Identifying Preservation and Restoration Priority Areas for Desert Fishes in an Increasingly Invaded World

A commonly overlooked aspect of conservation planning assessments is that wildlife managers are increasingly focused on habitats that contain non-native species. We examine this management challenge in the Gila River basin (150,730 km²), and present a new planning strategy for fish conservation. By applying a hierarchical prioritization algorithm to >850,000 fish records in 27,181 sub-watersheds we first identified high priority areas (PAs) termed “preservation PAs” with high native fish richness and low non-native richness; these represent traditional conservation targets. Second, we identified “restoration PAs” with high native fish richness that also contained high numbers of non-native species; these represent less traditional conservation targets. The top 10 % of preservation and restoration PAs contained common native species (e.g., Catostomus clarkii, desert sucker; Catostomus insignis, Sonora sucker) in addition to native species with limited distributions (i.e., Xyrauchen texanus, razorback sucker; Oncorhynchus gilae apache, Apache trout). The top preservation and restoration PAs overlapped by 42 %, indicating areas with high native fish richness range from minimally to highly invaded. Areas exclusively identified as restoration PAs also encompassed a greater percentage of native species ranges than would be expected by the random addition of an equivalent basin area. Restoration PAs identified an additional 19.0 and 26.6 % of the total ranges of two federally endangered species—Meda fulgida (spikedace) and Gila intermedia (Gila chub), respectively, compared to top preservation PAs alone—despite adding only 5.8 % of basin area. We contend that in addition to preservation PAs, restoration PAs are well suited for complementary management activities benefiting native fishes.     

The evolution of Müllerian mimicry

It is now 130 years since Fritz Müller proposed an evolutionary explanation for the close similarity of co-existing unpalatable prey species, a phenomenon now known as Müllerian mimicry. Müller's hypothesis was that unpalatable species evolve a similar appearance to reduce the mortality involved in training predators to avoid them, and he backed up his arguments with a mathematical model in which predators attack a fixed number (n) of each distinct unpalatable type in a given season before avoiding them. Here, I review what has since been discovered about Müllerian mimicry and consider in particular its relationship to other forms of mimicry. Müller's specific model of associative learning involving a "fixed n" in a given season has not been supported, and several experiments now suggest that two distinct unpalatable prey types may be just as easy to learn to avoid as one. Nevertheless, Müller's general insight that novel unpalatable forms have higher mortality than common unpalatable forms as a result of predation has been well supported by field experiments. From its inception, there has been a heated debate over the nature of the relationship between Müllerian co-mimics that differ in their level of defence. There is now a growing awareness that this relationship can be mediated by many factors, including synergistic effects between co-mimics that differ in their mode of defence, rates of generalisation among warning signals and concomitant changes in prey density as mimicry evolves. I highlight areas for future enquiry, including the possibility of Müllerian mimicry systems based on profitability rather than unprofitability and the co-evolution of defence.     

A resilience-based approach for comparing expert preferences across two large-scale coastal management programs

This report proposes a method for assessing resilience-building components in coastal social–ecological systems. Using the proposed model, the preferences of experts in Masan Bay (South Korea) and Puget Sound (USA) are compared. A total of 30 management objectives were determined and used to build a hierarchic tree designed using the principles of the Analytic Hierarchy Process (AHP). Surveys were performed with 35 Puget Sound experts using face-to-face interviews and with 28 Masan Bay experts by mail. The results demonstrate that the legal objective, which enables legislation, was the highest preferred component in both regions. The knowledge translation variable was also given a high preference score in both regions. An analysis of variance (ANOVA) showed that the Puget Sound experts significantly favored attention to education, habitat restoration and species protection objectives in comparison to the Masan Bay experts. The Masan Bay experts placed greater emphasis on legislation and the type of institutional design than did the Puget Sound experts. Using cluster analysis, four distinct groups of respondents were independently identified in Puget Sound and three groups were identified in Masan Bay. One unique subgroup in the Puget Sound experts group, which was characterized by its high preferences for habitat restoration and species protection, was not observed in Masan Bay. Demographic variables (length of career and role in coastal issue) failed to account for the differences in groupings and preferences in either region, except for the variable ‘favoring information source’ in the Puget Sound group. This finding implies that the demographic information was not related to differences in group opinions in both regions. The analysis framework presented here was effective in identifying expert preferences regarding the overall structure and emphasis in coastal management programs. Thus, this framework can be applied towards coastal policy development.     

