Use of Inverse Spatial Conservation Prioritization to Avoid Biological Diversity Loss Outside Protected Areas

Globally expanding human land use sets constantly increasing pressure for maintenance of biological diversity and functioning ecosystems. To fight the decline of biological diversity, conservation science has broken ground with methods such as the operational model of systematic conservation planning (SCP), which focuses on design and on‐the‐ground implementation of conservation areas. The most commonly used method in SCP is reserve selection that focuses on the spatial design of reserve networks and their expansion. We expanded these methods by introducing another form of spatial allocation of conservation effort relevant for land‐use zoning at the landscape scale that avoids negative ecological effects of human land use outside protected areas. We call our method inverse spatial conservation prioritization. It can be used to identify areas suitable for economic development while simultaneously limiting total ecological and environmental effects of that development at the landscape level by identifying areas with highest economic but lowest ecological value. Our method is not based on a priori targets, and as such it is applicable to cases where the effects of land use on, for example, individual species or ecosystem types are relatively small and would not lead to violation of regional or national conservation targets. We applied our method to land‐use allocation to peat mining. Our method identified a combination of profitable production areas that provides the needed area for peat production while retaining most of the landscape‐level ecological value of the ecosystem. The results of this inverse spatial conservation prioritization are being used in land‐use zoning in the province of Central Finland.     

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.     

Reorienting Systematic Conservation Assessment for Effective Conservation Planning

Abstract: Systematic conservation assessment (an information‐gathering and prioritization process used to select the spatial foci of conservation initiatives) is often considered vital to conservation‐planning efforts, yet published assessments have rarely resulted in conservation action. Conservation assessments may lead more directly to effective conservation action if they are reoriented to inform conservation decisions. Toward this goal, we evaluated the relative priority for conservation of 7 sites proposed for the first forest reserves in the Union of the Comoros, an area with high levels of endemism and rapidly changing land uses in the western Indian Ocean. Through the analysis of 30 indicator variables measured at forest sites and nearby villages, we assessed 3 prioritization criteria at each site: conservation value, threat to loss of biological diversity from human activity, and feasibility of reserve establishment. Our results indicated 2 sites, Yiméré and Hassera‐Ndrengé, were priorities for conservation action. Our approach also informed the development of an implementation strategy and enabled an evaluation of previously unexplored relations among prioritization criteria. Our experience suggests that steps taken to ensure the closer involvement of practitioners, include a broader range of social data, encourage stakeholder participation, and consider the feasibility of conservation action can improve the relevance of assessments for conservation planning, strengthen the scientific basis for conservation decisions, and result in a more realistic evaluation of conservation alternatives.     

Effect of Land Cover and Ecosystem Mapping on Ecosystem‐Risk Assessment in the Little Karoo,South Africa

Extinction‐risk assessments aim to identify biological diversity features threatened with extinction. Although largely developed at the species level, these assessments have recently been applied at the ecosystem level. In South Africa, national legislation provides for the listing and protection of threatened ecosystems. We assessed how land‐cover mapping and the detail of ecosystem classification affected the results of risk assessments that were based on extent of habitat loss. We tested 3 ecosystem classifications and 4 land‐cover data sets of the Little Karoo region, South Africa. Degraded land (in particular, overgrazed areas) was successfully mapped in just one of the land‐cover data sets. From <3% to 25% of the Little Karoo was classified as threatened, depending on the land‐cover data set and ecosystem classification applied. The full suite of threatened ecosystems on a fine‐scale map was never completely represented within the spatial boundaries of a coarse‐scale map of threatened ecosystems. Our assessments highlight the importance of land‐degradation mapping for the listing of threatened ecosystems. On the basis of our results, we recommend that when budgets are constrained priority be given to generating more‐detailed land‐cover data sets rather than more‐detailed ecosystem classifications for the assessment of threatened ecosystems. El Efecto de la Cobertura Terrestre y el Mapeo de Ecosistemas en la Valoración de Riesgos en los Ecosistemas en Little Karoo, Sudáfrica     

