Evaluating the success of road-crossing mitigation for arboreal mammals: how does monitoring effort influence the detection of population-level effects?

© 2014 Dr. Kylie SoanesRoads and traffic threaten wildlife populations, fragmenting habitat, restricting animal movement and increasing mortality rates through roadkill. Millions of dollars are spent on crossing structures to reduce the impacts of roads on wildlife. Although the use of the structures has often been demonstrated, their success in mitigating population-level impacts is largely unknown. Crossing structures, such as canopy bridges, glider poles and vegetated medians, are increasingly installed to provide safe passage across roads for threatened arboreal marsupials. I evaluated the effectiveness of these methods for the squirrel glider (Petaurus norfolcensis) along the Hume Freeway in south-east Australia. Where the gap across the freeway exceeds 50 m squirrel gliders rarely attempt to cross, and those that do risk being killed by traffic. Canopy bridges and glider poles were retrofitted to 40-year-old sections of freeway in 2007, while vegetated medians had been present since the freeway was widened in the 1970s. Canopy bridges and glider poles were also installed along newly-widened sections of freeway at the time of road construction. I used motion-triggered cameras, PIT tag scanners, radiotracking and mark-recapture surveys to collect data on movement, gene flow and survival as part of a before-after-control-impact study (BACI). Motion-triggered cameras placed on canopy bridges and glider poles revealed that squirrel gliders and several other species of arboreal mammal used these structures to cross the freeway. The crossing rate increased over time, revealing a habituation period of approximately two-and-a-half years before crossing rates plateaued. Radiotracking suggested that the unmitigated freeway (treeless gap >50 m) was a barrier to squirrel glider movement relative to control sites (treeless gap <10 m). Vegetated medians, canopy bridges and glider poles all increased movement across the freeway, and retrofitted structures were able to re-establish movement at sites that were previously a barrier. However, it appeared that crossing structures only partially mitigated the barrier relative to control sites. Changes to gene flow were assessed through analysis of spatial genetic structure, assignment and parentage relationships. In contrast to the radiotracking results, genetic analyses revealed that the freeway was not a complete genetic barrier for squirrel gliders. Where genetic structuring occurred, the installation of crossing structures improved gene flow across the freeway. Further, parentage analysis revealed that individuals that used the crossing structures (as detected by radiotracking or PIT tag readers) had offspring on the opposite side, suggesting that the use of these structures can contribute to gene flow. Previous analysis of squirrel glider survival rates based on two-and-a-half years of surveys showed that the freeway reduced squirrel glider survival. However, when we repeated this analysis, including data collected over a longer survey period (six years), I found no difference in the survival rate of squirrel glider populations living adjacent to the freeway and those at non-freeway sites. This suggests that adult mortality at the freeway (e.g. through roadkill) is not high enough to affect squirrel gliders at the population level. Canopy bridges, glider poles and vegetated medians can improve connectivity between squirrel glider populations on either side of a freeway. However in this case they were not required to mitigate the effects of roadkill on squirrel glider survival rates. My work shows that survey duration and BACI study design are critical aspects of road ecology research. Studies that are too short or that lack 'before' data risk misinterpreting the impacts of roads on wildlife and the effectiveness of mitigation. Furthermore, genetic approaches provided a more comprehensive understanding of the impacts on movement and gene flow. When these principles are applied to population-level monitoring we gain a much better understanding of the importance and effectiveness of wildlife crossing structures

Genetic data for squirrel gliders (Petaurus norfolcensis) along the Hume Highway in south-east Australia 2005-2013_Soanes et al.csv

Genotype data for 399 squirrel gliders (Petaurus norfolcensis) at 8 micro satellite loci. The data support the publication "Evaluating the success of wildlife crossing structures using genetic approaches and an experimental design: lessons from a gliding mammal", Journal of Applied Ecology, 2017 (DOI to follow). Study was conducted along the Hume Highway in south-east Australia, 2005-2013. Data are provided for 13 sites divided into 4 treatment types, before and after crossing structures were added to a highway. Genotypes were first grouped into genetic regions (southern, central and northern) and then population structure within each region (among sites, sides of the highway, and time periods) were investigated. Contact Kylie Soanes for further information ([email protected]). Microsatellite loci are described in Millis 2000 (Molecular Ecology) and Soanes et al 2014 (Conservation Genetic Resources)

How to work with children and animals: A guide for school-based citizen science in wildlife research

Engaging school students in wildlife research through citizen science projects can be a win–win for scientists and educators. Not only does it provide a way for scientists to gather new data, but it can also con-tribute to science education and help younger generations become more environmentally aware. However, wild-life research can be challenging in the best of circumstances, and there are few guidelines available to help scientists create successful citizen science projects for school students. This paper explores the opportunities and challenges faced when developing school-based citizen science projects in wildlife research by synthesising two sources of information. First, we conducted a small, school-based citizen science project that investigated the effects of supplementary feeding on urban birds as a case study. Second, we reviewed the literature to develop a database of school-based citizen science projects that address questions in wildlife ecology and conservation. Based on these activities, we present five lessons for scientists considering a school-based citizen science project. Overall, we found that school-based citizen science projects must be carefully designed to ensure reliable data are collected, students remain engaged, and the project is achievable under the logistical constraints presented by conducting wildlife research in a school environment. Ultimately, we conclude that school-based citizen science projects can be a powerful way of collecting wildlife data while also contributing to the education and development of environmentally aware students

Ecological connectivity as a planning tool for the conservation of wildlife in cities

