Improving effectiveness of systematic conservation planning with density data

Systematic conservation planning aims to design networks of protected areas that meet conservation goals across large landscapes. The optimal design of these conservation networks is most frequently based on the modeled habitat suitability or probability of occurrence of species, despite evidence that model predictions may not be highly correlated with species density. We hypothesized that conservation networks designed using species density distributions more efficiently conserve populations of all species considered than networks designed using probability of occurrence models. To test this hypothesis, we used the Zonation conservation prioritization algorithm to evaluate conservation network designs based on probability of occurrence versus density models for 26 land bird species in the U.S. Pacific Northwest. We assessed the efficacy of each conservation network based on predicted species densities and predicted species diversity. High‐density model Zonation rankings protected more individuals per species when networks protected the highest priority 10‐40% of the landscape. Compared with density‐based models, the occurrence‐based models protected more individuals in the lowest 50% priority areas of the landscape. The 2 approaches conserved species diversity in similar ways: predicted diversity was higher in higher priority locations in both conservation networks. We conclude that both density and probability of occurrence models can be useful for setting conservation priorities but that density‐based models are best suited for identifying the highest priority areas. Developing methods to aggregate species count data from unrelated monitoring efforts and making these data widely available through ecoinformatics portals such as the Avian Knowledge Network will enable species count data to be more widely incorporated into systematic conservation planning efforts.     

Benefits to poorly studied taxa of conservation of bird and mammal diversity on islands

Protected area delineation and conservation action are urgently needed on marine islands, but the potential biodiversity benefits of these activities can be difficult to assess due to lack of species diversity information for lesser known taxa. We used linear mixed effects modeling and simple spatial analyses to investigate whether conservation activities based on the diversity of well‐known insular taxa (birds and mammals) are likely to also capture the diversity of lesser known taxa (reptiles, amphibians, vascular land plants, ants, land snails, butterflies, and tenebrionid beetles). We assembled total, threatened, and endemic diversity data for both well‐known and lesser known taxa and combined these with physical island biogeography characteristics for 1190 islands from 109 archipelagos. Among physical island biogeography factors, island area was the best indicator of diversity of both well‐known and little‐known taxa. Among taxonomic factors, total mammal species richness was the best indicator of total diversity of lesser known taxa, and the combination of threatened mammal and threatened bird diversity was the best indicator of lesser known endemic richness. The results of other intertaxon diversity comparisons were highly variable, however. Based on our results, we suggest that protecting islands above a certain minimum threshold area may be the most efficient use of conservation resources. For example, using our island database, if the threshold were set at 10 km² and the smallest 10% of islands greater than this threshold were protected, 119 islands would be protected. The islands would range in size from 10 to 29 km² and would include 268 lesser known species endemic to a single island, along with 11 bird and mammal species endemic to a single island. Our results suggest that for islands of equivalent size, prioritization based on total or threatened bird and mammal diversity may also capture opportunities to protect lesser known species endemic to islands. Beneficios de los Taxa Poco Estudiados para la Conservación de la Diversidad de Aves y Mamíferos en Islas     

Geographic range size and extinction risk assessment in nomadic species

Geographic range size is often conceptualized as a fixed attribute of a species and treated as such for the purposes of quantification of extinction risk; species occupying smaller geographic ranges are assumed to have a higher risk of extinction, all else being equal. However many species are mobile, and their movements range from relatively predictable to‐and‐fro migrations to complex irregular movements shown by nomadic species. These movements can lead to substantial temporary expansion and contraction of geographic ranges, potentially to levels which may pose an extinction risk. By linking occurrence data with environmental conditions at the time of observations of nomadic species, we modeled the dynamic distributions of 43 arid‐zone nomadic bird species across the Australian continent for each month over 11 years and calculated minimum range size and extent of fluctuation in geographic range size from these models. There was enormous variability in predicted spatial distribution over time; 10 species varied in estimated geographic range size by more than an order of magnitude, and 2 species varied by >2 orders of magnitude. During times of poor environmental conditions, several species not currently classified as globally threatened contracted their ranges to very small areas, despite their normally large geographic range size. This finding raises questions about the adequacy of conventional assessments of extinction risk based on static geographic range size (e.g., IUCN Red Listing). Climate change is predicted to affect the pattern of resource fluctuations across much of the southern hemisphere, where nomadism is the dominant form of animal movement, so it is critical we begin to understand the consequences of this for accurate threat assessment of nomadic species. Our approach provides a tool for discovering spatial dynamics in highly mobile species and can be used to unlock valuable information for improved extinction risk assessment and conservation planning.     