Understanding the effects of different social data on selecting priority conservation areas

Conservation success is contingent on assessing social and environmental factors so that cost‐effective implementation of strategies and actions can be placed in a broad social–ecological context. Until now, the focus has been on how to include spatially explicit social data in conservation planning, whereas the value of different kinds of social data has received limited attention. In a regional systematic conservation planning case study in Australia, we examined the spatial concurrence of a range of spatially explicit social values and land‐use preferences collected using a public participation geographic information system and biological data. We used Zonation to integrate the social data with the biological data in a series of spatial‐prioritization scenarios to determine the effect of the different types of social data on spatial prioritization compared with biological data alone. The type of social data (i.e., conservation opportunities or constraints) significantly affected spatial prioritization outcomes. The integration of social values and land‐use preferences under different scenarios was highly variable and generated spatial prioritizations 1.2–51% different from those based on biological data alone. The inclusion of conservation‐compatible values and preferences added relatively few new areas to conservation priorities, whereas including noncompatible economic values and development preferences as costs significantly changed conservation priority areas (48.2% and 47.4%, respectively). Based on our results, a multifaceted conservation prioritization approach that combines spatially explicit social data with biological data can help conservation planners identify the type of social data to collect for more effective and feasible conservation actions.     

Representation of critical natural capital in China

Traditional means of assessing representativeness of conservation value in protected areas depend on measures of structural biodiversity. The effectiveness of priority conservation areas at representing critical natural capital (CNC) (i.e., an essential and renewable subset of natural capital) remains largely unknown. We analyzed the representativeness of CNC‐conservation priority areas in national nature reserves (i.e., nature reserves under jurisdiction of the central government with large spatial distribution across the provinces) in China with a new biophysical‐based composite indicator approach. With this approach, we integrated the net primary production of vegetation, topography, soil, and climate variables to map and rank terrestrial ecosystems capacities to generate CNC. National nature reserves accounted for 6.7% of CNC‐conservation priority areas across China. Considerable gaps (35.2%) existed between overall (or potential) CNC representativeness nationally and CNC representation in national reserves, and there was significant spatial heterogeneity of representativeness in CNC‐conservation priority areas at the regional and provincial levels. For example, the best and worst representations were, respectively, 13.0% and 1.6% regionally and 28.9% and 0.0% provincially. Policy in China is transitioning toward the goal of an ecologically sustainable civilization. We identified CNC‐conservation priority areas and conservation gaps and thus contribute to the policy goals of optimization of the national nature reserve network and the demarcation of areas critical to improving the representativeness and conservation of highly functioning areas of natural capital. Moreover, our method for assessing representation of CNC can be easily adapted to other large‐scale networks of conservation areas because few data are needed, and our model is relatively simple.     

Interpreting beta‐diversity components over time to conserve metacommunities in highly dynamic ecosystems

The concept of metacommunity (i.e., a set of local communities linked by dispersal) has gained great popularity among community ecologists. However, metacommunity research mostly addresses questions on spatial patterns of biodiversity at the regional scale, whereas conservation planning requires quantifying temporal variation in those metacommunities and the contributions that individual (local) sites make to regional dynamics. We propose that recent advances in diversity‐partitioning methods may allow for a better understanding of metacommunity dynamics and the identification of keystone sites. We used time series of the 2 components of beta diversity (richness and replacement) and the contributions of local sites to these components to examine which sites controlled source‐sink dynamics in a highly dynamic model system (an intermittent river). The relative importance of the richness and replacement components of beta diversity fluctuated over time, and sample aggregation led to underestimation of beta diversity by up to 35%. Our literature review revealed that research on intermittent rivers would benefit greatly from examination of beta‐diversity components over time. Adequately appraising spatiotemporal variability in community composition and identifying sites that are pivotal for maintaining biodiversity at the landscape scale are key needs for conservation prioritization and planning. Thus, our framework may be used to guide conservation actions in highly dynamic ecosystems when time‐series data describing biodiversity across sites connected by dispersal are available.     