How well do predators adjust to climate-mediated shifts in prey distribution? A study on Australian water pythons

Climate change can move the spatial location of resources critical for population viability, and a species' resilience to such changes will depend upon its ability to flexibly shift its activities away from no-longer-suitable sites to exploit new opportunities. Intuition suggests that vagile predators should be able to track spatial shifts in prey availability, but our data on water pythons (Liasisfuscus) in tropical Australia suggest a less encouraging scenario. These pythons undergo regular long-range (to >10 kmin) seasonal migrations to follow flooding-induced migrations by their prey (native dusky rats, Rattus colletti). However, when an extreme flooding event virtually eliminated rats for a three-year period, the local pythons did not disperse despite the presence of abundant rats only 8 km away; instead, many pythons starved to death. This inflexibility suggests that some vagile species that track seasonally migrating prey may do so by responding to habitat attributes that have consistently predicted prey availability over evolutionary time, rather than reacting to proximate cues that signal the presence of prey per se. A species' vulnerability to climate change will be increased by an inability to shift its activities away from historical sites toward newly favorable areas.     

River network structure shapes interannual feedbacks between adult sea lamprey migration and larval habitation

Adult sea lampreys (Petromyzon marinus) migrating upstream to spawn follow a pheromone released by instream larvae. The size (i.e. flow) of a tributary dilutes the concentration of this pheromone, such that the downstream propagation pattern of larval pheromone must be influenced by patterns in the relative sizes and numbers of confluent tributaries. We developed an individual-based model to explicitly test the resulting hypothesis that river network structure influences the migration decisions of adult lampreys following the larval pheromone, and in turn the distribution of larvae. First, we initialized the model using randomly generated river networks, and found a strong positive relationship between network diameter and larval aggregation. Larvae aggregated over time, and the degree and rate of this aggregation depended on network diameter. Second, we initialized the model using a river network based on the Muskegon River, Michigan, and compared model-generated larval distribution to available field survey data. We found a significant correlation between model-generated larval abundance and field-measured larval densities (r₂ = 0.54; p < 0.0001). We also found an inverse relationship between subwatershed area and the degree to which path-dependent effects influenced larval abundance in that subwatershed. Our results overall suggest that larval distribution across a watershed results from a system of context-dependent interannual feedbacks shaped by network structure and the past migratory and spawning behavior of adults.     

Modelling landscape effects on density-contact rate relationships of deer in eastern Alberta: Implications for chronic wasting disease

Managing wildlife diseases requires an understanding of disease transmission, which may be strongly affected by host population density and landscape features. Transmission models are typically fit from time-series disease prevalence data and modelled based on how the contact rate among hosts is affected by density, which is often assumed to be a linear (density-dependent transmission) or constant (frequency-dependent transmission) relationship. However, long-term time-series data is unavailable for emerging diseases, and this approach cannot account for independent effects of landscape. We developed a mechanistic model based on ecological data to empirically derive the contact rate-density relationship in white-tailed and mule deer in an enzootic region of chronic wasting disease (CWD) in Alberta, Canada and to determine whether it was affected by landscape. Using data collected from aerial surveys and GPS-telemetry, we developed empirical relationships predicting deer group size, home range size, and habitat selection to iteratively simulate deer distributions across a range of densities and landscapes. We calculated a relative measure of total per-capita contact rate, which is proportional to the number of other deer contacted per individual per unit time, for each distribution as the sum of pairwise contact rates between a target deer and all other individuals. Each pairwise contact rate was estimated from an empirical relationship developed from GPS-telemetry data predicting pairwise contact rates as a function of home range overlap and landscape structure. Total per-capita contact rates increased as a saturating function of density, supporting a transmission model intermediate between density- and frequency-dependent transmission. This pattern resulted from group sizes that reached an asymptote with increasing deer density, although this relationship was mediated by tree and shrub coverage in the landscape, such that in heavily wooded areas, the contact rate saturated at much lower densities. These results suggest that CWD management based on herd reductions, which require a density-dependent contact rate to be effective, may have variable effects on disease across a single management region. The novel mechanistic approach we employed for estimating effects of density and landscape on transmission is a powerful complement to typical data-fitting approaches for modelling disease transmission.     

