Resolving future fire management conflicts using multicriteria decision making

Management strategies to reduce the risks to human life and property from wildfire commonly involve burning native vegetation. However, planned burning can conflict with other societal objectives such as human health and biodiversity conservation. These conflicts are likely to intensify as fire regimes change under future climates and as growing human populations encroach farther into fire‐prone ecosystems. Decisions about managing fire risks are therefore complex and warrant more sophisticated approaches than are typically used. We applied a multicriteria decision making approach (MCDA) with the potential to improve fire management outcomes to the case of a highly populated, biodiverse, and flammable wildland–urban interface. We considered the effects of 22 planned burning options on 8 objectives: house protection, maximizing water quality, minimizing carbon emissions and impacts on human health, and minimizing declines of 5 distinct species types. The MCDA identified a small number of management options (burning forest adjacent to houses) that performed well for most objectives, but not for one species type (arboreal mammal) or for water quality. Although MCDA made the conflict between objectives explicit, resolution of the problem depended on the weighting assigned to each objective. Additive weighting of criteria traded off the arboreal mammal and water quality objectives for other objectives. Multiplicative weighting identified scenarios that avoided poor outcomes for any objective, which is important for avoiding potentially irreversible biodiversity losses. To distinguish reliably among management options, future work should focus on reducing uncertainty in outcomes across a range of objectives. Considering management actions that have more predictable outcomes than landscape fuel management will be important. We found that, where data were adequate, an MCDA can support decision making in the complex and often conflicted area of fire management.     

Setting population targets for mammals using body mass as a predictor of population persistence

Conservation planning and biodiversity assessments need quantitative targets to optimize planning options and assess the adequacy of current species protection. However, targets aiming at persistence require population‐specific data, which limit their use in favor of fixed and nonspecific targets, likely leading to unequal distribution of conservation efforts among species. We devised a method to derive equitable population targets; that is, quantitative targets of population size that ensure equal probabilities of persistence across a set of species and that can be easily inferred from species‐specific traits. In our method, we used models of population dynamics across a range of life‐history traits related to species’ body mass to estimate minimum viable population targets. We applied our method to a range of body masses of mammals, from 2 g to 3825 kg. The minimum viable population targets decreased asymptotically with increasing body mass and were on the same order of magnitude as minimum viable population estimates from species‐ and context‐specific studies. Our approach provides a compromise between pragmatic, nonspecific population targets and detailed context‐specific estimates of population viability for which only limited data are available. It enables a first estimation of species‐specific population targets based on a readily available trait and thus allows setting equitable targets for population persistence in large‐scale and multispecies conservation assessments and planning.     

Wildlife and wildlife management in Tanzania

Tanzania, arguably mainland Africa's most important nation for conservation, is losing habitat and natural resources rapidly. Moving away from a charcoal energy base and developing sustainable finance mechanisms for natural forests are critical to slowing persistent deforestation. Addressing governance and capacity deficits, including law enforcement, technical skills, and funding, across parts of the wildlife sector are key to effective wildlife protection. These changes could occur in tandem with bringing new models of natural resource management into play that include capacity building, corporate payment for ecosystem services, empowering nongovernmental organizations in law enforcement, greater private‐sector involvement, and novel community conservation strategies. The future of Tanzania's wildlife looks uncertain—as epitomized by the current elephant crisis—unless the country confronts issues of governance, embraces innovation, and fosters greater collaboration with the international community.     

Killing Tigers to Save Them: Fallacies of the Farming Argument

Abstract: The lucrative, illegal trade in tigers (Panthera tigris) remains a major conservation problem. Tiger farming has been proposed as a potential solution, with farmed tigers substituting for wild tigers. At first glance, this argument's logic seems simple: farming will increase the supply of tigers, prices will fall, and poaching will no longer be profitable. We contend, however, that this supply‐side argument relies on mistaken assumptions. First, tiger markets are imperfect, meaning they are dominated by a few producers who control price. Second, consumers prefer wild tigers to farmed tigers and therefore the two are not pure substitutes. In economic terms, products from wild tigers are luxury goods, commanding a price premium. Third, there is no evidence that farmed tigers can be produced or sold more cheaply than wild tigers. In sum, it is unlikely that farming will drive down the price of wild‐caught tigers or decrease profitability for tiger poachers. Rather, tiger farming is more likely to increase aggregate demand for tiger products and stimulate higher levels of poaching.     