Prioritizing sites for conservation based on similarity to historical baselines and feasibility of protection

The concept of shifting baselines in conservation science implies advocacy for the use of historical knowledge to inform these baselines but does not address the feasibility of restoring sites to those baselines. In many regions, conservation feasibility varies among sites due to differences in resource availability, statutory power, and land‐owner participation. We used zooarchaeological records to identify a historical baseline of the freshwater mussel community's composition before Euro‐American influence at a river‐reach scale (i.e., a kilometer stretch of river that is abiotically similar) in the Leon River of central Texas (U.S.A.). We evaluated how the community reference position and the feasibility of conservation might enable identification of sites where conservation actions would preserve historically representative communities and be likely to succeed. We devised a conceptual model that incorporated community information and landscape factors to link the best conservation areas to potential cost and conservation benefits. Using fuzzy ordination, we identified modern mussel beds that were most like the historical baseline. We then quantified housing density and land use near each river reach identified to estimate feasibility of habitat restoration. Using our conceptual framework, we identified reaches of high conservation value (i.e., contain the best mussel beds) and where restoration actions would be most likely to succeed. Reaches above Lake Belton were most similar in species composition and relative abundance to zooarchaeological sites. A subset of these mussel beds occurred in locations where conservation actions appeared most feasible. Our results show how to use zooarchaeological data (biodiversity data often readily available) and estimates of conservation feasibility to inform conservation priorities at a local spatial scale.     

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.     

A Comparison of Global Conservation Prioritization Models with Spatial Spending Patterns of Conservation Nongovernmental Organizations

Abstract: In recent decades, various conservation organizations have developed models to prioritize locations for conservation. Through a survey of the spending patterns of 281 conservation nongovernmental organizations (NGOs), we examined the relation between 2 such models and spatial patterns of spending by conservation NGOs in 44 countries in sub‐Saharan Africa. We tested whether, at the country level, the proportion of a country designated as a conservation priority was correlated with where NGOs spent money. For one model (the combination of Conservation International's hotspots and High Biodiversity Wilderness Areas, which are areas of high endemism with high or low levels of vegetation loss respectively), there was no relation between the proportion of a country designated as a priority and levels of NGO spending, including by the NGO associated with the model. In the second model (Global 200), the proportion of a country designated as a priority and the amount of money spent by NGOs were significantly and positively related. Less money was spent in countries in northern and western sub‐Saharan Africa than countries in southern and eastern Africa, relative to the proportion of the country designated as a conservation priority. We suggest that on the basis of our results some NGOs consider increasing their spending on the areas designated as of conservation priority which are currently relatively underfunded, although there are economic, political, cultural, historical, biological, and practical reasons why current spending patterns may not align with priority sites.     

Setting conservation priorities for migratory networks under uncertainty

Conserving migratory species requires protecting connected habitat along the pathways they travel. Despite recent improvements in tracking animal movements, migratory connectivity remains poorly resolved at a population level for the vast majority of species, thus conservation prioritization is hampered. To address this data limitation, we developed a novel approach to spatial prioritization based on a model of potential connectivity derived from empirical data on species abundance and distance traveled between sites during migration. We applied the approach to migratory shorebirds of the East Asian‐Australasian Flyway. Conservation strategies that prioritized sites based on connectivity and abundance metrics together maintained larger populations of birds than strategies that prioritized sites based only on abundance metrics. The conservation value of a site therefore depended on both its capacity to support migratory animals and its position within the migratory pathway; the loss of crucial sites led to partial or total population collapse. We suggest that conservation approaches that prioritize sites supporting large populations of migrants should, where possible, also include data on the spatial arrangement of sites.     

