts are limiting, the net effect of increasing host diversity might not be correctly predicted using simple frequency-dependent epidemiological models