Explore the vast range of titles available.

Area-based conservation is essential to safeguard nature’s diversity. In view of expanding human land use, increasing climate change and unmet conservation targets, area-based conservation requires efficiency and effectiveness more than ever. In this review, I identify and relate pressing challenges to promising opportunities for effective and efficient protected area governance and management, to enhance research, decision-making and capacity building in area-based conservation under uncertain future developments. I reveal that protected area management is particularly challenged by human land use, climate change, invasive species, and social, political and economic limitations. Protected area management often lacks the continuous availability of data on current states and trends of nature and threats. Biocultural conservation, climate-smart management and biosecurity approaches help to overcome challenges induced by human needs, climate change and invasive species, respectively. Economic valuation and shifts in funding priorities can boost protected area effectiveness and efficiency. In-situ monitoring techniques, remote sensing and open data infrastructures can fill data and information gaps for protected area planning and management. Moreover, adaptive management is an auspicious concept in the framework of systematic conservation planning to ensure the enduring effectiveness of protected areas despite unpredictable future developments. Post-2020 international biodiversity and sustainable development goals could be met earlier if protected areas were more effective. I consequently conclude with the need for a global information system that is to support area-based conservation by synthesizing challenges and opportunities for protected area management effectiveness and efficiency at the local to global level.

To contribute to the aspirations of recent international biodiversity conventions, protected areas (PAs) must be strategically located and not simply established on economically marginal lands as they have in the past. With refined international commitments under the Convention on Biological Diversity to target protected areas in places of \"importance to biodiversity,\" perhaps they may now be. We analyzed location biases in PAs globally over historic (pre-2004) and recent periods. Specifically, we examined whether the location of protected areas are more closely associated with high concentrations of threatened vertebrate species or with areas of low agricultural opportunity costs. We found that both old and new protected areas did not target places with high concentrations of threatened vertebrate species. Instead, they appeared to be established in locations that minimize conflict with agriculturally suitable lands. This entrenchment of past trends has substantial implications for the contributions these protected areas are making to international commitments to conserve biodiversity. If protected-area growth from 2004 to 2014 had strategically targeted unrepresented threatened vertebrates, >30 times more species (3086 or 2553 potential vs. 85 actual new species represented) would have been protected for the same area or the same cost as the actual expansion. With the land available for conservation declining, nations must urgently focus new protection on places that provide for the conservation outcomes outlined in international treaties. Para contribuir con las aspiraciones de las recientes convenciones internacionales por la biodiversidad, las áreas protegidas (APs) deben estar ubicadas estratégicamente y no establecidas simplemente en tierras marginadas económicamente como ha sido en el pasado. Con compromisos internacionales refinados bajo la Convención por la Diversidad Biológica para enfocarse en áreas protegidas en lugares de \"importancia para la biodiversidad\", tal vez las APs ya sean así. Analizamos los sesgos de ubicación de las APs a nivel mundial a través de periodos históricos (antes del 2004) y recientes. En específico, examinamos si la ubicación de las áreas protegidas está asociada más cercanamente con concentraciones altas de especies de vertebrados amenazadas o con áreas de bajo costos de oportunidad agrícola. Encontramos que tanto las áreas protegidas nuevas como las viejas no se enfocaban en lugares con alta concentración de especies de vertebrados amenazadas. En su lugar, parece que están establecidos en localidades que minimizan el conflicto con tierras adecuadas para la agricultura. Este ajuste de las tendencias pasadas tiene implicaciones sustanciales para las contribuciones que estas áreas protegidas están haciendo para los compromisos internacionales para conservar la biodiversidad. Si el crecimiento de las áreas protegidas de 2004 a 2014 se hubiera enfocado estratégicamente en los vertebrados amenazados poco representados, >30 veces más especies (3086 ó 2553 potenciales vs. 85 especies nuevas actuales representadas) habrían sido protegidas por la misma área o al mismo costo que la expansión actual. Con la declinación del suelo disponible para la conservación, los países deben enfocar urgentemente la nueva protección en sitios que proporcionen para los resultados de conservación resaltados en los tratados internacionales.

