Emergent conservation outcomes of shared risk perception in human-wildlife systems

Human perception of risks related to economic damages caused by nearby wildlife can be transmitted through social networks. Understanding how sharing risk information within a human community alters the spatial dynamics of human-wildlife interactions has important implications for the design and implementation of effective conservation actions. We developed an agent-based model that simulates farmer livelihood decisions and activities in an agricultural landscape shared with a population of a generic wildlife species (wildlife-human interactions in shared landscapes [WHISL]). In the model, based on risk perception and economic information, farmers decide how much labor to allocate to farming and whether and where to exclude wildlife from their farms (e.g., through fencing, trenches, or vegetation thinning). In scenarios where the risk perception of farmers was strongly influenced by other farmers, exclusion of wildlife was widespread, resulting in decreased quality of wildlife habitat and frequency of wildlife damages across the landscape. When economic losses from encounters with wildlife were high, perception of risk increased and led to highly synchronous behaviors by farmers in space and time. Interactions between wildlife and farmers sometimes led to a spillover effect of wildlife damage displaced from socially and spatially connected communities to less connected neighboring farms. The WHISL model is a useful conservation-planning tool because it provides a test bed for theories and predictions about human-wildlife dynamics across a range of different agricultural landscapes.     

Priority areas for conservation of and research focused on terrestrial vertebrates

Effective conservation policies require comprehensive knowledge of biodiversity. However, knowledge shortfalls still remain, hindering possibilities to improve decision making and built such policies. During the last 2 decades, conservationists have made great efforts to allocate resources as efficiently as possible but have rarely considered the idea that if research investments are also strategically allocated, it would likely fill knowledge gaps while simultaneously improving conservation actions. Therefore, prioritizing areas where both conservation and research actions could be conducted becomes a critical endeavor that can further maximize return on investment. We used Zonation, a conservation planning tool and geographical distributions of amphibians, birds, mammals, and reptiles to suggest and compare priority areas for conservation and research of terrestrial vertebrates worldwide. We also evaluated the degree of human disturbance in both types of priority areas by describing the value of the human footprint index within such areas. The spatial concordance between priority conservation and research areas was low: 0.36% of the world's land area. In these areas, we found it would be possible to protect almost half of the currently threatened species and to gather information on nearly 42% of data-deficient (DD) species. We also found that 6199 protected areas worldwide are located in such places, although only 35% of them have strict conservation purposes. Areas of consensus between conservation and research areas represent an opportunity for simultaneously conserving and acquiring knowledge of threatened and DD species of vertebrates. Although the picture is not the most encouraging, joint conservation and research efforts are possible and should be fostered to save vertebrate species from our own ignorance and extinction.     

Minimizing the cost of translocation failure with decision‐tree models that predict species’ behavioral response in translocation sites

The high number of failures is one reason why translocation is often not recommended. Considering how behavior changes during translocations may improve translocation success. To derive decision‐tree models for species’ translocation, we used data on the short‐term responses of an endangered Australian skink in 5 simulated translocations with different release conditions. We used 4 different decision‐tree algorithms (decision tree, decision‐tree parallel, decision stump, and random forest) with 4 different criteria (gain ratio, information gain, gini index, and accuracy) to investigate how environmental and behavioral parameters may affect the success of a translocation. We assumed behavioral changes that increased dispersal away from a release site would reduce translocation success. The trees became more complex when we included all behavioral parameters as attributes, but these trees yielded more detailed information about why and how dispersal occurred. According to these complex trees, there were positive associations between some behavioral parameters, such as fight and dispersal, that showed there was a higher chance, for example, of dispersal among lizards that fought than among those that did not fight. Decision trees based on parameters related to release conditions were easier to understand and could be used by managers to make translocation decisions under different circumstances. Minimizar el Costo del Fracaso de la Reubicación con Modelos de Árboles de Decisión que Predigan la Respuesta Conductual de la Especie en los Sitios de Reubicación     

The need for spatially explicit quantification of benefits in invasive‐species management

Worldwide, invasive species are a leading driver of environmental change across terrestrial, marine, and freshwater environments and cost billions of dollars annually in ecological damages and economic losses. Resources limit invasive‐species control, and planning processes are needed to identify cost‐effective solutions. Thus, studies are increasingly considering spatially variable natural and socioeconomic assets (e.g., species persistence, recreational fishing) when planning the allocation of actions for invasive‐species management. There is a need to improve understanding of how such assets are considered in invasive‐species management. We reviewed over 1600 studies focused on management of invasive species, including flora and fauna. Eighty‐four of these studies were included in our final analysis because they focused on the prioritization of actions for invasive species management. Forty‐five percent (n = 38) of these studies were based on spatial optimization methods, and 35% (n = 13) accounted for spatially variable assets. Across all 84 optimization studies considered, 27% (n = 23) explicitly accounted for spatially variable assets. Based on our findings, we further explored the potential costs and benefits to invasive species management when spatially variable assets are explicitly considered or not. To include spatially variable assets in decision‐making processes that guide invasive‐species management there is a need to quantify environmental responses to invasive species and to enhance understanding of potential impacts of invasive species on different natural or socioeconomic assets. We suggest these gaps could be filled by systematic reviews, quantifying invasive species impacts on native species at different periods, and broadening sources and enhancing sharing of knowledge.     

