Using Phylogenetic Diversity Measures to Set Priorities in Conservation: an Example from Southern South America

Abstract: Phylogenetic diversity measures rank areas for biodiversity conservation priorities based on information encoded in phylogenies (cladograms). The goal of these ranks for conservation is to consider as many factors as possible that provide additional taxic information, such as taxa richness, taxa distributional patterns, area endemicity, and complementarity between areas. At present there are many measures that consider phylogenetic information, including node-based, genetic-distance, and feature-based measures. We devised a modified phylogenetic node-based index that we call "taxonomic endemicity standardized weight," which considers not only the taxonomic distinctness of the taxa that inhabit a given area but their endemicity as well. Once the standardized weight of the taxonomic endemicity identifies the area of highest priority, complementarity can be used to identify the second area and so on. We used this node-based index to rank priority areas for conservation in southern South America, and we compared the results of our rankings to results based on other node-based indexes. Our index identified Santiago district, in Central Chile province, as the highest priority area for conservation, followed by Maule, Malvinas, and districts of Subantarctic province. Malvinas exhibits greater complementarity relative to Santiago than Maule does, however, so Malvinas is ranked second in priority. Indexes based on phylogenetic information measure the evolutionary component of biodiversity and allow one to identify areas that will ensure the preservation of evolutionary potential and phylogenetically rare taxa. The modified index we propose is sensitive to taxic distinctness and endemicity as well and allows information from diverse taxa to be combined (i.e., different cladograms). The use of complementarity allows for preservation of the maximum quantity of taxa in a minimal number of protected areas.     

The Silent Mass Extinction of Insect Herbivores in Biodiversity Hotspots

Abstract: Habitat loss is silently leading numerous insects to extinction. Conservation efforts, however, have not been designed specifically to protect these organisms, despite their ecological and evolutionary significance. On the basis of species–host area equations, parameterized with data from the literature and interviews with botanical experts, I estimated the number of specialized plant‐feeding insects (i.e., monophages) that live in 34 biodiversity hotspots and the number committed to extinction because of habitat loss. I estimated that 795,971–1,602,423 monophagous insect species live in biodiversity hotspots on 150,371 endemic plant species, which is 5.3–10.6 monophages per plant species. I calculated that 213,830–547,500 monophagous species are committed to extinction in biodiversity hotspots because of reduction of the geographic range size of their endemic hosts. I provided rankings of biodiversity hotspots on the basis of estimated richness of monophagous insects and on estimated number of extinctions of monophagous species. Extinction rates were predicted to be higher in biodiversity hotspots located along strong environmental gradients and on archipelagos, where high spatial turnover of monophagous species along the geographic distribution of their endemic plants is likely. The results strongly support the overall strategy of selecting priority conservation areas worldwide primarily on the basis of richness of endemic plants. To face the global decline of insect herbivores, one must expand the coverage of the network of protected areas and improve the richness of native plants on private lands.     

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.     

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.     

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.     

Identifying conservation priorities for threatened Eastern Himalayan mammals

To augment mammal conservation in the Eastern Himalayan region, we assessed the resident 255 terrestrial mammal species and identified the 50 most threatened species based on conservation status, endemism, range size, and evolutionary distinctiveness. By using the spatial analysis package letsR and the complementarity core‐area method in the conservation planning software Zonation, we assessed the current efficacy of their protection and identified priority conservation areas by comparing protected areas (PAs), land cover, and global ecoregion 2017 maps at a 100 × 100 m spatial scale. The 50 species that were most threatened, geographically restricted, and evolutionarily distinct faced a greater extinction risk than globally nonthreatened and wide‐ranging species and species with several close relatives. Small, medium‐sized, and data‐deficient species faced extinction from inadequate protection in PAs relative to wide‐ranging charismatic species. There was a mismatch between current PA distribution and priority areas for conservation of the 50 most endangered species. To protect these species, the skewed regional PA distribution would require expansion. Where possible, new PAs and transboundary reserves in the 35 priority areas we identified should be established. There are adequate remaining natural areas in which to expand current Eastern Himalayan PAs. Consolidation and expansion of PAs in the EH requires strengthening national and regional transboundary collaboration, formulating comprehensive regional land‐use plans, diversifying conservation funding, and enhancing information sharing through a consolidated regional database.     

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.     

