The value of flexibility in conservation financing

Land‐acquisition strategies employed by conservation organizations vary in their flexibility. Conservation‐planning theory largely fails to reflect this by presenting models that are either extremely inflexible—parcel acquisitions are irreversible and budgets are fixed—or extremely flexible—previously acquired parcels can readily be sold. This latter approach, the selling of protected areas, is infeasible or problematic in many situations. We considered the value to conservation organizations of increasing the flexibility of their land‐acquisition strategies through their approach to financing deals. Specifically, we modeled 2 acquisition‐financing methods commonly used by conservation organizations: borrowing and budget carry‐over. Using simulated data, we compared results from these models with those from an inflexible fixed‐budget model and an extremely flexible selling model in which previous acquisitions could be sold to fund new acquisitions. We then examined 3 case studies of how conservation organizations use borrowing and budget carry‐over in practice. Model comparisons showed that borrowing and budget carry‐over always returned considerably higher rewards than the fixed‐budget model. How they performed relative to the selling model depended on the relative conservation value of past acquisitions. Both the models and case studies showed that incorporating flexibility through borrowing or budget carry‐over gives conservation organizations the ability to purchase parcels of higher conservation value than when budgets are fixed without the problems associated with the selling of protected areas.     

Reliability of Indicators of Decline in Abundance

Abstract: Although there are many indicators of endangerment (i.e., whether populations or species meet criteria that justify conservation action), their reliability has rarely been tested. Such indicators may fail to identify that a population or species meets criteria for conservation action (false negative) or may incorrectly show that such criteria have been met (false positive). To quantify the rate of both types of error for 20 commonly used indicators of declining abundance (threat indicators), we used receiver operating characteristic curves derived from historical (1938–2007) data for 18 sockeye salmon (Oncorhynchus nerka) populations in the Fraser River, British Columbia, Canada. We retrospectively determined each population's yearly status (reflected by change in abundance over time) on the basis of each indicator. We then compared that population's status in a given year with the status in subsequent years (determined by the magnitude of decline in abundance across those years). For each sockeye population, we calculated how often each indicator of past status matched subsequent status. No single threat indicator provided error‐free estimates of status, but indicators that reflected the extent (i.e., magnitude) of past decline in abundance (through comparison of current abundance with some historical baseline abundance) tended to better reflect status in subsequent years than the rate of decline over the previous 3 generations (a widely used indicator). We recommend that when possible, the reliability of various threat indicators be evaluated with empirical analyses before such indicators are used to determine the need for conservation action. These indicators should include estimates from the entire data set to take into account a historical baseline.     

Expert judgment and uncertainty regarding the protection of imperiled species

Decisions concerning the appropriate listing status of species under the U.S. Endangered Species Act (ESA) can be controversial even among conservationists. These decisions may determine whether a species persists in the near term and have long‐lasting social and political ramifications. Given the ESA's mandate that such decisions be based on the best available science, it is important to examine what factors contribute to experts’ judgments concerning the listing of species. We examined how a variety of factors (such as risk perception, value orientations, and norms) influenced experts’ judgments concerning the appropriate listing status of the grizzly bear (Ursus arctos horribilis) population in the Greater Yellowstone Ecosystem. Experts were invited to complete an online survey examining their perceptions of the threats grizzly bears face and their listing recommendation. Although experts’ assessments of the threats to this species were strongly correlated with their recommendations for listing status, this relationship did not exist when other cognitive factors were included in the model. Specifically, values related to human use of wildlife and norms (i.e., a respondent's expectation of peers’ assessments) were most influential in listing status recommendations. These results suggest that experts’ decisions about listing, like all human decisions, are subject to the use of heuristics (i.e., decision shortcuts). An understanding of how heuristics and related biases affect decisions under uncertainty can help inform decision making about threatened and endangered species and may be useful in designing effective processes for protection of imperiled species.     