The application of ecological theory in urban planning is becoming more important as land managers focus on increasing biodiversity to improve human welfare in cities. Authorities must decide not only what types of biodiversity-focused infrastructure should be prioritized, but also where new resources should be positioned and existing resources protected or enhanced. Measuring the contribution of green infrastructure to landscape connectivity can maximise the successful return and conservation of urban nature. By using ecological connectivity theory as a planning tool, the effect of different interventions (both positive and negative) on the ease with which wildlife can move across the landscape can be compared. Here we outline an approach to a) quantify ecological connectivity for different urban wildlife species and b) use this to test different urban planning scenarios using QGIS. We demonstrate extensions which improve the application of this method as a planning tool: • Conversion of the effective mesh size value (meff) to a “probability of connectedness” (Pc, for easier interpretation by local government and comparisons between planning scenarios). • An approach for measuring species-specific connectivity, including how to decide what spatial information should be included and which types of species might be most responsive to connectivity planning. • Guidance for using the method to compare different urban planning scenarios

How effective is road mitigation at reducing road-kill? A meta-analysis

Road traffic kills hundreds of millions of animals every year, posing a critical threat to the populations of many species. To address this problem there are more than forty types of road mitigation measures available that aim to reduce wildlife mortality on roads (road-kill). For road planners, deciding on what mitigation method to use has been problematic because there is little good information about the relative effectiveness of these measures in reducing road-kill, and the costs of these measures vary greatly. We conducted a metaanalysis using data from 50 studies that quantified the relationship between road-kill and a mitigation measure designed to reduce road-kill. Overall, mitigation measures reduce roadkill by 40% compared to controls. Fences, with or without crossing structures, reduce roadkill by 54%. We found no detectable effect on road-kill of crossing structures without fencing. We found that comparatively expensive mitigation measures reduce large mammal road-kill much more than inexpensive measures. For example, the combination of fencing and crossing structures led to an 83% reduction in road-kill of large mammals, compared to a 57% reduction for animal detection systems, and only a 1% for wildlife reflectors. We suggest that inexpensive measures such as reflectors should not be used until and unless their effectiveness is tested using a high-quality experimental approach. Our meta-analysis also highlights the fact that there are insufficient data to answer many of the most pressing questions that road planners ask about the effectiveness of road mitigation measures, such as whether other less common mitigation measures (e.g., measures to reduce traffic volume and/or speed) reduce road mortality, or to what extent the attributes of crossing structures and fences influence their effectiveness. To improve evaluations of mitigation effectiveness, studies should incorporate data collection before the mitigation is applied, and we recommend a minimum study duration of four years for Before-After, and a minimum of either four years or four sites for Before-After-Control-Impact designs.</p

Conserving urban biodiversity: Current practice, barriers, and enablers

Abstract Urban biodiversity conservation is critical if cities are to tackle the biodiversity‐extinction crisis and connect people with nature. However, little attention has been paid to how urban environmental managers navigate complex socio‐ecological contexts to conserve biodiversity in cities. We interviewed environmental managers from Australian cities to identify (1) the breadth of conservation actions undertaken and (2) the barriers and enablers to action. We found current practice to be more diverse, innovative, and proactive than previously described (318 actions across nine categories). Conversely, priority actions identified by the literature are yet to be “mainstream” in practice (e.g., designing for human–nature connection, securing space for nature in cities). Further, we identified a suite of levers to overcome barriers. Our research provides scientists and practitioners with an understanding of the multiple facets of conservation in cities and emphasizes the importance of interdisciplinary approaches in future research and practice

Experimental study designs to improve the evaluation of road mitigation measures for wildlife

An experimental approach to road mitigation that maximizes inferential power is essential to ensure that mitigation is both ecologically-effective and cost-effective. Here, we set out the need for and standards of using an experimental approach to road mitigation, in order to improve knowledge of the influence of mitigation measures on wildlife populations. We point out two key areas that need to be considered when conducting mitigation experiments. First, researchers need to get involved at the earliest stage of the road or mitigation project to ensure the necessary planning and funds are available for conducting a high quality experiment. Second, experimentation will generate new knowledge about the parameters that influence mitigation effectiveness, which ultimately allows better prediction for future road mitigation projects. We identify seven key questions about mitigation structures (i.e., wildlife crossing structures and fencing) that remain largely or entirely unanswered at the population-level: (1) Does a given crossing structure work? What type and size of crossing structures should we use? (2) How many crossing structures should we build? (3) Is it more effective to install a small number of large-sized crossing structures or a large number of small-sized crossing structures? (4) How much barrier fencing is needed for a given length of road? (5) Do we need funnel fencing to lead animals to crossing structures, and how long does such fencing have to be? (6) How should we manage/manipulate the environment in the area around the crossing structures and fencing? (7) Where should we place crossing structures and barrier fencing? We provide experimental approaches to answering each of them using example Before-After-Control-Impact (BACI) study designs for two stages in the road/mitigation project where researchers may become involved: (1) at the beginning of a road/mitigation project, and (2) after the mitigation has been constructed; highlighting real case studies when available

Candidate predictor variables by category.

<p>Candidate predictor variables by category.</p

Number of studies (white bars) and effect size estimates (solid bars) in relation to (A) mitigation type, (B) crossing structure type, (C) fencing type, and (D) other mitigation types.

<p>Crossing: crossing structures; Crossing with fencing: combination of crossing structures and associated fencing; ADS: animal detection systems; Reflectors: wildlife reflectors; Other: other mitigation types e.g., wildlife warning signs; Mamm: mammal.</p

Relationship between weighted-mean effect sizes and the weighted-mean percent road-kill reduction for (A) study design, and (B) whether mortality data collected during construction of the mitigation measure was excluded, based on studies employing BA or BACI designs.

<p>Values in parentheses are the number of effect size estimates. Error bars indicate 95% confidence intervals.</p