Defining Landscape Resistance Values in Least-Cost Connectivity Models for the Invasive Grey Squirrel: A Comparison of Approaches Using Expert-Opinion and Habitat Suitability Modelling

Least-cost models are widely used to study the functional connectivity of habitat within a varied landscape matrix. A critical step in the process is identifying resistance values for each land cover based upon the facilitating or impeding impact on species movement. Ideally resistance values would be parameterised with empirical data, but due to a shortage of such information, expert-opinion is often used. However, the use of expert-opinion is seen as subjective, human-centric and unreliable. This study derived resistance values from grey squirrel habitat suitability models (HSM) in order to compare the utility and validity of this approach with more traditional, expert-led methods. Models were built and tested with MaxEnt, using squirrel presence records and a categorical land cover map for Cumbria, UK. Predictions on the likelihood of squirrel occurrence within each land cover type were inverted, providing resistance values which were used to parameterise a leastcost model. The resulting habitat networks were measured and compared to those derived from a least-cost model built with previously collated information from experts. The expert-derived and HSM-inferred least-cost networks differ in precision. The HSM-informed networks were smaller and more fragmented because of the higher resistance values attributed to most habitats. These results are discussed in relation to the applicability of both approaches for conservation and management objectives, providing guidance to researchers and practitioners attempting to apply and interpret a leastcost approach to mapping ecological networks.This project was funded by the Forestry Commission GB and the National School of Forestry at the University of Cumbria. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Niches for Species, a multi-species model to guide woodland management: An example based on Scotland's native woodlands

Designating and managing areas with the aim of protecting biodiversity requires information on species distributions and habitat associations, but a lack of reliable occurrence records for rare and threatened species precludes robust empirical modelling. Managers of Scotland’s native woodlands are obliged to consider 208 protected species, which each have their own, narrow niche requirements. To support decision-making, we developed Niches for Species (N4S), a model that uses expert knowledge to predict the potential occurrence of 179 woodland protected species representing a range of taxa: mammals, birds, invertebrates, fungi, bryophytes, lichens and vascular plants. Few existing knowledge-based models have attempted to include so many species. We collated knowledge to define each species’ suitable habitat according to a hierarchical habitat classification: woodland type, stand structure and microhabitat. Various spatial environmental datasets were used singly or in combination to classify and map Scotland’s native woodlands accordingly, thus allowing predictive mapping of each species’ potential niche. We illustrate how the outputs can inform individual species management, or can be summarised across species and regions to provide an indicator of woodland biodiversity potential for landscape scale decisions. We tested the model for ten species using available occurrence records. Although concordance between predicted and observed distributions was indicated for nine of these species, this relationship was statistically significant in only five cases. We discuss the difficulties in reliably testing predictions when the records available for rare species are typically low in number, patchy and biased, and suggest future model improvements. Finally, we demonstrate how using N4S to synthesise complex, multi-species information into an easily digestible format can help policy makers and practitioners consider large numbers of species and their conservation needs

Predicting hedgehog mortality risks on British roads using habitat suitability modelling

Road vehicle collisions are likely to be an important contributory factor in the decline of the European hedgehog (Erinaceus europaeus) in Britain. Here, a collaborative roadkill dataset collected from multiple projects across Britain was used to assess when, where and why hedgehog roadkill are more likely to occur. Seasonal trends were assessed using a Generalized Additive Model. There were few casualties in winter—the hibernation season for hedgehogs—with a gradual increase from February that reached a peak in July before declining thereafter. A sequential multi-level Habitat Suitability Modelling (HSM) framework was then used to identify areas showing a high probability of hedgehog roadkill occurrence throughout the entire British road network (∼400,000 km) based on multi-scale environmental determinants. The HSM predicted that grassland and urban habitat coverage were important in predicting the probability of roadkill at a national scale. Probabilities peaked at approximately 50% urban cover at a one km scale and increased linearly with grassland cover (improved and rough grassland). Areas predicted to experience high probabilities of hedgehog roadkill occurrence were therefore in urban and suburban environments, that is, where a mix of urban and grassland habitats occur. These areas covered 9% of the total British road network. In combination with information on the frequency with which particular locations have hedgehog road casualties, the framework can help to identify priority areas for mitigation measures