A guide to representing variability and uncertainty in biodiversity indicators

Biodiversity indicators are used to inform decisions and measure progress toward global targets, such as the United Nations Sustainable Development Goals. Indicators aggregate and simplify complex information, so underlying information influencing its reliability and interpretation (e.g., variability in data and uncertainty in indicator values) can be lost. Communicating uncertainty is necessary to ensure robust decisions and limit misinterpretations of trends, yet variability and uncertainty are rarely quantified in biodiversity indicators. We developed a guide to representing uncertainty and variability in biodiversity indicators. We considered the key purposes of biodiversity indicators and commonly used methods for representing uncertainty (standard error, bootstrap resampling, and jackknife resampling) and variability (quantiles, standard deviation, median absolute deviation, and mean absolute deviation) with intervals. Using 3 high-profile biodiversity indicators (Red List Index, Living Planet Index, and Ocean Health Index), we tested the use, suitability, and interpretation of each interval method based on the formulation and data types underpinning the indicators. The methods revealed vastly different information; indicator formula and data distribution affected the suitability of each interval method. Because the data underpinning each indicator were not normally distributed, methods relying on normality or symmetrical spread were unsuitable. Quantiles, bootstrapping, and jackknifing provided useful information about the underlying variability and uncertainty. We built a decision tree to inform selection of the appropriate interval method to represent uncertainty or variation in biodiversity indicators, depending on data type and objectives. Our guide supports transparent and effective communication of biodiversity indicator trends to facilitate accurate interpretation by decision makers.     

Refuge‐Effect Hypothesis and the Demise of the Dodo

The Dodo was last sighted on the inshore island of Ile d'Ambre in 1662, nearly 25 years after the previous sighting on the mainland of Mauritius. It has been suggested that its survival on the inshore island is representative of the refuge effect. Understanding what constitutes significant persistence is fundamental to conservation. I tested the refuge‐effect hypothesis for the persistence of the Dodo (Raphus cucullatus) on an inshore island beyond that of the mainland population. For a location to be considered a refuge, most current definitions suggest that both spatial and temporal isolation from the cause of disturbance are required. These results suggest the island was not a refuge for the Dodo because the sighting in 1662 was not temporally isolated from that of the mainland sightings. Furthermore, with only approximately 350 m separating Ile d'Ambre from the mainland of Mauritius, it is unlikely this population of Dodos was spatially isolated. Hipótesis del Efecto Refugio y la Desaparición del Dodo     

Incorporating Uncertainty of Management Costs in Sensitivity Analyses of Matrix Population Models

The importance of accounting for economic costs when making environmental‐management decisions subject to resource constraints has been increasingly recognized in recent years. In contrast, uncertainty associated with such costs has often been ignored. We developed a method, on the basis of economic theory, that accounts for the uncertainty in population‐management decisions. We considered the case where, rather than taking fixed values, model parameters are random variables that represent the situation when parameters are not precisely known. Hence, the outcome is not precisely known either. Instead of maximizing the expected outcome, we maximized the probability of obtaining an outcome above a threshold of acceptability. We derived explicit analytical expressions for the optimal allocation and its associated probability, as a function of the threshold of acceptability, where the model parameters were distributed according to normal and uniform distributions. To illustrate our approach we revisited a previous study that incorporated cost‐efficiency analyses in management decisions that were based on perturbation analyses of matrix population models. Incorporating derivations from this study into our framework, we extended the model to address potential uncertainties. We then applied these results to 2 case studies: management of a Koala (Phascolarctos cinereus) population and conservation of an olive ridley sea turtle (Lepidochelys olivacea) population. For low aspirations, that is, when the threshold of acceptability is relatively low, the optimal strategy was obtained by diversifying the allocation of funds. Conversely, for high aspirations, the budget was directed toward management actions with the highest potential effect on the population. The exact optimal allocation was sensitive to the choice of uncertainty model. Our results highlight the importance of accounting for uncertainty when making decisions and suggest that more effort should be placed on understanding the distributional characteristics of such uncertainty. Our approach provides a tool to improve decision making.     