Using individual‐condition measures to predict the long‐term importance of habitat extent for population persistence

Habitat loss and fragmentation are causing widespread population declines, but identifying how and when to intervene remains challenging. Predicting where extirpations are likely to occur and implementing management actions before losses result may be more cost‐effective than trying to reestablish lost populations. Early indicators of pressure on populations could be used to make such predictions. Previous work conducted in 2009 and 2010 identified that the presence of Eastern Yellow Robins (Eopsaltria australis) in 42 sites in a fragmented region of eastern Australia was unrelated to woodland extent within 500 m of a site, but the robins’ heterophil:lymphocyte (H:L) ratios (an indicator of chronic stress) were elevated at sites with low levels of surrounding woodland. We resurveyed these 42 sites in 2013 and 2014 for robin presence to determine whether the H:L ratios obtained in 2009 and 2010 predicted the locations of extirpations and whether the previous pattern in H:L ratios was an early sign that woodland extent would become an important predictor of occupancy. We also surveyed for robins at 43 additional sites to determine whether current occupancy could be better predicted by landscape context at a larger scale, relevant to dispersal movements. At the original 42 sites, H:L ratios and extirpations were not related, although only 4 extirpations were observed. Woodland extent within 500 m had become a strong predictor of occupancy. Taken together, these results provide mixed evidence as to whether patterns of individual condition can reveal habitat relationships that become evident as local shifts in occupancy occur but that are not revealed by a single snapshot of species distribution. Across all 85 sites, woodland extent at scales relevant to dispersal (5 km) was not related to occurrence. We recommend that conservation actions focus on regenerating areas of habitat large enough to support robin territories rather than increasing connectivity within the landscape.     

Effects of threat management interactions on conservation priorities

Decisions need to be made about which biodiversity management actions are undertaken to mitigate threats and about where these actions are implemented. However, management actions can interact; that is, the cost, benefit, and feasibility of one action can change when another action is undertaken. There is little guidance on how to explicitly and efficiently prioritize management for multiple threats, including deciding where to act. Integrated management could focus on one management action to abate a dominant threat or on a strategy comprising multiple actions to abate multiple threats. Furthermore management could be undertaken at sites that are in close proximity to reduce costs. We used cost‐effectiveness analysis to prioritize investments in fire management, controlling invasive predators, and reducing grazing pressure in a bio‐diverse region of southeastern Queensland, Australia. We compared outcomes of 5 management approaches based on different assumptions about interactions and quantified how investment needed, benefits expected, and the locations prioritized for implementation differed when interactions were taken into account. Managing for interactions altered decisions about where to invest and in which actions to invest and had the potential to deliver increased investment efficiency. Differences in high priority locations and actions were greatest between the approaches when we made different assumptions about how management actions deliver benefits through threat abatement: either all threats must be managed to conserve species or only one management action may be required. Threatened species management that does not consider interactions between actions may result in misplaced investments or misguided expectations of the effort required to mitigate threats to species.     

