Quantifying the expected value of uncertain management choices for over-abundant Greylag Geese

In many parts of the world, conservation successes or global anthropogenic changes have led to increasing native species populations that then compete with human resource use. In the Orkney Islands, Scotland, a 60-fold increase in Greylag Goose Anser anser numbers over 24 years has led to agricultural damages and culling attempts that have failed to prevent population increase. To address uncertainty about why populations have increased, we combined empirical modelling of possible drivers of Greylag Goose population change with expert-elicited benefits of alternative management actions to identify whether to learn versus act immediately to reduce damages by geese. We built linear mixed-effects models relating annual goose densities on farms to land-use and environmental covariates and estimated AICc model weights to indicate relative support for six hypotheses of change. We elicited from experts the expected likelihood that one of six actions would achieve an objective of halting goose population growth, given each hypothesis for population change. Model weights and expected effects of actions were combined in Value of Information analysis (VoI) to quantify the utility of resolving uncertainty in each hypothesis through adaptive management and monitoring. The action with the highest expected value under existing uncertainty was to increase the extent of low quality habitats, whereas assuming equal hypothesis weights changed the best action to culling. VoI analysis showed that the value of learning to resolve uncertainty in any individual hypothesis for goose population change was low, due to high support for a single hypothesis of change. Our study demonstrates a two-step framework that learns about the most likely drivers of change for an over-abundant species, and uses this knowledge to weight the utility of alternative management actions. Our approach helps inform which strategies might best be implemented to resolve uncertainty when there are competing hypotheses for change and competing management choices

Informed actions: Where to cost effectively manage multiple threats to species to maximize return on investment

Conservation practitioners, faced with managing multiple threats to biodiversity and limited funding, must prioritize investment in different management actions. From an economic perspective, it is routine practice to invest where the highest rate of return is expected. This return-on-investment (ROI) thinking can also benefit species conservation, and researchers are developing sophisticated approaches to support decision-making for cost-effective conservation. However, applied use of these approaches is limited. Managers may be wary of "black-box'' algorithms or complex methods that are difficult to explain to funding agencies. As an alternative, we demonstrate the use of a basic ROI analysis for determining where to invest in cost-effective management to address threats to species. This method can be applied using basic geographic information system and spreadsheet calculations. We illustrate the approach in a management action prioritization for a biodiverse region of eastern Australia. We use ROI to prioritize management actions for two threats to a suite of threatened species: habitat degradation by cattle grazing, and predation by invasive red foxes (Vulpes vulpes). We show how decisions based on cost-effective threat management depend upon how expected benefits to species are defined and how benefits and costs co-vary. By considering a combination of species richness, restricted habitats, species vulnerability, and costs of management actions, small investments can result in greater expected benefit compared with management decisions that consider only species richness. Furthermore, a landscape management strategy that implements multiple actions is more efficient than managing only for one threat, or more traditional approaches that don't consider ROI. Our approach provides transparent and logical decision support for prioritizing different actions intended to abate threats associated with multiple species; it is of use when managers need a justifiable and repeatable approach to investment

Source Spectra and Site Response from SWaves of Intermediate-Depth Vrancea (Romania) Earthquakes

Seismograms from 55 intermediate-depth Vrancea earthquakes (M=4.0- 7.1) recorded at 43 stations of an accelerometric network in Romania are used to derive source spectra and site amplification functions from S-waves in the frequency range 0.5-20 Hz with the generalized inversion technique (GIT) (Castro et al., 1990). Attenuation is taken into account using the nonparametric attenuation functions derived by Oth et al. (2008) from the same dataset, and the attenuation-corrected data are then split into source and site contributions. The source spectra follow the ω-2-model (Brune, 1970, 1971) with high corner frequencies and a related Brune stress drop of the order of 100 MPa. The site amplification functions are determined for both horizontal and vertical components separately. Contrary to wide-spread expectation the vertical component shows significant amplification effects at high frequencies. The H/Z ratios determined from the GIT results compare well with H/V ratios computed directly from the S-wave window of the accelerograms (Lermo and Chávez-García, 1993). The basic assumption for the determination of site effects from H/V ratios is that the vertical component is not or only little affected by site effects. For Vrancea earthquakes, this assumption is incorrect and consequently site effects should not be estimated from H/V ratios. The reason for this peculiar fact is the geometry of intermediate-depth seismicity that leads to almost vertical raypaths beneath the stations