Using soundscapes to detect variable degrees of human influence on tropical forests in Papua New Guinea

There is global concern about tropical forest degradation, in part, because of the associated loss of biodiversity. Communities and indigenous people play a fundamental role in tropical forest management and are often efficient at preventing forest degradation. However, monitoring changes in biodiversity due to degradation, especially at a scale appropriate to local tropical forest management, is plagued by difficulties, including the need for expert training, inconsistencies across observers, and lack of baseline or reference data. We used a new biodiversity remote‐sensing technology, the recording of soundscapes, to test whether the acoustic saturation of a tropical forest in Papua New Guinea decreases as land‐use intensity by the communities that manage the forest increases. We sampled soundscapes continuously for 24 hours at 34 sites in different land‐use zones of 3 communities. Land‐use zones where forest cover was fully retained had significantly higher soundscape saturation during peak acoustic activity times (i.e., dawn and dusk chorus) compared with land‐use types with fragmented forest cover. We conclude that, in Papua New Guinea, the relatively simple measure of soundscape saturation may provide a cheap, objective, reproducible, and effective tool for monitoring tropical forest deviation from an intact state, particularly if it is used to detect the presence of intact dawn and dusk choruses.     

Use of stochastic patch occupancy models in the California red-legged frog for Bayesian inference regarding past events and future persistence

Assessing causes of population decline is critically important to management of threatened species. Stochastic patch occupancy models (SPOMs) are popular tools for examining spatial and temporal dynamics of populations when presence–absence data in multiple habitat patches are available. We developed a Bayesian Markov chain method that extends existing SPOMs by focusing on past environmental changes that may have altered occupancy patterns prior to the beginning of data collection. Using occupancy data from 3 creeks, we applied the method to assess 2 hypothesized causes of population decline—in situ die-off and residual impact of past source population loss—in the California red-legged frog. Despite having no data for the 20–30 years between the hypothetical event leading to population decline and the first data collected, we were able to discriminate among hypotheses, finding evidence that in situ die-off increased in 2 of the creeks. Although the creeks had comparable numbers of occupied segments, owing to different extinction–colonization dynamics, our model predicted an 8-fold difference in persistence probabilities of their populations to 2030. Adding a source population led to a greater predicted persistence probability than did decreasing the in situ die-off, emphasizing that reversing the deleterious impacts of a disturbance may not be the most efficient management strategy. We expect our method will be useful for studying dynamics and evaluating management strategies of many species.     

Using individual-based movement information to identify spatial conservation priorities for mobile species

The optimal design of reserve networks and fisheries closures depends on species occurrence information and knowledge of how anthropogenic impacts interact with the species concerned. However, challenges in surveying mobile and cryptic species over adequate spatial and temporal scales can mask the importance of particular habitats, leading to uncertainty about which areas to protect to optimize conservation efforts. We investigated how telemetry-derived locations can help guide the scale and timing of fisheries closures with the aim of reducing threatened species bycatch. Forty juvenile speartooth sharks (Glyphis glyphis) were monitored over 22 months with implanted acoustic transmitters and an array of hydrophone receivers. Using the decision-support tool Marxan, we formulated a permanent fisheries closure that prioritized areas used more frequently by tagged sharks and considered areas perceived as having high value to fisheries. To explore how the size of the permanent closure compared with an alternative set of time-area closures (i.e., where different areas were closed to fishing at different times of year), we used a cluster analysis to group months that had similar arrangements of selected planning units (informed by shark movements during that month) into 2 time-area closures. Sharks were consistent in their timing and direction of migratory movements, but the number of tagged sharks made a big difference in the placement of the permanent closure; 30 individuals were needed to capture behavioral heterogeneity. The dry-season (May–January) and wet-season (February–April) time-area closures opened 20% and 25% more planning units to fishing, respectively, compared with the permanent closure with boundaries fixed in space and time. Our results show that telemetry has the potential to inform and improve spatial management of mobile species and that the temporal component of tracking data can be incorporated into prioritizations to reduce possible impacts of spatial closures on established fisheries.