Using empirical models of species colonization under multiple threatening processes to identify complementary threat‐mitigation strategies

Approaches to prioritize conservation actions are gaining popularity. However, limited empirical evidence exists on which species might benefit most from threat mitigation and on what combination of threats, if mitigated simultaneously, would result in the best outcomes for biodiversity. We devised a way to prioritize threat mitigation at a regional scale with empirical evidence based on predicted changes to population dynamics—information that is lacking in most threat‐management prioritization frameworks that rely on expert elicitation. We used dynamic occupancy models to investigate the effects of multiple threats (tree cover, grazing, and presence of an hyperaggressive competitor, the Noisy Miner (Manorina melanocephala) on bird‐population dynamics in an endangered woodland community in southeastern Australia. The 3 threatening processes had different effects on different species. We used predicted patch‐colonization probabilities to estimate the benefit to each species of removing one or more threats. We then determined the complementary set of threat‐mitigation strategies that maximized colonization of all species while ensuring that redundant actions with little benefit were avoided. The single action that resulted in the highest colonization was increasing tree cover, which increased patch colonization by 5% and 11% on average across all species and for declining species, respectively. Combining Noisy Miner control with increasing tree cover increased species colonization by 10% and 19% on average for all species and for declining species respectively, and was a higher priority than changing grazing regimes. Guidance for prioritizing threat mitigation is critical in the face of cumulative threatening processes. By incorporating population dynamics in prioritization of threat management, our approach helps ensure funding is not wasted on ineffective management programs that target the wrong threats or species.     

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.     

The Capacity of Australia's Protected‐Area System to Represent Threatened Species

Abstract: The acquisition or designation of new protected areas is usually based on criteria for representation of different ecosystems or land‐cover classes, and it is unclear how well‐threatened species are conserved within protected‐area networks. Here, we assessed how Australia's terrestrial protected‐area system (89 million ha, 11.6% of the continent) overlaps with the geographic distributions of threatened species and compared this overlap against a model that randomly placed protected areas across the continent and a spatially efficient model that placed protected areas across the continent to maximize threatened species’ representation within the protected‐area estate. We defined the minimum area needed to conserve each species on the basis of the species’ range size. We found that although the current configuration of protected areas met targets for representation of a given percentage of species’ ranges better than a random selection of areas, 166 (12.6%) threatened species occurred entirely outside protected areas and target levels of protection were met for only 259 (19.6%) species. Critically endangered species were among those with the least protection; 12 (21.1%) species occurred entirely outside protected areas. Reptiles and plants were the most poorly represented taxonomic groups, and amphibians the best represented. Spatial prioritization analyses revealed that an efficient protected‐area system of the same size as the current protected‐area system (11.6% of the area of Australia) could meet representation targets for 1272 (93.3%) threatened species. Moreover, the results of these prioritization analyses showed that by protecting 17.8% of Australia, all threatened species could reach target levels of representation, assuming all current protected areas are retained. Although this amount of area theoretically could be protected, existing land uses and the finite resources available for conservation mean land acquisition may not be possible or even effective for the recovery of threatened species. The optimal use of resources must balance acquisition of new protected areas, where processes that threaten native species are mitigated by the change in ownership or on‐ground management jurisdiction, and management of threatened species inside and outside the existing protected‐area system.     

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 (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.     

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.     

Predicting occurrence of juvenile shark habitat to improve conservation planning

Fishing and habitat degradation have increased the extinction risk of sharks, and conservation strategies recognize that survival of juveniles is critical for the effective management of shark populations. Despite the rapid expansion of marine protected areas (MPAs) globally, the paucity of shark‐monitoring data on large scales (100s–1000s km) means that the effectiveness of MPAs in halting shark declines remains unclear. Using data collected by baited remote underwater video systems (BRUVS) in northwestern Australia, we developed generalized linear models to elucidate the ecological drivers of habitat suitability for juvenile sharks. We assessed occurrence patterns at the order and species levels. We included all juvenile sharks sampled and the 3 most abundant species sampled separately (grey reef [Carcharhinus amblyrhynchos], sandbar [Carcharhinus plumbeus], and whitetip reef sharks [Triaenodon obesus]). We predicted the occurrence of juvenile sharks across 490,515 km² of coastal waters and quantified the representation of highly suitable habitats within MPAs. Our species‐level models had higher accuracy (? ≥ 0.69) and deviance explained (≥48%) than our order‐level model (? = 0.36 and deviance explained of 10%). Maps of predicted occurrence revealed different species‐specific patterns of highly suitable habitat. These differences likely reflect different physiological or resource requirements between individual species and validate concerns over the utility of conservation targets based on aggregate species groups as opposed to a species‐focused approach. Highly suitable habitats were poorly represented in MPAs with the most restrictions on extractive activities. This spatial mismatch possibly indicates a lack of explicit conservation targets and information on species distribution during the planning process. Non‐extractive BRUVS provided a useful platform for building the suitability models across large scales to assist conservation planning across multiple maritime jurisdictions, and our approach provides a simple for method for testing the effectiveness of MPAs.     