UK landscape ecology: trends and perspectives from the first 25 years of ialeUK

Context The 25th anniversary of the founding of the UK chapter of the International Association for Landscape Ecology (ialeUK) was marked in 2017. Objectives To assess trends in UK landscape ecology research over ialeUK’s first 25 years, to compare these trends to changes elsewhere in the world, and to consider how ialeUK can continue to support landscape ecology research and practice. Methods A database of conference abstracts was compiled and examined in combination with a questionnaire that surveyed existing and former active members of ialeUK. Results Across 1992–2017 we observe noticeable trends including the declining roles of statutory bodies, the development of the ecosystem services concept, and a decrease in use of empirical methods. Analysis of questionnaire results highlighted four key areas: Developing new researchers; Facilitating conferences for networking, learning and discussion; Linking policy with practice; and Driving the continued growth of landscape ecology as a discipline. Challenges were also noted, especially regarding the adoption of a wider understanding of landscape ecological principles in management. Conclusions Increases in qualitative research, decreases in studies explicitly examining connectivity/fragmentation and an absence of landscape genetics studies in the UK are seemingly distinct from US landscape ecology and elsewhere around the world, based on published accounts. ialeUK has had success in increasing the role of landscape ecology in policy and practice, but needs to continue to aim for improved collaboration with other landscape-related professional bodies and contributions to wider sustainability agendas

An analytical framework for spatially targeted management of natural capital

A major sustainability challenge is determining where to target management to enhance natural capital and the ecosystem services it provides. Achieving this understanding is difficult, given that the effects of most actions vary according to wider environmental conditions; and this context dependency is typically poorly understood. Here, we describe an analytical framework that helps meet this challenge by identifying both why and where management actions are most effective for enhancing natural capital across large geographic areas. We illustrate the framework’s generality by applying it to two examples for Britain: pond water quality and invasion of forests by rhododendron

Knowledge sharing, problem solving and professional development in a Scottish Ecosystem Services Community of Practice

The ecosystem services framework has now been embodied in policy and practice, creating the need for governance structures that allow science, policy and practice to come together and facilitate shared learning. We describe five years of progress in developing an Ecosystem Services Community of Practice in Scotland, which brings together over 600 individuals from diverse constituencies to share experiences and learn from each other. We consider the ‘community’ and ‘practice’ aspects to demonstrate the benefits of establishing an Ecosystem Services Community (ESCom). We also demonstrate how the journey involved in the creation and continuing evolution of ESCom has proved valuable to researchers, policy-makers, practitioners and students and as such has contributed to social learning. We reflect on challenges, given the voluntary nature, absence of formal institutional support and emergence of initiatives focusing on overlapping topics. Based on our experience, we provide ten recommendations to help future ecosystem services communities of practice

Identifying postpartum intervention approaches to prevent type 2 diabetes in women with a history of gestational diabetes

<p>Abstract</p> <p>Background</p> <p>Women who develop gestational diabetes mellitus (GDM) have an increased risk for the development of type 2 diabetes. Despite this "window of opportunity," few intervention studies have targeted postpartum women with a history of GDM. We sought perspectives of women with a history of GDM to identify a) barriers and facilitators to healthy lifestyle changes postpartum, and b) specific intervention approaches that would facilitate participation in a postpartum lifestyle intervention program.</p> <p>Methods</p> <p>We used mixed methods to gather data from women with a prior history of GDM, including focus groups and informant interviews. Analysis of focus groups relied on grounded theory and used open-coding to categorize data by themes, while frequency distributions were used for the informant interviews.</p> <p>Results</p> <p>Of 38 women eligible to participate in focus groups, only ten women were able to accommodate their schedules to attend a focus group and 15 completed informant interviews by phone. We analyzed data from 25 women (mean age 35, mean pre-pregnancy BMI 28, 52% Caucasian, 20% African American, 12% Asian, 8% American Indian, 8% refused to specify). Themes from the focus groups included concern about developing type 2 diabetes, barriers to changing diet, and barriers to increasing physical activity. In one focus group, women expressed frustration about feeling judged by their physicians during their GDM pregnancy. Cited barriers to lifestyle change were identified from both methods, and included time and financial constraints, childcare duties, lack of motivation, fatigue, and obstacles at work. Informants suggested facilitators for lifestyle change, including nutrition education, accountability, exercise partners/groups, access to gyms with childcare, and home exercise equipment. All focus group and informant interview participants reported access to the internet, and the majority expressed interest in an intervention program delivered primarily via the internet that would include the opportunity to work with a lifestyle coach.</p> <p>Conclusion</p> <p>Time constraints were a major barrier. Our findings suggest that an internet-based lifestyle intervention program should be tested as a novel approach to prevent type 2 diabetes in postpartum women with a history of GDM.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01102530">NCT01102530</a></p