Global rarity of intact coastal regions.

Management of the land-sea interface is essential for global conservation and sustainability objectives because coastal regions maintain natural processes that support biodiversity and the livelihood of billions of people. However, assessments of coastal regions have focused strictly on either the terrestrial or marine realm. Consequently, understanding of the overall state of Earth's coastal regions is poor. We integrated the terrestrial human footprint and marine cumulative human impact maps in a global assessment of the anthropogenic pressures affecting coastal regions. Of coastal regions globally, 15.5% had low anthropogenic pressure, mostly in Canada, Russia, and Greenland. Conversely, 47.9% of coastal regions were heavily affected by humanity, and in most countries (84.1%) >50% of their coastal regions were degraded. Nearly half (43.3%) of protected areas across coastal regions were exposed to high human pressures. To meet global sustainability objectives, all nations must undertake greater actions to preserve and restore the coastal regions within their borders.

costa, huella humana, impacto humano cumulativo, litoral, presión humana, restauración, tierras vírgenes Resumen El manejo de la interfaz entre la tierra y el mar es esencial para los objetivos mundiales de conservación y sustentabilidad ya que las regiones costeras mantienen los procesos naturales que sostienen a la biodiversidad y al sustento de miles de millones de personas. Sin embargo, los análisis de las regiones costeras se han enfocado estrictamente en el ámbito marino o en el terrestre, pero no en ambos. Por consiguiente, el conocimiento del estado general de las regiones costeras del planeta es muy pobre. Integramos la huella terrestre humana y mapas marinos del impacto humano cumulativo en un análisis global de las presiones antropogénicas que afectan las áreas costeras. De las áreas costeras de todo el mundo, el 15.5% tuvieron una presión antropogénica reducida, principalmente en Canadá, Rusia y Groenlandia. En cambio, el 47.9% de las regiones costeras estuvieron fuertemente afectas por la humanidad, y en la mayoría de los países (84.1%) >50% de sus regiones litorales se encuentran degradadas. Casi la mitad (43.3%) de las áreas protegidas en las regiones costeras tienen un grado de exposición a fuertes presiones humanas. Para cumplir los objetivos mundiales de sustentabilidad, todos los países deben emprender mejores acciones para preservar y restaurar las regiones litorales dentro de sus fronteras.

Multinational coordination required for conservation of over 90% of marine species.

Marine species are declining at an unprecedented rate, catalyzing many nations to adopt conservation and management targets within their jurisdictions. However, marine species and the biophysical processes that sustain them are naive to international borders. An understanding of the prevalence of cross-border species distributions is important for informing high-level conservation strategies, such as bilateral or regional agreements. Here, we examined 28,252 distribution maps to determine the number and locations of transboundary marine plants and animals. More than 90% of species have ranges spanning at least two jurisdictions, with 58% covering more than 10 jurisdictions. All jurisdictions have at least one transboundary species, with the highest concentrations of transboundary species in the USA, Australia, Indonesia, and the Areas Beyond National Jurisdiction. Distributions of mapped biodiversity indicate that overcoming the challenges of multinational governance is critical for a much wider suite of species than migratory megavertebrates and commercially exploited fish stocks-the groups that have received the vast majority of multinational management attention. To effectively protect marine biodiversity, international governance mechanisms (particularly those related to the Convention on Biological Diversity, the Convention on Migratory Species, and Regional Seas Organizations) must be expanded to promote multinational conservation planning, and complimented by a holistic governance framework for biodiversity beyond national jurisdiction.

Spatial cost-benefit analysis of blue restoration and factors driving net benefits globally.

Marine coastal ecosystems, commonly referred to as blue ecosystems, provide valuable services to society but are under increasing threat worldwide due to a variety of drivers, including eutrophication, development, land-use change, land reclamation, and climate change. Ecological restoration is sometimes necessary to facilitate recovery in coastal ecosystems. Blue restoration (i.e., in marine coastal systems) is a developing field, and projects to date have been small scale and expensive, leading to the perception that restoration may not be economically viable. We conducted a global cost-benefit analysis to determine the net benefits of restoring coral reef, mangrove, saltmarsh, and seagrass ecosystems, where the benefit is defined as the monetary value of ecosystem services. We estimated costs from published restoration case studies and used an adjusted-value-transfer method to assign benefit values to these case studies. Benefit values were estimated as the monetary value provided by ecosystem services of the restored habitats. Benefits outweighed costs (i.e., there were positive net benefits) for restoration of all blue ecosystems. Mean benefit:cost ratios for ecosystem restoration were eight to 10 times higher than prior studies of coral reef and seagrass restoration, most likely due to the more recent lower cost estimates we used. Among ecosystems, saltmarsh had the greatest net benefits followed by mangrove; coral reef and seagrass ecosystems had lower net benefits. In general, restoration in nations with middle incomes had higher (eight times higher in coral reefs and 40 times higher in mangroves) net benefits than those with high incomes. Within an ecosystem type, net benefit varied with restoration technique (coral reef and saltmarsh), ecosystem service produced (mangrove and saltmarsh), and project duration (seagrass). These results challenge the perceptions of the low economic viability of blue restoration and should encourage further targeted investment in this field.