Assessing the shelf life of cost‐efficient conservation plans for species at risk across gradients of agricultural land use

High costs of land in agricultural regions warrant spatial prioritization approaches to conservation that explicitly consider land prices to produce protected‐area networks that accomplish targets efficiently. However, land‐use changes in such regions and delays between plan design and implementation may render optimized plans obsolete before implementation occurs. To measure the shelf life of cost‐efficient conservation plans, we simulated a land‐acquisition and restoration initiative aimed at conserving species at risk in Canada's farmlands. We accounted for observed changes in land‐acquisition costs and in agricultural intensity based on censuses of agriculture taken from 1986 to 2011. For each year of data, we mapped costs and areas of conservation priority designated using Marxan. We compared plans to test for changes through time in the arrangement of high‐priority sites and in the total cost of each plan. For acquisition costs, we measured the savings from accounting for prices during site selection. Land‐acquisition costs and land‐use intensity generally rose over time independent of inflation (24–78%), although rates of change were heterogeneous through space and decreased in some areas. Accounting for spatial variation in land price lowered the cost of conservation plans by 1.73–13.9%, decreased the range of costs by 19–82%, and created unique solutions from which to choose. Despite the rise in plan costs over time, the high conservation priority of particular areas remained consistent. Delaying conservation in these critical areas may compromise what optimized conservation plans can achieve. In the case of Canadian farmland, rapid conservation action is cost‐effective, even with moderate levels of uncertainty in how to implement restoration goals.     

Effects of Dam‐Induced Landscape Fragmentation on Amazonian Ant–Plant Mutualistic Networks

Mutualistic networks are critical to biological diversity maintenance; however, their structures and functionality may be threatened by a swiftly changing world. In the Amazon, the increasing number of dams poses a large threat to biological diversity because they greatly alter and fragment the surrounding landscape. Tight coevolutionary interactions typical of tropical forests, such as the ant–myrmecophyte mutualism, where the myrmecophyte plants provide domatia nesting space to their symbiotic ants, may be jeopardized by the landscape changes caused by dams. We analyzed 31 ant–myrmecophyte mutualistic networks in undisturbed and disturbed sites surrounding Balbina, the largest Central Amazonian dam. We tested how ant–myrmecophyte networks differ among dam‐induced islands, lake edges, and undisturbed forests in terms of species richness, composition, structure, and robustness (number of species remaining in the network after partner extinctions). We also tested how landscape configuration in terms of area, isolation, shape, and neighborhood alters the structure of the ant–myrmecophyte networks on islands. Ant–myrmecophytic networks were highly compartmentalized in undisturbed forests, and the compartments had few strongly connected mutualistic partners. In contrast, networks at lake edges and on islands were not compartmentalized and were negatively affected by island area and isolation in terms of species richness, density, and composition. Habitat loss and fragmentation led to coextinction cascades that contributed to the elimination of entire ant–plant compartments. Furthermore, many myrmecophytic plants in disturbed sites lost their mutualistic ant partners or were colonized by opportunistic, nonspecialized ants. Robustness of ant–myrmecophyte networks on islands was lower than robustness near lake edges and in undisturbed forest and was particularly susceptible to the extinction of plants. Beyond the immediate habitat loss caused by the building of large dams in Amazonia, persistent edge effects and habitat fragmentation associated with dams had large negative effects on animal–plant mutualistic networks. Efectos de la Fragmentación del Paisaje Inducida por Presas sobre Redes Mutualistas Hormiga‐Planta Amazónicas     