When and how to use Q methodology to understand perspectives in conservation research

Understanding human perspectives is critical in a range of conservation contexts, for example, in overcoming conflicts or developing projects that are acceptable to relevant stakeholders. The Q methodology is a unique semiquantitative technique used to explore human perspectives. It has been applied for decades in other disciplines and recently gained traction in conservation. This paper helps researchers assess when Q is useful for a given conservation question and what its use involves. To do so, we explained the steps necessary to conduct a Q study, from the research design to the interpretation of results. We provided recommendations to minimize biases in conducting a Q study, which can affect mostly when designing the study and collecting the data. We conducted a structured literature review of 52 studies to examine in what empirical conservation contexts Q has been used. Most studies were subnational or national cases, but some also address multinational or global questions. We found that Q has been applied to 4 broad types of conservation goals: addressing conflict, devising management alternatives, understanding policy acceptability, and critically reflecting on the values that implicitly influence research and practice. Through these applications, researchers found hidden views, understood opinions in depth and discovered points of consensus that facilitated unlocking difficult disagreements. The Q methodology has a clear procedure but is also flexible, allowing researchers explore long‐term views, or views about items other than statements, such as landscape images. We also found some inconsistencies in applying and, mainly, in reporting Q studies, whereby it was not possible to fully understand how the research was conducted or why some atypical research decisions had been taken in some studies. Accordingly, we suggest a reporting checklist.     

Environmental cost of using poor decision metrics to prioritize environmental projects

Conservation decision makers commonly use project‐scoring metrics that are inconsistent with theory on optimal ranking of projects. As a result, there may often be a loss of environmental benefits. We estimated the magnitudes of these losses for various metrics that deviate from theory in ways that are common in practice. These metrics included cases where relevant variables were omitted from the benefits metric, project costs were omitted, and benefits were calculated using a faulty functional form. We estimated distributions of parameters from 129 environmental projects from Australia, New Zealand, and Italy for which detailed analyses had been completed previously. The cost of using poor prioritization metrics (in terms of lost environmental values) was often high—up to 80% in the scenarios we examined. The cost in percentage terms was greater when the budget was smaller. The most costly errors were omitting information about environmental values (up to 31% loss of environmental values), omitting project costs (up to 35% loss), omitting the effectiveness of management actions (up to 9% loss), and using a weighted‐additive decision metric for variables that should be multiplied (up to 23% loss). The latter 3 are errors that occur commonly in real‐world decision metrics, in combination often reducing potential benefits from conservation investments by 30–50%. Uncertainty about parameter values also reduced the benefits from investments in conservation projects but often not by as much as faulty prioritization metrics.     

Getting caught up in the game: managing non-formal dynamics in the remediation of contaminated sediments in Oslo harbor

This study aims at describing, analyzing and evaluating the relation between management styles and process dynamics of a complex planning process confronted with unexpected dynamics. The development of an aquatic disposal site for dredged contaminated sediments in Oslo was managed by a project management style focused on timely and cost-effective implementation. Coupling the remediation project with another infrastructural project and the actual construction of the site led to unexpected dynamics in terms of resistance and controversy. Project management had difficulties in adjusting its style accordingly, resulting in even more delay and resistance. Managing complex planning projects requires a style suitable to the characteristics of the project and the capability of adjusting it to changing circumstances. The paper concludes with some explanations why it is difficult to change management styles in complex planning and implementation processes and complexity-embracing approaches to deal with this.     

A spatially explicit backcasting approach for sustainable land-use planning

General backcasting as a decision support and planning method starts from desired future states and simulates developments backwards until reaching the present state. Development pathways that reveal steps to be taken to reach a certain future state, and milestones that serve as interim goals, are created during the process. Backcasting has hitherto only been applied in workshops or as a theoretical framework and no spatially explicit backcasting model has previously been established. This paper presents the development of a spatially explicit backcasting model. The proposed model first creates a future scenario utilizing an agent-based model and then simulates backwards. It is implemented using the programming language Python. The model has been applied to a case study for sustainable land-use planning in Salzburg, Austria. The results of the model run show a successful backcasting of land-use classes from a future state back to the present, in 10 year time steps.     

Ecosystem services assessments in local municipal decision making in South Africa: justification for the use of a business-based approach

The ecosystem services (ES) concept is being increasingly incorporated into environmental policy formulation and management approaches. The Corporate Ecosystem Services Review (ESR) is a framework used to assess the dependence and impact that a business has on ES. The success of the corporate experience of ES assessment provides an opportunity for adaption for local authority decision making. In this paper, the ESR tool was adapted to the South African setting at a local government level, and tested at two sites in the Msunduzi Municipality, KwaZulu-Natal. In testing the tool and gathering feedback from key stakeholders, it was found that there are both opportunities and challenges to this approach. Overall, however, it provides an opportunity for the systematic inclusion of ES assessment into existing regulatory frameworks for land-use planning and Integrated Environmental Management, whether in a strategic application, at a broader spatial (municipal) scale or in a specific locale within the municipality.     

基于BDD考虑共因失效的接触网系统可靠性分析

为分析共因失效对高速铁路接触网系统的影响，将二元决策图(Binary Decision Diagram，BDD)与共因失效理论引入到接触网系统可靠性分析中。利用逻辑相邻优先组合法(Logic Neighbor Priority Connect，LNPC)将高速铁路接触网系统的故障树模型转化为BDD模型并求取其可靠度表达式，利用隐式方法对考虑了共因失效的接触网系统可靠度进行计算，利用MATLAB绘制考虑共因失效和不考虑共因失效情况下接触网系统可靠度变化曲线。研究结果表明:提出的分析方法适用于接触网系统的可靠性分析，为接触网系统的可靠性分析提供了一定的理论依据。