A general approach to the analysis of habitat selection

The investigation of animal habitat selection aims at the detection of selective usage of habitat types and the identification of covariates influencing their selection. The results not only allow for a better understanding of the habitat selection process but are also intended to help improve the conservation of animals. Usually, habitat selection by larger animals is assessed by radio-tracking or visual observation studies, where the chosen habitat is determined for some animals at a set of specific points in time. Hence the resulting data often have the following structure: a categorical variable indicating the habitat type selected by an animal at a specific point in time is repeatedly observed and will be explained by covariates. These may either describe properties of the habitat types currently available and/or properties of the animal. In this paper, we present a general approach to the analysis of such data in a categorical regression setup. The proposed model generalizes and improves upon several of the approaches previously discussed in the literature. In particular, it accounts for changing habitat availability due to the movement of animals within the observation area. It incorporates both habitat- and animal-specific covariates, and includes individual-specific random effects to account for correlations introduced by the repeated measurements on single animals. Furthermore, the assumption that the effects are linear can be dropped by including the effects in nonparametric manner based on a penalized spline approach. The methodology is implemented in a freely available software package. We demonstrate the general applicability and the potential of the proposed approach in two case studies: The analysis of a songbird community in South-America and a study on brown bears in Central Europe.     

Leaf ontogeny interacts with Bt modification to affect innate resistance in GM aspens

Bioassays with a non-target slug (Deroceras spp.) and chemical analyses were conducted using leaf tissue from already existing genetically modified insect-resistant aspen trees to examine whether genetic modifications to produce Bacillus thuringiensis (Bt) toxins could affect plant phytochemistry, which in turn might influence plant–herbivore interactions. Three major patterns emerged. First, two independent modifications for Bt resistance affected the phytochemical profiles of leaves such that both were different from the isogenic wild-type (Wt) control leaves, but also different from each other. Among the contributors to these differences are substances with a presumed involvement in resistance, such as salicortin and soluble condensed tannins. Second, bioassays with one Bt line suggest that the modification somehow affected innate resistance (“Innate” is used here in opposition to the “acquired” Bt resistance) in ways such that slugs preferred Bt over Wt leaves. Third, the preference test suggests that the innate resistance in Bt relative to Wt plants may not be uniformly expressed throughout the whole plant and that leaf ontogeny interacts with the modification to affect resistance. This was manifested through an ontogenetic determined increase in leaf consumption that was more than four times higher in Bt compared to Wt leaves. Our result are of principal importance, as these indicate that genetic modifications can affect innate resistance and thus non-target herbivores in ways that may have commercial and/or environmental consequences. The finding of a modification–ontogeny interaction effect on innate resistance may be especially important in assessments of GM plants with a long lifespan such as trees.     

A uniform fish consumption advisory protocol for the Ohio River

ORSANCO and the six Ohio River main stem states have been working to align states' fish consumption advisories (FCAs) to enhance the value of advice issued to the public. To achieve this goal, ORSANCO worked closely with a panel consisting of state and USEPA representatives. The result of this effort is the Ohio River Fish Consumption Advisory Protocol (ORFCAP). The ORFCAP represents a single set of variables agreed upon by the panel that allows for a standardized protocol to create advisory thresholds to which states can defer to issue consumption advice for the Ohio River. The ORFCAP identifies ORSANCO as a clearinghouse for data which will be distributed to the panel for decision making. Other components include identifying primary contaminants of concern (PCBs and mercury) and dividing the river into four reporting units. The protocol was developed to issue FCAs for the protection of sensitive populations using five advisory groupings for PCBs and four for mercury. Specific variables used in the calculation of advisory thresholds such as health protection values, cooking reductions, average meal sizes, etc., were selected by the panel. Lastly, the protocol calls for FCA decisions to be based on analysis of the most recent 10?years of data for each species in each reporting unit to determine size class needs and advisory groupings. Upon pending implementation of the protocol by the main stem states, these decisions will be made annually through a series of discussions involving ORSANCO, the panel, and other appropriate state personnel.