Applying network theory to prioritize multispecies habitat networks that are robust to climate and land‐use change

Designing connected landscapes is among the most widespread strategies for achieving biodiversity conservation targets. The challenge lies in simultaneously satisfying the connectivity needs of multiple species at multiple spatial scales under uncertain climate and land‐use change. To evaluate the contribution of remnant habitat fragments to the connectivity of regional habitat networks, we developed a method to integrate uncertainty in climate and land‐use change projections with the latest developments in network‐connectivity research and spatial, multipurpose conservation prioritization. We used land‐use change simulations to explore robustness of species’ habitat networks to alternative development scenarios. We applied our method to 14 vertebrate focal species of periurban Montreal, Canada. Accounting for connectivity in spatial prioritization strongly modified conservation priorities and the modified priorities were robust to uncertain climate change. Setting conservation priorities based on habitat quality and connectivity maintained a large proportion of the region's connectivity, despite anticipated habitat loss due to climate and land‐use change. The application of connectivity criteria alongside habitat‐quality criteria for protected‐area design was efficient with respect to the amount of area that needs protection and did not necessarily amplify trade‐offs among conservation criteria. Our approach and results are being applied in and around Montreal and are well suited to the design of ecological networks and green infrastructure for the conservation of biodiversity and ecosystem services in other regions, in particular regions around large cities, where connectivity is critically low.     

Rank aggregation of local expert knowledge for conservation planning of the critically endangered saola

There has been much recent interest in using local knowledge and expert opinion for conservation planning, particularly for hard‐to‐detect species. Although it is possible to ask for direct estimation of quantities such as population size, relative abundance is easier to estimate. However, an expert's knowledge is often geographically restricted relative to the area of interest. Combining (or aggregating) experts’ assessments of relative abundance is difficult when each expert only knows a part of the area of interest. We used Google's PageRank algorithm to aggregate ranked abundance scores elicited from local experts through a rapid rural‐appraisal method. We applied this technique to conservation planning for the saola (Pseudoryx nghetinhensis), a poorly known bovid. Near a priority landscape for the species, composed of 3 contiguous protected areas, we asked groups of local people to indicate relative abundances of saola and other species by placing beans on community maps. For each village, we used this information to rank areas within the knowledge area of that village for saola abundance. We used simulations to compare alternative methods to aggregate the rankings from the different villages. The best‐performing method was then used to produce a single map of relative abundance across the entire landscape, an area larger than that known to any one village. This map has informed prioritization of surveys and conservation action in the continued absence of direct information about the saola.     

Quantitative Determination of Rarity of Freshwater Fishes and Implications for Imperiled‐Species Designations

Abstract: Conserving rare species and protecting biodiversity and ecosystem functioning depends on sound information on the nature of rarity. Rarity is multidimensional and has a variety of definitions, which presents the need for a quantitative classification scheme with which to categorize species as rare or common. We constructed such a classification for North American freshwater fishes to better describe rarity in fishes and provide researchers and managers with a tool to streamline conservation efforts. We used data on range extents, habitat specificities, and local population sizes of North American freshwater fishes and a variety of quantitative methods and statistical decision criteria, including quantile regression and a cost‐function algorithm to determine thresholds for categorizing a species as rare or common. Species fell into eight groups that conform to an established framework for rarity. Fishes listed by the American Fisheries Society (AFS) as endangered, threatened, or vulnerable were most often rare because their local population sizes were low, ranges were small, and they had specific habitat needs, in that order, whereas unlisted species were most often considered common on the basis of these three factors. Species with large ranges generally had few specific habitat needs, whereas those with small ranges tended to have narrow habitat specificities. We identified 30 species not designated as imperiled by AFS that were rare along all dimensions of rarity and may warrant further study or protection, and we found three designated species that were common along all dimensions and may require a review of their imperilment status. Our approach could be applied to other taxa to aid conservation decisions and serve as a useful tool for future revisions of listings of fish species.     