The practice of conservation occurs within complex socioecological systems fraught with challenges that require transparent, defensible, and often socially engaged project planning and management. Planning and decision support frameworks are designed to help conservation practitioners increase planning rigor, project accountability, stakeholder participation, transparency in decisions, and learning. We describe and contrast five common frameworks within the context of six fundamental questions (why, who, what, where, when, how) at each of three planning stages of adaptive management (project scoping, operational planning, learning). We demonstrate that decision support frameworks provide varied and extensive tools for conservation planning and management. However, using any framework in isolation risks diminishing potential benefits since no one framework covers the full spectrum of potential conservation planning and decision challenges. We describe two case studies that have effectively deployed tools from across conservation frameworks to improve conservation actions and outcomes. Attention to the critical questions for conservation project planning should allow practitioners to operate within any framework and adapt tools to suit their specific management context. We call on conservation researchers and practitioners to regularly use decision support tools as standard practice for framing both practice and research.

ContextAccording to Global Biodiversity Outlook 5, the Aichi Biodiversity Target regarding protected areas (PAs) has been partially achieved with limited progress in valid performance for biodiversity conservation and effective management. This suggests that not only the spatial planning of PAs but also the spatial prioritization for PAs under different management scenarios need more prudent decision-making.ObjectivesWe aim to develop a comprehensive approach to identify and prioritize PAs to maximize the effectiveness of biodiversity conservation while minimize the conservation costs.MethodsTaking Beijing-Tianjin-Hebei region as a case study, we consider the supply and demand of ecosystem services, and landscape connectivity to identify PAs. Systematic conservation planning decision support tool Marxan was employed to identify the priority areas of PAs under multi-target scenarios. The conservation costs, the critical step in the planning process, was estimated using habitat quality evaluation module embedding in InVEST model.ResultsThe results showed that the conservation costs for construction land and unused land were the highest, while the costs for forest land, grassland, and farmland were very low. Sensitivity analysis confirmed the most appropriate conservation goal was 50% of the total area. Therefore, we generated spatial prioritization outcomes based on this target. The highest priority area was mainly located in the northwest of Beijing, the north of Chengde, and the east of Zhangjiakou.ConclusionsIt is concluded that the proposed approach helps decision-makers to identify spatial prioritization for biodiversity conservation based on different scenarios and also yields insights into systematic conservation planning and management.

The contributions of species to ecosystem functions or services depend not only on their presence but also on their local abundance. Progress in predictive spatial modelling has largely focused on species occurrence rather than abundance. As such, limited guidance exists on the most reliable methods to explain and predict spatial variation in abundance. We analysed the performance of 68 abundance‐based species distribution models fitted to 800 000 standardised abundance records for more than 800 terrestrial bird and reef fish species. We found a large amount of variation in the performance of abundance‐based models. While many models performed poorly, a subset of models consistently reconstructed range‐wide abundance patterns. The best predictions were obtained using random forests for frequently encountered and abundant species and for predictions within the same environmental domain as model calibration. Extending predictions of species abundance outside of the environmental conditions used in model training generated poor predictions. Thus, interpolation of abundances between observations can help improve understanding of spatial abundance patterns, but our results indicate extrapolated predictions of abundance under changing climate have a much greater uncertainty. Our synthesis provides a road map for modelling abundance patterns, a key property of species distributions that underpins theoretical and applied questions in ecology and conservation.