Conservation planning on China's borders with Myanmar,Laos, and Vietnam

Transboundary conservation is playing an increasingly important role in maintaining ecosystem integrity and halting biodiversity loss caused by anthropogenic activities. However, lack of information on species distributions in transboundary regions and understanding of the threats in these areas impairs conservation. We developed a spatial conservation plan for the transboundary areas between Yunnan province, southwestern China, and neighboring Myanmar, Laos, and Vietnam in the Indo-Burma biodiversity hotspot. To identify priority areas for conservation and restoration, we determined species distribution patterns and recent land-use changes and examined the spatiotemporal dynamics of the connected natural forest, which supports most species. We assessed connectivity with equivalent connected area (ECA), which is the amount of reachable habitat for a species. An ECA incorporates the presence of habitat in a patch and the amount of habitat in other patches within dispersal distance. We analyzed 197,845 locality records from specimen collections and monographs for 21,004 plant and vertebrate species. The region of Yunnan immediately adjacent to the international borders had the highest species richness, with 61% of recorded species and 56% of threatened vertebrates, which suggests high conservation value. Satellite imagery showed the area of natural forest in the border zone declined by 5.2% (13,255 km²) from 1995 to 2018 and monoculture plantations increased 92.4%, shrubland 10.1%, and other cropland 6.2%. The resulting decline in connected natural forest reduced the amount of habitat, especially for forest specialists with limited dispersal abilities. The most severe decline in connectivity was along the Sino-Vietnamese border. Many priority areas straddle international boundaries, indicating demand and potential for establishing transboundary protected areas. Our results illustrate the importance of bi- and multilateral cooperation to protect biodiversity in this region and provide guidance for future conservation planning and practice.     

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.     

Integrating Habitat Status, Human Population Pressure, and Protection Status into Biodiversity Conservation Priority Setting

Abstract:  Priority setting is an essential component of biodiversity conservation. Existing methods to identify priority areas for conservation have focused almost entirely on biological factors. We suggest a new relative ranking method for identifying priority conservation areas that integrates both biological and social aspects. It is based on the following criteria: the habitat's status, human population pressure, human efforts to protect habitat, and number of endemic plant and vertebrate species. We used this method to rank 25 hotspots, 17 megadiverse countries, and the hotspots within each megadiverse country. We used consistent, comprehensive, georeferenced, and multiband data sets and analytical remote sensing and geographic information system tools to quantify habitat status, human population pressure, and protection status. The ranking suggests that the Philippines, Atlantic Forest, Mediterranean Basin, Caribbean Islands, Caucasus, and Indo-Burma are the hottest hotspots and that China, the Philippines, and India are the hottest megadiverse countries. The great variation in terms of habitat, protected areas, and population pressure among the hotspots, the megadiverse countries, and the hotspots within the same country suggests the need for hotspot- and country-specific conservation policies.     

Where the wild things are: predicting hotspots of seabird aggregations in the California Current System

Marine protected areas (MPAs) provide an important tool for conservation of marine ecosystems. To be most effective, these areas should be strategically located in a manner that supports ecosystem function. To inform marine spatial planning and support strategic establishment of MPAs within the California Current System, we identified areas predicted to support multispecies aggregations of seabirds ("hotspots"). We developed habitat-association models for 16 species using information from at-sea observations collected over an 11-year period (1997-2008), bathymetric data, and remotely sensed oceanographic data for an area from north of Vancouver Island, Canada, to the USA/Mexico border and seaward 600 km from the coast. This approach enabled us to predict distribution and abundance of seabirds even in areas of few or no surveys. We developed single-species predictive models using a machine-learning algorithm: bagged decision trees. Single-species predictions were then combined to identify potential hotspots of seabird aggregation, using three criteria: (1) overall abundance among species, (2) importance of specific areas ("core areas") to individual species, and (3) predicted persistence of hotspots across years. Model predictions were applied to the entire California Current for four seasons (represented by February, May, July, and October) in each of 11 years. Overall, bathymetric variables were often important predictive variables, whereas oceanographic variables derived from remotely sensed data were generally less important. Predicted hotspots often aligned with currently protected areas (e.g., National Marine Sanctuaries), but we also identified potential hotspots in Northern California/Southern Oregon (from Cape Mendocino to Heceta Bank), Southern California (adjacent to the Channel Islands), and adjacent to Vancouver Island, British Columbia, that are not currently included in protected areas. Prioritization and identification of multispecies hotspots will depend on which group of species is of highest management priority. Modeling hotspots at a broad spatial scale can contribute to MPA site selection, particularly if complemented by fine-scale information for focal areas.     