The importance of incorporating functional habitats into conservation planning for highly mobile species in dynamic systems

The distribution of mobile species in dynamic systems can vary greatly over time and space. Estimating their population size and geographic range can be problematic and affect the accuracy of conservation assessments. Scarce data on mobile species and the resources they need can also limit the type of analytical approaches available to derive such estimates. We quantified change in availability and use of key ecological resources required for breeding for a critically endangered nomadic habitat specialist, the Swift Parrot (Lathamus discolor). We compared estimates of occupied habitat derived from dynamic presence-background (i.e., presence-only data) climatic models with estimates derived from dynamic occupancy models that included a direct measure of food availability. We then compared estimates that incorporate fine-resolution spatial data on the availability of key ecological resources (i.e., functional habitats) with more common approaches that focus on broader climatic suitability or vegetation cover (due to the absence of fine-resolution data). The occupancy models produced significantly (P < 0.001) smaller (up to an order of magnitude) and more spatially discrete estimates of the total occupied area than climate-based models. The spatial location and extent of the total area occupied with the occupancy models was highly variable between years (131 and 1498 km2 ). Estimates accounting for the area of functional habitats were significantly smaller (2-58% [SD 16]) than estimates based only on the total area occupied. An increase or decrease in the area of one functional habitat (foraging or nesting) did not necessarily correspond to an increase or decrease in the other. Thus, an increase in the extent of occupied area may not equate to improved habitat quality or function. We argue these patterns are typical for mobile resource specialists but often go unnoticed because of limited data over relevant spatial and temporal scales and lack of spatial data on the availability of key resources. Understanding changes in the relative availability of functional habitats is crucial to informing conservation planning and accurately assessing extinction risk for mobile resource specialists

Evaluating complementary networks of restoration plantings for landscape-scale occurrence of temporally dynamic species

Multibillion dollar investments in land restoration make it critical that conservation goals are achieved cost-effectively. Approaches developed for systematic conservation planning offer opportunities to evaluate landscape-scale, temporally dynamic biodiversity outcomes from restoration and improve on traditional approaches that focus on the most species-rich plantings. We investigated whether it is possible to apply a complementarity-based approach to evaluate the extent to which an existing network of restoration plantings meets representation targets. Using a case study of woodland birds of conservation concern in southeastern Australia, we compared complementarity-based selections of plantings based on temporally dynamic species occurrences with selections based on static species occurrences and selections based on ranking plantings by species richness. The dynamic complementarity approach, which incorporated species occurrences over 5 years, resulted in higher species occurrences and proportion of targets met compared with the static complementarity approach, in which species occurrences were taken at a single point in time. For equivalent cost, the dynamic complementarity approach also always resulted in higher average minimum percent occurrence of species maintained through time and a higher proportion of the bird community meeting representation targets compared with the species-richness approach. Plantings selected under the complementarity approaches represented the full range of planting attributes, whereas those selected under the species-richness approach were larger in size. Our results suggest that future restoration policy should not attempt to achieve all conservation goals within individual plantings, but should instead capitalize on restoration opportunities as they arise to achieve collective value of multiple plantings across the landscape. Networks of restoration plantings with complementary attributes of age, size, vegetation structure, and landscape context lead to considerably better outcomes than conventional restoration objectives of site-scale species richness and are crucial for allocating restoration investment wisely to reach desired conservation goals.We thank the Australian Research Council, the Murrayand Riverina Local Land Services, and the Caring for OurCountry Program for funding for this project

The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple-use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders' willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders' decisions to engage in management. To test the utility of our best-supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost-effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost-effective for prioritizing management when social data collection costs were low

Diversionary feeding: an effective management strategy for conservation conflict?