Policies and research increasingly focus on the protection of ecosystem services (ESs) through priority-area conservation. Priority areas for ESs should be identified based on ES capacity and ES demand and account for the connections between areas of ES capacity and demand (flow) resulting in areas of unique demand-supply connections (flow zones). We tested ways to account for ES demand and flow zones to identify priority areas in the European Union. We mapped the capacity and demand of a global (carbon sequestration), a regional (flood regulation), and 3 local ESs (air quality, pollination, and urban leisure). We used Zonation software to identify priority areas for ESs based on 6 tests: with and without accounting for ES demand and 4 tests that accounted for the effect of ES flow zone. There was only 37.1% overlap between the 25% of priority areas that encompassed the most ESs with and without accounting for ES demand. The level of ESs maintained in the priority areas increased from 23.2% to 57.9% after accounting for ES demand, especially for ESs with a small flow zone. Accounting for flow zone had a small effect on the location of priority areas and level of ESs maintained but resulted in fewer flow zones without ES maintained relative to ignoring flow zones. Accounting for demand and flow zones enhanced representation and distribution of ESs with local to regional flow zones without large trade-offs relative to the global ES. We found that ignoring ES demand led to the identification of priority areas in remote regions where benefits from ES capacity to society were small. Incorporating ESs in conservation planning should therefore always account for ES demand to identify an effective priority network for ESs. Las políticas y las investigaciones cada vez más se enfocan en la protección de los servicios ambientales (SAs) por medio de la conservación de áreas prioritarias. Las áreas prioritarias para los SAs deberían ser identificadas con base en la capacidad de SAs y la demanda de SAs, y deberían representar las conexiones entre las áreas de capacidad de SAs y la demanda (flujo), resultando así en áreas de conexiones únicas de demanda y suministro (zonas de flujo). Probamos maneras para representar la demanda de SAs y las zonas de flujo para identificar las áreas prioritarias en la Unión Europea. Mapeamos la capacidad y la demanda de un SA global (secuestro de carbono), regional (regulación de inundación), y tres locales (calidad del aire, polinización, y tiempo libre urbano). Usamos el software Zonation para identificar las áreas prioritarias para los SAs con base en seis experimentos: con y sin representación de la demanda de los SAs, y cuatro experimentos que representaron el efecto de la zona de flujo de los SAs. Sólo hubo un traslape de 37.1 % entre el 25 % de las áreas prioritarias que englobaron la mayoría de los SAs con y sin representación de la demanda de SAs. El nivel de los SAs que se mantuvo en las áreas prioritarias incrementó de un 23.2 % a 57.9 % después de considerar la demanda de los SAs, especialmente para aquellos SAs con una zona de flujo reducida. Representar la zona de flujo tuvo un pequeño efecto sobre la ubicación de las áreas prioritarias y el nivel de SAs que se mantuvo, pero resultó en menos zonas de flujo sin SAs mantenidos en relación a ignorar las zonas de flujo. Representar la demanda y las zonas de flujo mejoró la representación y distribución de los SAs con zonas de flujo de regionales a locales sin compensaciones grandes en relación al SA global. Hallamos que ignorar la demanda de SAs llevó a la identificación de las áreas prioritarias en las regiones remotas en donde los beneficios de la capacidad de los SAs para la sociedad fueron pequeños. Incorporar los SAs a la planeación de la conservación por lo tanto debería siempre representar a la demanda de los SAs para identificar una red efectiva de prioridades para los SAs. reducida. Representar la zona de flujo tuvo un pequeño efecto sobre la ubicación de las áreas prioritarias y el nivel de SAs que se mantuvo, pero resultó en menos zonas de flujo sin SAs mantenidos en relación a ignorar las zonas de flujo. Representar la demanda y las zonas de flujo mejoró la representación y distribución de los SAs con zonas de flujo de regionales a locales sin compensaciones grandes en relación al SA global. Hallamos que ignorar la demanda de SAs llevó a la identificación de las áreas prioritarias en las regiones remotas en donde los beneficios de la capacidad de los SAs para la sociedad fueron pequeños. Incorporar los SAs a la planeación de la conservación por lo tanto debería siempre representar a la demanda de los SAs para identificar una red efectiva de prioridades para los SAs.

Aim: To evaluate the representativeness of the current network of protected areas (PAs) of one of the most threatened ecoregions in the world, the South American Gran Chaco, and determine priority conservation areas for endemic (and nearly endemic) terrestrial vertebrates of the region. Location: South America. Methods: We identified all those amphibians, mammals and birds whose distributions were at least 70% within the Gran Chaco. Then, we refined and corrected species' distributional ranges, first, using records from collections and expert knowledge, and second, by incorporating environmental and topographic data using a technique for range polygon refinement. Lastly, we used Zonation, a spatial conservation prioritization software, to evaluate representativeness of the current protected areas (PAs) network of the region and to define forest remnants to strategically expand PAs while maximizing the representativeness of the selected groups and considering human activities. Results: Current PAs cover 9% of the region and represent 9.1% of the total distribution of endemic species. Considering our prioritization, increasing the coverage to 17% to match the Aichi targets would substantially increase the representativeness of the PA network, covering on average more than 30% of the ranges of all endemic species and 77% of the distributions of threatened and DD endemic species. Main conclusions: Our results highlight that the need for well-informed decisions in the Gran Chaco is imperative. While the current PA network in the region ensures a very poor representation of endemic terrestrial vertebrates, opportunities to efficiently expand the PAs network are really high. This emphasizes the potential of complementarity-based systematic conservation planning tools as an essential support for conservation decisions. Given the great information gaps regarding biodiversity and human activities in the region, similar studies with updated data would improve conservation planning in the Gran Chaco in the future.