Effects of uncertainty and variability on population declines and IUCN Red List classifications

The International Union for Conservation of Nature (IUCN) Red List Categories and Criteria is a quantitative framework for classifying species according to extinction risk. Population models may be used to estimate extinction risk or population declines. Uncertainty and variability arise in threat classifications through measurement and process error in empirical data and uncertainty in the models used to estimate extinction risk and population declines. Furthermore, species traits are known to affect extinction risk. We investigated the effects of measurement and process error, model type, population growth rate, and age at first reproduction on the reliability of risk classifications based on projected population declines on IUCN Red List classifications. We used an age‐structured population model to simulate true population trajectories with different growth rates, reproductive ages and levels of variation, and subjected them to measurement error. We evaluated the ability of scalar and matrix models parameterized with these simulated time series to accurately capture the IUCN Red List classification generated with true population declines. Under all levels of measurement error tested and low process error, classifications were reasonably accurate; scalar and matrix models yielded roughly the same rate of misclassifications, but the distribution of errors differed; matrix models led to greater overestimation of extinction risk than underestimations; process error tended to contribute to misclassifications to a greater extent than measurement error; and more misclassifications occurred for fast, rather than slow, life histories. These results indicate that classifications of highly threatened taxa (i.e., taxa with low growth rates) under criterion A are more likely to be reliable than for less threatened taxa when assessed with population models. Greater scrutiny needs to be placed on data used to parameterize population models for species with high growth rates, particularly when available evidence indicates a potential transition to higher risk categories.     

Species composition of the international shark fin trade assessed through a retail‐market survey in Hong Kong

The shark fin trade is a major driver of shark exploitation in fisheries all over the world, most of which are not managed on a species‐specific basis. Species‐specific trade information highlights taxa of particular concern and can be used to assess the efficacy of management measures and anticipate emerging threats. The species composition of the Hong Kong Special Administrative Region of China, one of the world's largest fin trading hubs, was partially assessed in 1999–2001. We randomly selected and genetically identified fin trimmings (n = 4800), produced during fin processing, from the retail market of Hong Kong in 2014–2015 to assess contemporary species composition of the fin trade. We used nonparametric species estimators to determine that at least 76 species of sharks, batoids, and chimaeras supplied the fin trade and a Bayesian model to determine their relative proportion in the market. The diversity of traded species suggests species substitution could mask depletion of vulnerable species; one‐third of identified species are threatened with extinction. The Bayesian model suggested that 8 species each comprised >1% of the fin trimmings (34.1–64.2% for blue [Prionace glauca], 0.2–1.2% for bull [Carcharhinus leucas] and shortfin mako [Isurus oxyrinchus]); thus, trade was skewed to a few globally distributed species. Several other coastal sharks, batoids, and chimaeras are in the trade but poorly managed. Fewer than 10 of the species we modeled have sustainably managed fisheries anywhere in their range, and the most common species in trade, the blue shark, was not among them. Our study and approach serve as a baseline to track changes in composition of species in the fin trade over time to better understand patterns of exploitation and assess the effects of emerging management actions for these animals.     

Life-history traits and the fate of translocated populations

Attempts to identify predictors and mechanisms of invasion success have been weakened by poor data quality, mostly because monitoring does not begin immediately after introduction events. To overcome this issue, we used data from conservation translocations of threatened bird species. We analyzed information on >1200 translocation events of >150 bird species to investigate how life-history traits affect population establishment measured based on rates of survival and reproduction. Species position along the slow–fast life-history continuum was a key predictor of translocation success. Species with fast-paced life histories were less likely to survive (over both short- and mid-term) and more likely to breed successfully than species with slow life histories. The temporal partitioning of reproductive effort (number of clutches per year) also affected the probability of successful reproduction. Our results illustrate how conservation-motivated reintroduction programs can provide proxies for the initial stages of the invasion process, enabling empirical tests of predictions from life-history theory and informing management.     