Plant Diversity Hotspots in the Atlantic Coastal Forests of Brazil

Abstract:  Plant-diversity hotspots on a global scale are well established, but smaller local hotspots within these must be identified for effective conservation of plants at the global and local scales. We used the distributions of endemic and endemic-threatened species of Myrtaceae to indicate areas of plant diversity and conservation importance within the Atlantic coastal forests ( Mata Atlântica ) of Brazil. We applied 3 simple, inexpensive geographic information system (GIS) techniques to a herbarium specimen database: predictive species-distribution modeling (Maxent); complementarity analysis (DIVA-GIS); and mapping of herbarium specimen collection locations. We also considered collecting intensity, which is an inherent limitation of use of natural history records for biodiversity studies. Two separate areas of endemism were evident: the Serra do Mar mountain range from Paraná to Rio de Janeiro and the coastal forests of northern Espírito Santo and southern Bahia. We identified 12 areas of approximately 35 km² each as priority areas for conservation. These areas had the highest species richness and were highly threatened by urban and agricultural expansion. Observed species occurrences, species occurrences predicted from the model, and results of our complementarity analysis were congruent in identifying those areas with the most endemic species. These areas were then prioritized for conservation importance by comparing ecological data for each.     

A Phylogenetic Approach to Conserving Amazonian Biodiversity

Abstract: Amazonia is a highly threatened rainforest that encompasses a major proportion of Earth's biological diversity. Our main goal was to establish conservation priorities for Amazonia's areas of endemism on the basis of measures of evolutionary distinctiveness. We considered two previously identified sets of areas of endemism. The first set consisted of eight large areas used traditionally in biogeographical studies: Belém, Tapajós, Xingu, Guiana, Rondônia, Imeri, Inambari, and Napo. The second set consisted of 16 smaller areas that were subdivisions of the larger areas. We assembled a data set of 50 phylogenies that represented 16 orders and 1715 distributional records. We identified priority conservation areas for the areas of endemism according to node‐based metrics of evolutionary distinctiveness. We contrasted these results with priority areas identified on the basis of raw species richness and species endemicity. For the larger areas, we identified Guiana and Inambari as the first‐ and second‐most important areas for conservation. The remaining areas in this first group scored half (e.g., Napo) or less than Guiana and Inambari on all indices. For the smaller areas, a subdivision of Guiana (i.e., Guyana and the Brazilian states of Roraima and Amazonas) was at the top of the ranking and was followed by a subdivision of Inambari (i.e., northwestern portion of Amazonas) and then another subdivision of Guiana (i.e., Suriname, French Guiana, and the Brazilian state of Amapá). The distinctiveness‐based rankings of the priority of areas correlated directly with those derived from species richness and species endemicity. Current conservation strategies in Amazonia, although they rely on many other criteria apart from phylogeny, are focusing on the most important areas for conservation we identified here.     

西藏生态整体性水平测度

为了探讨资源-环境双重约束下地处我国生态环境脆弱区的西藏的生态整体性特征,利用生态环境质量指数和生态现代化指数（EMI）对地处我国西南边陲的西藏地区的生态现代化水平进行了分析。结果表明：全球生态现代化水平在区域之间存在比较明显的空间分异。2004年西藏生态现代化指数为50,在全国排名为3位,较2000年的排名16位有了明显的提高。生态进步指数、经济生态化指数好于其他4个少数民族地区,但社会生态化指数落后于其他4个少数民族地区,人均SO2排放与新疆、广西相同,但高于内蒙古和宁夏;1980—2007年西藏现代化程度虽然有所提升,但远低于世界平均水平和中等发达国家以及我国平均水平和其他4个少数民族地区;1996—2007年西藏区域环境水平呈＂W＂型变动态势。资源转化率和水污染指数呈＂N＂型不稳定变动,生态保护指数和环境治理指数呈剧烈变动,生态脆弱性和环境支持系统的不稳定性没有明显改观。因此,西藏应立足地缘和资源优势,充分考虑西藏生态地域、生态系统服务功能、生态资产、生态敏感性以及人类活动对生态环境胁迫等要素的综合影响,依据青藏高原高寒生态大区和高寒草甸生态区、青藏高原高山草原、高寒草甸生态地区生态区划,发展人工设计生态方案的生态重建途径。建立严格的生态补偿制度,逐步提升生态现代化水平。     