Human population growth has led to increased contact between people and wildlife, with adverse impacts for both, such as damage to economic crops and wildlife persecution. Diversionary feeding, where food is used to draw animals away from problem activities or locations, is sometimes proposed as a socially acceptable conservation action, but little information exists on its success or what influences its efficacy. Here, we review literature on diversionary feeding and evaluate factors contributing to its success or failure. Success varied greatly among studies and successful uptake of diversionary food did not consistently produce outcomes that met stakeholder objectives. Studies often failed to report results in sufficient detail to allow a quantitative evaluation of efficiency. Of 30 trials presented in 21 studies, 13 enabled assessment of outcomes related to the ultimate objective of reducing conflict (related to threatened prey density, crop yield or nuisance reports) and only five of these were considered successful by the researchers conducting the study. A grand mean increase of 15% in respective measures of success at the outcome stage was found across all studies. Although diversionary feeding is considered expensive, cost-effectiveness analyses were rarely conducted. Only a third of studies reported information on costs and benefits that could be used to inform future management actions. We propose a decision-making framework that incorporates ecological knowledge, financial costs and evidence from previous studies to aid the planning and implementation of diversionary feeding in an adaptive format. Future studies of diversionary feeding should clearly report objectives, results, costsand effort to allow the return-on-investment to be calculated for different levels of management effort

Cross-boundary collaboration: Key to the conservation puzzle

Conservation science is advancing rapidly, yet the majority of research overlooks a key factor that can play a major role in shaping the outcomes of conservation initiatives: collaboration. Here, we review the importance, benefits and limitations of incorporating collaboration into conservation and specifically into systematic conservation planning, providing a general framework for considering collaboration in conservation planning. Recent work shows that cross-boundary collaboration can have both positive and negative impacts on the outcomes of conservation and management efforts for protected areas, ecosystems, threatened and invasive species. The feasibility of collaboration, its likely effects and associated trade-offs should therefore be explicitly incorporated into conservation science and planning. This will ensure that conservation decisions avoid wasted funding when collaboration is infeasible, promoting collaboration when the benefits outweigh the costs

How the EAT-Lancet commission report 'Food in the Anthropocene' influenced discourse and research on food systems: a systematic review covering the first two years post-publication

In 2019, the EAT–Lancet Commission's report on food in the Anthropocene presented a planetary heath diet to improve health while reducing the environmental effect of food systems globally. We assessed EAT–Lancet's immediate influence on academic research and debate by conducting a systematic review of articles citing the Commission and others published from January, 2019, to April, 2021. The Commission influenced methods, results, or discourse for 192 (7·5%) of 2560 citing articles, stimulating cross-disciplinary research and debate across life sciences (47%), health and medical sciences (42%), and social sciences (11%). Sentiment analysis of 76 critiquing articles indicated that opinions were, on average, more positive than negative. Positive sentiments centred on benefits for informing policy, public health, and raising public awareness. Negative sentiments included insufficient attention to socioeconomic dimensions, feasibility, and environmental effects other than emissions. Empirical articles predominantly evaluated the effects of changed diets or food production on the environment and wellbeing (29%), compared current diets with EAT–Lancet recommendations (12%), or informed future policy and research agendas (20%). Despite limitations in EAT–Lancet's method, scope, and implementation feasibility, the academic community supported these recommendations. A broad suite of research needs was identified focusing on the effects of food processing, socioeconomic and political drivers of diet and health, and optimising consumption or production for environment and health

Trade-offs between data resolution, accuracy, and cost when choosing information to plan reserves for coral reef ecosystems

Conservation planners must reconcile trade-offs associated with using biodiversity data of differing qualities to make decisions. Coarse habitat classifications are commonly used as surrogates to design marine reserve networks when fine-scale biodiversity data are incomplete or unavailable. Although finely-classified habitat maps provide more detail, they may have more misclassification errors, a common problem when remotely-sensed imagery is used. Despite these issues, planners rarely consider the effects of errors when choosing data for spatially explicit conservation prioritizations. Here we evaluate trade-offs between accuracy and resolution of hierarchical coral reef habitat data (geomorphology and benthic substrate) derived from remote sensing, in spatial planning for Kubulau District, Fiji. For both, we use accuracy information describing the probability that a mapped habitat classification is correct to design marine reserve networks that achieve habitat conservation targets, and demonstrate inadequacies of using habitat maps without accuracy data. We show that using more detailed habitat information ensures better representation of biogenic habitats (i.e. coral and seagrass), but leads to larger and more costly reserves, because these data have more misclassification errors, and are also more expensive to obtain. Reduced impacts on fishers are possible using coarsely-classified data, which are also more cost-effective for planning reserves if we account for data collection costs, but using these data may under-represent reef habitats that are important for fisheries and biodiversity, due to the maps low thematic resolution. Finally, we show that explicitly accounting for accuracy information in decisions maximizes the chance of successful conservation outcomes by reducing the risk of missing conservation representation targets, particularly when using finely classified data