Geographic bias in citation rates of conservation research

We investigated whether the impact of conservation science is greater for research conducted in countries with more pressing conservation problems. We quantified research impact for 231 countries based on 2 citation metrics (mean cites per paper and h index) and fitted models predicting research impact based on number of threatened bird and mammal species (as a measure of conservation importance of a country) and a range of demographic variables. Citation rates of conservation research increased as a country's conservation need increased and as human population, quality of governance, and wealth increased. Even after accounting for these factors, citation rates among regions and countries within regions varied significantly. The conservation research community needs to consider ways to begin addressing the entrenched disadvantages some countries have when it comes to initiating projects and producing high‐quality research.     

Mathematical Methods for Spatially Cohesive Reserve Design

The problem of designing spatially cohesive nature reserve systems that meet biodiversity objectives is formulated as a nonlinear integer programming problem. The multiobjective function minimises a combination of boundary length, area and failed representation of the biological attributes we are trying to conserve. The task is to reserve a subset of sites that best meet this objective. We use data on the distribution of habitats in the Northern Territory, Australia, to show how simulated annealing and a greedy heuristic algorithm can be used to generate good solutions to such large reserve design problems, and to compare the effectiveness of these methods.     

Planning for persistence in marine reserves: a question of catastrophic importance.

Large-scale catastrophic events, although rare, lie generally beyond the control of local management and can prevent marine reserves from achieving biodiversity outcomes. We formulate a new conservation planning problem that aims to minimize the probability of missing conservation targets as a result of catastrophic events. To illustrate this approach we formulate and solve the problem of minimizing the impact of large-scale coral bleaching events on a reserve system for the Great Barrier Reef, Australia. We show that by considering the threat of catastrophic events as part of the reserve design problem it is possible to substantially improve the likely persistence of conservation features within reserve networks for a negligible increase in cost. In the case of the Great Barrier Reef, a 2% increase in overall reserve cost was enough to improve the long-run performance of our reserve network by >60%. Our results also demonstrate that simply aiming to protect the reefs at lowest risk of catastrophic bleaching does not necessarily lead to the best conservation outcomes, and enormous gains in overall persistence can be made by removing the requirement to represent all bioregions in the reserve network. We provide an explicit and well-defined method that allows the probability of catastrophic disturbances to be included in the site selection problem without creating additional conservation targets or imposing arbitrary presence/absence thresholds on existing data. This research has implications for reserve design in a changing climate.     

Evaluating surrogates of genetic diversity for conservation planning

Protected-area systems should conserve intraspecific genetic diversity. Because genetic data require resources to obtain, several approaches have been proposed for generating plans for protected-area systems (prioritizations) when genetic data are not available. Yet such surrogate-based approaches remain poorly tested. We evaluated the effectiveness of potential surrogate-based approaches based on microsatellite genetic data collected across the Iberian Peninsula for 7 amphibian and 3 reptilian species. Long-term environmental suitability did not effectively represent sites containing high genetic diversity (allelic richness). Prioritizations based on long-term environmental suitability had similar performance to random prioritizations. Geographic distances and resistance distances based on contemporary environmental suitability were not always effective surrogates for identification of combinations of sites that contain individuals with different genetic compositions. Our results demonstrate that population genetic data based on commonly used neutral markers can inform prioritizations, and we could not find an adequate substitute. Conservation planners need to weigh the potential benefits of genetic data against their acquisition costs.     

Software for prioritizing conservation actions based on probabilistic information

Marxan is the most common decision-support tool used to inform the design of protected-area systems. The original version of Marxan does not consider risk and uncertainty associated with threatening processes affecting protected areas, including uncertainty about the location and condition of species’ populations and habitats now and in the future. We described and examined the functionality of a modified version of Marxan, Marxan with Probability. This software explicitly considers 4 types of uncertainty: probability that a feature exists in a particular place (estimated based on species distribution models or spatially explicit population models); probability that features in a site will be lost in the future due to a threatening process, such as climate change, natural catastrophes, and uncontrolled human interventions; probability that a feature will exist in the future due to natural successional processes, such as a fire or flood; and probability the feature exists but has been degraded by threatening processes, such as overfishing or pollution, and thus cannot contribute to conservation goals. We summarized the results of 5 studies that illustrate how each type of uncertainty can be used to inform protected area design. If there were uncertainty in species or habitat distribution, users could maximize the chance that these features were represented by including uncertainty using Marxan with Probability. Similarly, if threatening processes were considered, users minimized the chance that species or habitats were lost or degraded by using Marxan with Probability. Marxan with Probability opens up substantial new avenues for systematic conservation planning research and application by agencies.     

Wilderness forms and their implications for global environmental policy and conservation

With the intention of securing industry-free land and seascapes, protecting wilderness entered international policy as a formal target for the first time in the zero draft of the Post-2020 Global Biodiversity Framework under the Convention on Biological Diversity. Given this increased prominence in international policy, it is timely to consider the extent to which the construct of wilderness supports global conservation objectives. We evaluated the construct by overlaying recently updated cumulative human pressure maps that offer a global-scale delineation of industry-free land as wilderness with maps of carbon stock, species richness, and ground travel time from urban centers. Wilderness areas took variable forms in relation to carbon stock, species richness, and proximity to urban centers, where 10% of wilderness areas represented high carbon and species richness, 20% low carbon and species richness, and 3% high levels of remoteness (>48 h), carbon, and species richness. Approximately 35% of all remaining wilderness in 2013 was accessible in <24 h of travel time from urban centers. Although the construct of wilderness can be used to secure benefits in specific contexts, its application in conservation must account for contextual and social implications. The diverse characterization of wilderness under a global environmental conservation lens shows that a nuanced framing and application of the construct is needed to improve understanding, communication, and retention of its variable forms as industry-free places.