Climate change is already having profound effects on biodiversity, but climate change adaptation has yet to be fully incorporated into area-based management tools used to conserve biodiversity, such as protected areas. One main obstacle is the lack of consensus regarding how impacts of climate change can be included in spatial conservation plans. We propose a climate-smart framework that prioritizes the protection of climate refugia—areas of low climate exposure and high biodiversity retention—using climate metrics. We explorefour aspects of climate-smart conservation planning: (1) climate model ensembles; (2) multiple emission scenarios; (3) climate metrics; and (4) approaches to identifying climate refugia. We illustrate this framework in the Western Pacific Ocean, but it is equally applicable to terrestrial systems. We found that all aspects of climate-smart conservation planning considered affected the configuration of spatial plans. The choice of climate metrics and approaches to identifying refugia have large effects in the resulting climatesmart spatial plans, whereas the choice of climate models and emission scenarios have smaller effects. As the configuration of spatial plans depended on climate metrics used, a spatial plan based on a single measure of climate change (e.g., warming) will not necessarily be robust against other measures of climate change (e.g., ocean acidification). We therefore recommend using climate metrics most relevant for the biodiversity and region considered based on a single or multiple climate drivers. To include the uncertainty associated with different climate futures, we recommend using multiple climate models (i.e., an ensemble) and emission scenarios. Finally, we show that the approaches we used to identify climate refugia feature trade-offs between: (1) the degree to which they are climate-smart, and (2) their efficiency in meeting conservation targets. Hence, the choice of approach will depend on the relative value that stakeholders place on climate adaptation. By using this framework, protected areas can be designed with improved longevity and thus safeguard biodiversity against current and future climate change. We hope that the proposed climate-smart framework helps transition conservation planning toward climate-smart approaches.

Conservation planning decisions are constrained by three important factors: budgets are limited, important areas for biodiversity compete for space with other uses, and climate‐ and land‐use changes are affecting the distribution of life thus compounding existing threats to biodiversity. Decisions about locating and allocating resources for conservation in such complex and dynamic world are far from trivial, with apparently optimal decisions in the present being potential suboptimal in the future. We propose a methodological framework for the dynamic spatial prioritization of conservation areas that optimizes long‐term conservation goals under climate change. This approach involves a sequential scheduling of conservation areas designation, followed by the release of some areas when they stop contributing to the specified long‐term conservation goals. The usefulness of the proposed approach is demonstrated with a case study involving ten species in the Iberian Peninsula under severe scenarios of climate change, but the framework could be applied more broadly. Species persistence under climate change is enhanced by the dynamic spatial prioritization strategy that assumes area release. With such strategy, the long‐term persistence of species is consistently higher than expected with no release of redundant areas, particularly when the budgets to acquire and manage conservation areas are small. When budgets are small, long‐term persistence of species might only be achieved when the release of previously selected areas is considered alongside the selection of new areas. Synthesis and applications. Given that conservation budgets are typically small, conservation strategies involving the release of some underperforming areas might be required to achieve long‐term persistence of species. This should be the case when climate change forces species to move out of current protected areas with other areas becoming important to meet conservation objectives. Implementing such dynamic prioritization approach would require a paradigm shift in conservation planning because conservation areas, once selected, are rarely released. Dynamic selection of areas also involves risks that should be considered in a case‐by‐case situation.

Context Spatial conservation prioritization (SCP) concerns, for example, identification of spatial priorities for biodiversity conservation or for impact avoidance in economic development. Software useable for SCP include Marxan, C-Plan and Zonation. SCP is often based on data about the distributions of biodiversity features (e.g., species, habitats), costs, threats, and/or ecosystem services (ES). Objectives and methods At simplest ES can be entered into a SCP analysis as independent supply maps, but this is not very satisfactory because connectivity requirements and consequent ideal spatial priority patterns may vary between ES. Therefore, we examine different ES and their connectivity requirements at the conceptual level. Results We find that the ideal spatial priority pattern for ES may differ in terms of: local supply area size and regional network requirements for the maintenance of ES provision, for flow between provision and demand, and with respect to the degree of dispersion that is needed for ES provision and access across different administrative regions. We then identify existing technical options in the Zonation software for dealing with such connectivity requirements of ES in SCP. Conclusions This work helps users of SCP to improve how ES are accounted for in analysis together with biodiversity and other considerations.