Examining the relationship between local extinction risk and position in range

Over half of globally threatened animal species have experienced rapid geographic range loss. Identifying the parts of species’ distributions most vulnerable to local extinction would benefit conservation planning. However, previous studies give little consensus on whether ranges decline to the core or edge. We built on previous work by using empirical data to examine the position of recent local extinctions within species’ geographic ranges, address range position as a continuum, and explore the influence of environmental factors. We aggregated point‐locality data for 125 Galliform species from across the Palearctic and Indo‐Malaya into equal‐area half‐degree grid cells and used a multispecies dynamic Bayesian occupancy model to estimate rates of local extinctions. Our model provides a novel approach to identify loss of populations from within species ranges. We investigated the relationship between extinction rates and distance from range edge by examining whether patterns were consistent across biogeographic realm and different categories of land use. In the Palearctic, local extinctions occurred closer to the range edge than range core in both unconverted and human‐dominated landscapes. In Indo‐Malaya, no pattern was found for unconverted landscapes, but in human‐dominated landscapes extinctions tended to occur closer to the core than the edge. Our results suggest that local and regional factors override general spatial patterns of recent local extinction within species’ ranges and highlight the difficulty of predicting the parts of a species’ distribution most vulnerable to threat.     

A Multispecies Framework for Landscape Conservation Planning

Abstract: Rapidly changing landscapes have spurred the need for quantitative methods for conservation assessment and planning that encompass large spatial extents. We devised and tested a multispecies framework for conservation planning to complement single‐species assessments and ecosystem‐level approaches. Our framework consisted of 4 elements: sampling to effectively estimate population parameters, measuring how human activity affects landscapes at multiple scales, analyzing the relation between landscape characteristics and individual species occurrences, and evaluating and comparing the responses of multiple species to landscape modification. We applied the approach to a community of terrestrial birds across 25,000 km² with a range of intensities of human development. Human modification of land cover, road density, and other elements of the landscape, measured at multiple spatial extents, had large effects on occupancy of the 67 species studied. Forest composition within 1 km of points had a strong effect on occupancy of many species and a range of negative, intermediate, and positive associations. Road density within 1 km of points, percent evergreen forest within 300 m, and distance from patch edge were also strongly associated with occupancy for many species. We used the occupancy results to group species into 11 guilds that shared patterns of association with landscape characteristics. Our multispecies approach to conservation planning allowed us to quantify the trade‐offs of different scenarios of land‐cover change in terms of species occupancy.     

Setting Practical Conservation Priorities for Birds in the Western Andes of Colombia

We aspired to set conservation priorities in ways that lead to direct conservation actions. Very large‐scale strategic mapping leads to familiar conservation priorities exemplified by biodiversity hotspots. In contrast, tactical conservation actions unfold on much smaller geographical extents and they need to reflect the habitat loss and fragmentation that have sharply restricted where species now live. Our aspirations for direct, practical actions were demanding. First, we identified the global, strategic conservation priorities and then downscaled to practical local actions within the selected priorities. In doing this, we recognized the limitations of incomplete information. We started such a process in Colombia and used the results presented here to implement reforestation of degraded land to prevent the isolation of a large area of cloud forest. We used existing range maps of 171 bird species to identify priority conservation areas that would conserve the greatest number of species at risk in Colombia. By at risk species, we mean those that are endemic and have small ranges. The Western Andes had the highest concentrations of such species—100 in total—but the lowest densities of national parks. We then adjusted the priorities for this region by refining these species ranges by selecting only areas of suitable elevation and remaining habitat. The estimated ranges of these species shrank by 18–100% after accounting for habitat and suitable elevation. Setting conservation priorities on the basis of currently available range maps excluded priority areas in the Western Andes and, by extension, likely elsewhere and for other taxa. By incorporating detailed maps of remaining natural habitats, we made practical recommendations for conservation actions. One recommendation was to restore forest connections to a patch of cloud forest about to become isolated from the main Andes. Establecimiento de Prioridades Prácticas para la Conservación de Aves en los Andes Occidentales de Colombia