Understanding complex drivers of wildlife crime to design effective conservation interventions

In conservation understanding the drivers of behavior and developing robust interventions to promote behavioral change is challenging and requires a multifaceted approach. This is particularly true for efforts to address illegal wildlife use, where pervasive—and sometimes simplistic—narratives often obscure complex realities. We used an indirect questioning approach, the unmatched count technique, to investigate the drivers and prevalence of wildlife crime in communities surrounding 2 national parks in Uganda and combined scenario interviews and a choice experiment to predict the performance of potential interventions designed to tackle these crimes. Although poverty is often assumed to be a key driver of wildlife crime, we found that better-off households and those subject to human–wildlife conflict and those that do not receive any benefits from the parks’ tourism revenue sharing were more likely to be involved in certain types of wildlife crime, especially illegal hunting. The interventions predicted to have the greatest impact on reducing local participation in wildlife crime were those that directly addressed the drivers including, mitigating damage caused by wildlife and generating financial benefits for park-adjacent households. Our triangulated approach provided insights into complex and hard-to-access behaviors and highlighted the importance of going beyond single-driver narratives.     

Conservation and monitoring of a persecuted African lion population by Maasai warriors

Although Africa has many threatened species and biological hot spots, there are few citizen science schemes, particularly in rural communities, and there has been limited evaluation of existing programs. We engaged traditional Maasai warriors (pastoralist men aged 15 to 35) in community‐based conservation and demographic monitoring of a persecuted African lion (Panthera leo) population. Through direct engagement, we investigated whether a citizen science approach employing local warriors, who had no formal education, could produce reliable data on the demographics, predation, and movements of a species with which their communities have been in conflict for generations. Warriors were given benefits such as literacy training and skill enhancement and engaged in the monitoring of the lions. The trained warriors reported on lion sign across an area nearly 4000 km². Scientists worked together with the warriors to verify their reports and gather observations on the lion population. Using the verified reports and collected observations, we examined our scientific knowledge relative to the lion population preceding and during the citizen science program. Our observations showed that data quality and quantity improved with the involvement and training of the participants. Furthermore, because they engaged in conservation and gained personal benefits, the participants came to appreciate a species that was traditionally their foe. We believe engaging other local communities in biodiversity conservation and monitoring may be an effective conservation approach in rural Africa.     

Tracing the geographic origin of traded leopard body parts in the indian subcontinent with DNA‐based assignment tests

Illicit trade in wildlife products is rapidly decimating many species across the globe. Such trade is often underestimated for wide‐ranging species until it is too late for the survival of their remaining populations. Policing this trade could be vastly improved if one could reliably determine geographic origins of illegal wildlife products and identify areas where greater enforcement is needed. Using DNA‐based assignment tests (i.e., samples are assigned to geographic locations), we addressed these factors for leopards (Panthera pardus) on the Indian subcontinent. We created geography‐specific allele frequencies from a genetic reference database of 173 leopards across India to infer geographic origins of DNA samples from 40 seized leopard skins. Sensitivity analyses of samples of known geographic origins and assignments of seized skins demonstrated robust assignments for Indian leopards. We found that confiscated pelts seized in small numbers were not necessarily from local leopards. The geographic footprint of large seizures appeared to be bigger than the cumulative footprint of several smaller seizures, indicating widespread leopard poaching across the subcontinent. Our seized samples had male‐biased sex ratios, especially the large seizures. From multiple seized sample assignments, we identified central India as a poaching hotspot for leopards. The techniques we applied can be used to identify origins of seized illegal wildlife products and trade routes at the subcontinent scale and beyond.