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     

Spatial,socio‐economic,and ecological implications of incorporating minimum size constraints in marine protected area network design

Marine protected areas (MPAs) are the cornerstone of most marine conservation strategies, but the effectiveness of each one partly depends on its size and distance to other MPAs in a network. Despite this, current recommendations on ideal MPA size and spacing vary widely, and data are lacking on how these constraints might influence the overall spatial characteristics, socio‐economic impacts, and connectivity of the resultant MPA networks. To address this problem, we tested the impact of applying different MPA size constraints in English waters. We used the Marxan spatial prioritization software to identify a network of MPAs that met conservation feature targets, whilst minimizing impacts on fisheries; modified the Marxan outputs with the MinPatch software to ensure each MPA met a minimum size; and used existing data on the dispersal distances of a range of species found in English waters to investigate the likely impacts of such spatial constraints on the region's biodiversity. Increasing MPA size had little effect on total network area or the location of priority areas, but as MPA size increased, fishing opportunity cost to stakeholders increased. In addition, as MPA size increased, the number of closely connected sets of MPAs in networks and the average distance between neighboring MPAs decreased, which consequently increased the proportion of the planning region that was isolated from all MPAs. These results suggest networks containing large MPAs would be more viable for the majority of the region's species that have small dispersal distances, but dispersal between MPA sets and spill‐over of individuals into unprotected areas would be reduced. These findings highlight the importance of testing the impact of applying different MPA size constraints because there are clear trade‐offs that result from the interaction of size, number, and distribution of MPAs in a network.     

Mapping Human and Social Dimensions of Conservation Opportunity for the Scheduling of Conservation Action on Private Land

Abstract Spatial prioritization techniques are applied in conservation‐planning initiatives to allocate conservation resources. Although typically they are based on ecological data (e.g., species, habitats, ecological processes), increasingly they also include nonecological data, mostly on the vulnerability of valued features and economic costs of implementation. Nevertheless, the effectiveness of conservation actions implemented through conservation‐planning initiatives is a function of the human and social dimensions of social‐ecological systems, such as stakeholders’ willingness and capacity to participate. We assessed human and social factors hypothesized to define opportunities for implementing effective conservation action by individual land managers (those responsible for making day‐to‐day decisions on land use) and mapped these to schedule implementation of a private land conservation program. We surveyed 48 land managers who owned 301 land parcels in the Makana Municipality of the Eastern Cape province in South Africa. Psychometric statistical and cluster analyses were applied to the interview data so as to map human and social factors of conservation opportunity across a landscape of regional conservation importance. Four groups of landowners were identified, in rank order, for a phased implementation process. Furthermore, using psychometric statistical techniques, we reduced the number of interview questions from 165 to 45, which is a preliminary step toward developing surrogates for human and social factors that can be developed rapidly and complemented with measures of conservation value, vulnerability, and economic cost to more‐effectively schedule conservation actions. This work provides conservation and land management professionals direction on where and how implementation of local‐scale conservation should be undertaken to ensure it is feasible.     

Drivers of Seabird Population Recovery on New Zealand Islands after Predator Eradication

Eradication of introduced mammalian predators from islands has become increasingly common, with over 800 successful projects around the world. Historically, introduced predators extirpated or reduced the size of many seabird populations, changing the dynamics of entire island ecosystems. Although the primary outcome of many eradication projects is the restoration of affected seabird populations, natural population responses are rarely documented and mechanisms are poorly understood. We used a generic model of seabird colony growth to identify key predictor variables relevant to recovery or recolonization. We used generalized linear mixed models to test the importance of these variables in driving seabird population responses after predator eradication on islands around New Zealand. The most influential variable affecting recolonization of seabirds around New Zealand was the distance to a source population, with few cases of recolonization without a source population ≤25 km away. Colony growth was most affected by metapopulation status; there was little colony growth in species with a declining status. These characteristics may facilitate the prioritization of newly predator‐free islands for active management. Although we found some evidence documenting natural recovery, generally this topic was understudied. Our results suggest that in order to guide management strategies, more effort should be allocated to monitoring wildlife response after eradication. Conductores de la Recuperación de Poblaciones de Aves Marinas en Islas de Nueva Zelanda después de la Erradicación de Depredadores     

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.     