Economic and Ecological Outcomes of Flexible Biodiversity Offset Systems

The commonly expressed goal of biodiversity offsets is to achieve no net loss of specific biological features affected by development. However, strict equivalency requirements may complicate trading of offset credits, increase costs due to restricted offset placement options, and force offset activities to focus on features that may not represent regional conservation priorities. Using the oil sands industry of Alberta, Canada, as a case study, we evaluated the economic and ecological performance of alternative offset systems targeting either ecologically equivalent areas (vegetation types) or regional conservation priorities (caribou and the Dry Mixedwood natural subregion). Exchanging dissimilar biodiversity elements requires assessment via a generalized metric; we used an empirically derived index of biodiversity intactness to link offsets with losses incurred by development. We considered 2 offset activities: land protection, with costs estimated as the net present value of profits of petroleum and timber resources to be paid as compensation to resource tenure holders, and restoration of anthropogenic footprint, with costs estimated from existing restoration projects. We used the spatial optimization tool MARXAN to develop hypothetical offset networks that met either the equivalent‐vegetation or conservation‐priority targets. Networks that required offsetting equivalent vegetation cost 2–17 times more than priority‐focused networks. This finding calls into question the prudence of equivalency‐based systems, particularly in relatively undeveloped jurisdictions, where conservation focuses on limiting and directing future losses. Priority‐focused offsets may offer benefits to industry and environmental stakeholders by allowing for lower‐cost conservation of valued ecological features and may invite discussion on what land‐use trade‐offs are acceptable when trading biodiversity via offsets. Resultados Económicos y Ecológicos de Sistemas de Compensación de Biodiversidad Flexible Habib et al.     

Determining the drivers of population structure in a highly urbanized landscape to inform conservation planning

Understanding the environmental contributors to population structure is of paramount importance for conservation in urbanized environments. We used spatially explicit models to determine genetic population structure under current and future environmental conditions across a highly fragmented, human‐dominated environment in Southern California to assess the effects of natural ecological variation and urbanization. We focused on 7 common species with diverse habitat requirements, home‐range sizes, and dispersal abilities. We quantified the relative roles of potential barriers, including natural environmental characteristics and an anthropogenic barrier created by a major highway, in shaping genetic variation. The ability to predict genetic variation in our models differed among species: 11–81% of intraspecific genetic variation was explained by environmental variables. Although an anthropogenically induced barrier (a major highway) severely restricted gene flow and movement at broad scales for some species, genetic variation seemed to be primarily driven by natural environmental heterogeneity at a local level. Our results show how assessing environmentally associated variation for multiple species under current and future climate conditions can help identify priority regions for maximizing population persistence under environmental change in urbanized regions.     

Predicting the Spatial Distribution of a Seabird Community to Identify Priority Conservation Areas in the Timor Sea

Understanding spatial and temporal variability in the distribution of species is fundamental to the conservation of marine and terrestrial ecosystems. To support strategic decision making aimed at sustainable management of the oceans, such as the establishment of protected areas for marine wildlife, we identified areas predicted to support multispecies seabird aggregations in the Timor Sea. We developed species distribution models for 21 seabird species based on at‐sea survey observations from 2000–2013 and oceanographic variables (e.g., bathymetry). We applied 4 statistical modeling techniques and combined the results into an ensemble model with robust performance. The ensemble model predicted the probability of seabird occurrence in areas where few or no surveys had been conducted and demonstrated 3 areas of high seabird richness that varied little between seasons. These were located within 150 km of Adele Island, Ashmore Reef, and the Lacepede Islands, 3 of the largest aggregations of breeding seabirds in Australia. Although these breeding islands were foci for high species richness, model performance was greatest for 3 nonbreeding migratory species that would have been overlooked had regional monitoring been restricted to islands. Our results indicate many seabird hotspots in the Timor Sea occur outside existing reserves (e.g., Ashmore Reef Marine Reserve), where shipping, fisheries, and offshore development likely pose a threat to resident and migratory populations. Our results highlight the need to expand marine spatial planning efforts to ensure biodiversity assets are appropriately represented in marine reserves. Correspondingly, our results support the designation of at least 4 new important bird areas, for example, surrounding Adele Island and Ashmore Reef. Pronostico de la Distribución Espacial de una Comunidad de Aves Marinas para Identificar Áreas Prioritarias de Conservación en el Mar de Timor     

Addressing transboundary conservation challenges through marine spatial prioritization