Global status of and prospects for protection of terrestrial geophysical diversity

Conservation of representative facets of geophysical diversity may help conserve biological diversity as the climate changes. We conducted a global classification of terrestrial geophysical diversity and analyzed how land protection varies across geophysical diversity types. Geophysical diversity was classified in terms of soil type, elevation, and biogeographic realm and then compared to the global distribution of protected areas in 2012. We found that 300 (45%) of 672 broad geophysical diversity types currently meet the Convention on Biological Diversity's Aichi Target 11 of 17% terrestrial areal protection, which suggested that efforts to implement geophysical diversity conservation have a substantive basis on which to build. However, current protected areas were heavily biased toward high elevation and low fertility soils. We assessed 3 scenarios of protected area expansion and found that protection focused on threatened species, if fully implemented, would also protect an additional 29% of geophysical diversity types, ecoregional‐focused protection would protect an additional 24%, and a combined scenario would protect an additional 42%. Future efforts need to specifically target low‐elevation sites with productive soils for protection and manage for connectivity among geophysical diversity types. These efforts may be hampered by the sheer number of geophysical diversity facets that the world contains, which makes clear target setting and prioritization an important next step.     

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.     

Applying the dark diversity concept to nature conservation

Linking diversity to biological processes is central for developing informed and effective conservation decisions. Unfortunately, observable patterns provide only a proportion of the information necessary for fully understanding the mechanisms and processes acting on a particular population or community. We suggest conservation managers use the often overlooked information relative to species absences and pay particular attention to dark diversity (i.e., a set of species that are absent from a site but that could disperse to and establish there, in other words, the absent portion of a habitat‐specific species pool). Together with existing ecological metrics, concepts, and conservation tools, dark diversity can be used to complement and further develop conservation prioritization and management decisions through an understanding of biodiversity relativized by its potential (i.e., its species pool). Furthermore, through a detailed understanding of the population, community, and functional dark diversity, the restoration potential of degraded habitats can be more rigorously assessed and so to the likelihood of successful species invasions. We suggest the application of the dark diversity concept is currently an underappreciated source of information that is valuable for conservation applications ranging from macroscale conservation prioritization to more locally scaled restoration ecology and the management of invasive species.     

Prioritizing Conservation Effort through the Use of Biological Soil Crusts as Ecosystem Function Indicators in an Arid Region

Abstract: Conservation prioritization usually focuses on conservation of rare species or biodiversity, rather than ecological processes. This is partially due to a lack of informative indicators of ecosystem function. Biological soil crusts (BSCs) trap and retain soil and water resources in arid ecosystems and function as major carbon and nitrogen fixers; thus, they may be informative indicators of ecosystem function. We created spatial models of multiple indicators of the diversity and function of BSCs (species richness, evenness, functional diversity, functional redundancy, number of rare species, number of habitat specialists, nitrogen and carbon fixation indices, soil stabilization, and surface roughening) for the 800,000‐ha Grand Staircase‐Escalante National Monument (Utah, U.S.A.). We then combined the indicators into a single BSC function map and a single BSC biodiversity map (2 alternative types of conservation value) with an unweighted averaging procedure and a weighted procedure derived from validations performance. We also modeled potential degradation with data from a rangeland assessment survey. To determine which areas on the landscape were the highest conservation priorities, we overlaid the function‐ and diversity‐based conservation‐value layers on the potential degradation layer. Different methods for ascribing conservation‐value and conservation‐priority layers all yielded strikingly similar results (r= 0.89–0.99), which suggests that in this case biodiversity and function can be conserved simultaneously. We believe BSCs can be used as indicators of ecosystem function in concert with other indicators (such as plant‐community properties) and that such information can be used to prioritize conservation effort in drylands.