The Adriatic and Ionian Region is an important area for both strategic maritime development and biodiversity conservation in the European Union (EU). However, given that both EU and non‐EU countries border the sea, multiple legal and regulatory frameworks operate at different scales, which can hinder the coordinated long‐term sustainable development of the region. Transboundary marine spatial planning can help overcome these challenges by building consensus on planning objectives and making the trade‐offs between biodiversity conservation and its influence on economically important sectors more explicit. We address this challenge by developing and testing 4 spatial prioritization strategies with the decision‐support tool Marxan, which meets targets for biodiversity conservation while minimizing impacts to users. We evaluated these strategies in terms of how priority areas shift under different scales of target setting (e.g., regional vs. country level). We also examined the trade‐off between cost‐efficiency and how equally solutions represent countries and maritime industries (n = 14) operating in the region with the protection‐equality metric. We found negligible differences in where priority conservation areas were located when we set targets for biodiversity at the regional versus country scale. Conversely, the prospective impacts on industries, when considered as costs to be minimized, were highly divergent across scenarios and biased the placement of protection toward industries located in isolation or where there were few other industries. We recommend underpinning future marine spatial planning efforts in the region through identification of areas of national significance, transboundary areas requiring cooperation between countries, and areas where impacts on maritime industries require careful consideration of the trade‐off between biodiversity conservation and socioeconomic objectives.     

Knowledge co‐production and boundary work to promote implementation of conservation plans

Knowledge co‐production and boundary work offer planners a new frame for critically designing a social process that fosters collaborative implementation of resulting plans. Knowledge co‐production involves stakeholders from diverse knowledge systems working iteratively toward common vision and action. Boundary work is a means of creating permeable knowledge boundaries that satisfy the needs of multiple social groups while guarding the functional integrity of contributing knowledge systems. Resulting products are boundary objects of mutual interest that maintain coherence across all knowledge boundaries. We examined how knowledge co‐production and boundary work can bridge the gap between planning and implementation and promote cross‐sectoral cooperation. We applied these concepts to well‐established stages in regional conservation planning within a national scale conservation planning project aimed at identifying areas for conserving rivers and wetlands of South Africa and developing an institutional environment for promoting their conservation. Knowledge co‐production occurred iteratively over 4 years in interactive stake‐holder workshops that included co‐development of national freshwater conservation goals and spatial data on freshwater biodiversity and local conservation feasibility; translation of goals into quantitative inputs that were used in Marxan to select draft priority conservation areas; review of draft priority areas; and packaging of resulting map products into an atlas and implementation manual to promote application of the priority area maps in 37 different decision‐making contexts. Knowledge co‐production stimulated dialogue and negotiation and built capacity for multi‐scale implementation beyond the project. The resulting maps and information integrated diverse knowledge types of over 450 stakeholders and represented >1000 years of collective experience. The maps provided a consistent national source of information on priority conservation areas for rivers and wetlands and have been applied in 25 of the 37 use contexts since their launch just over 3 years ago. When framed as a knowledge co‐production process supported by boundary work, regional conservation plans can be developed into valuable boundary objects that offer a tangible tool for multi‐agency cooperation around conservation. Our work provides practical guidance for promoting uptake of conservation science and contributes to an evidence base on how conservation efforts can be improved.     

A Comparison of Richness Hotspots, Rarity Hotspots, and Complementary Areas for Conserving Diversity of British Birds

Biodiversity conservation requires efficient methods for choosing priority areas for in situ conservation management. We compared three quantitative methods for choosing 5% (an arbitrary figure) of all the 10 × 10 km grid cells in Britain to represent the diversity of breeding birds: (1) hotspots of richness, which selects the areas richest in species; (2) hotspots of range-size rarity (narrow endemism), which selects areas richest in those species with the most restricted ranges; and (3) sets of complementary areas, which selects areas with the greatest combined species richness. Our results show that richness hotspots contained the highest number of species-in-grid-cell records (with many representations of the more widespread species), whereas the method of complementary areas obtained the lowest number. However, whereas richness hotspots included representation of 89% of British species of breeding birds, and rarity hotspots included 98%, the areas chosen using complementarity represented all the species, where possible, at least six times over. The method of complementary areas was also well suited to supplementing the existing conservation network. For example, starting with grid cells with over 50% area cover by existing "Sites of Special Scientific Interest," we searched for a set of areas that could complete the representation of all the most threatened birds in Britain, the Red Data species. The method of complementary areas distinguishes between irreplaceable and flexible areas, which helps planners by providing alternatives for negotiation. This method can also show which particular species justify the choice of each area. Yet the complementary areas method will not be fully able to select the best areas for conservation management until we achieve integration of some of the more important factors affecting viability, threat, and cost.