Análisis de Rentabilidad Espacial de la Restauración Azul y de los Factores Determinantes del Beneficio Neto Mundial Resumen Los ecosistemas costeros marinos, llamados comúnmente ecosistemas azules, proporcionan servicios valiosos para la sociedad, pero se encuentran bajo una amenaza creciente a nivel mundial causada por una variedad de determinantes, incluyendo la eutrofización, el desarrollo, el cambio en el uso de suelo, la reclamación de tierra y el cambio climático. Algunas veces se necesita de la restauración ecológica para facilitar la recuperación en los ecosistemas costeros. La restauración azul (es decir, en los sistemas costeros marinos) es un campo en desarrollo, con proyectos que a la fecha han sido a pequeña escala y costosos, lo que resulta en la percepción de que la restauración puede no ser viable económicamente. Realizamos un análisis de rentabilidad mundial para determinar los beneficios netos de la restauración de ecosistemas de arrecife de coral, manglar, marisma y pastos marinos en donde el beneficio está definido como el valor monetario de los servicios ambientales. Estimamos los costos a partir de estudios de caso de restauración publicados y usamos un método de transferencia de valor ajustado para asignar los valores de beneficio a estos estudios de caso. Los valores de los beneficios fueron estimados como el valor monetario proporcionado por los servicios ambientales de los hábitats restaurados. Los beneficios superaron los costos (es decir, fueron beneficios netos positivos) de la restauración de todos los ecosistemas azules. El beneficio promedio consistió en que la proporción de costos para la restauración del ecosistema fue 8-10 veces mayor que en los estudios anteriores de la restauración de los arrecifes de coral y los pastos marinos, probablemente debido a que usamos estimaciones de costo más bajas. Entre los ecosistemas, las marismas tuvieron los mayores beneficios netos seguidos por los manglares; los arrecifes de coral y los pastos marinos tuvieron los beneficios netos más bajos. En general, la restauración en los países con niveles medios de ingreso tuvo más beneficios netos (ocho veces más en los arrecifes de coral y 40 veces más en los manglares) que aquellos países con niveles altos de ingreso. En cuanto al tipo de ecosistema, el beneficio neto varió de acuerdo con la técnica de restauración (arrecife de coral y marisma), servicio ambiental producido (manglar y marisma) y duración del proyecto (pastos marinos). Estos resultados desafían las percepciones de la baja viabilidad económica que tiene la restauración azul y deberían fomentar una mayor inversión focalizada en este campo.

Software for prioritizing conservation actions based on probabilistic information.

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

Marxan es la herramienta de apoyo a las decisiones que más comúnmente se usa para orientar el diseño de los sistemas de áreas protegidas. La versión original de Marxan no considera el riesgo y la incertidumbre asociados con los procesos amenazantes que afectan a las áreas protegidas, incluyendo la incertidumbre sobre la ubicación y la condición de las poblaciones de las especies y su hábitat ahora y en el futuro. Describimos y analizamos la funcionalidad de una versión modificada de Marxan: Marxan con Probabilidad. Este software considera explícitamente cuatro tipos de incertidumbre: probabilidad de que una característica exista en un lugar en particular (estimada con base en los modelos de distribución de especies o con modelos de población espacialmente explícitos); probabilidad de que las características de un sitio se pierdan en el futuro debido a un proceso amenazante, como el cambio climático, las catástrofes naturales y las intervenciones humanas descontroladas; probabilidad de que una característica existirá en el futuro debido a los procesos naturales de sucesión; como los incendios o las inundaciones; y probabilidad de que una característica exista pero haya sido degradada por los procesos amenazantes, como la sobrepesca y la contaminación, y por lo tanto no puede contribuir a los objetivos de conservación. Sintetizamos los resultados de cinco estudios que ilustraron cómo cada tipo de incertidumbre puede usarse para orientar el diseño del área protegida. Si hubiera incertidumbre en la distribución de la especie o de su hábitat, los usuarios podrían maximizar la posibilidad de que estas características estuvieran representadas mediante la inclusión de Marxan con Probabilidad. De manera similar, si los procesos amenazantes estuvieran considerados, los usuarios minimizarían la posibilidad de que se pierda la especie o degrade el hábitat usando Marxan con Probabilidad. Marxan con Probabilidad abre nuevas vías importantes para la investigación sobre la planeación sistemática de la conservación y su aplicación por parte de las agencias.

Simple rules can guide whether land- or ocean-based conservation will best benefit marine ecosystems.

Coastal marine ecosystems can be managed by actions undertaken both on the land and in the ocean. Quantifying and comparing the costs and benefits of actions in both realms is therefore necessary for efficient management. Here, we quantify the link between terrestrial sediment runoff and a downstream coastal marine ecosystem and contrast the cost-effectiveness of marine- and land-based conservation actions. We use a dynamic land- and sea-scape model to determine whether limited funds should be directed to 1 of 4 alternative conservation actions-protection on land, protection in the ocean, restoration on land, or restoration in the ocean-to maximise the extent of light-dependent marine benthic habitats across decadal timescales. We apply the model to a case study for a seagrass meadow in Australia. We find that marine restoration is the most cost-effective action over decadal timescales in this system, based on a conservative estimate of the rate at which seagrass can expand into a new habitat. The optimal decision will vary in different social-ecological contexts, but some basic information can guide optimal investments to counteract land- and ocean-based stressors: (1) marine restoration should be prioritised if the rates of marine ecosystem decline and expansion are similar and low; (2) marine protection should take precedence if the rate of marine ecosystem decline is high or if the adjacent catchment is relatively intact and has a low rate of vegetation decline; (3) land-based actions are optimal when the ratio of marine ecosystem expansion to decline is greater than 1:1.4, with terrestrial restoration typically the most cost-effective action; and (4) land protection should be prioritised if the catchment is relatively intact but the rate of vegetation decline is high. These rules of thumb illustrate how cost-effective conservation outcomes for connected land-ocean systems can proceed without complex modelling.

Optimal conservation outcomes require both restoration and protection.

Conservation outcomes are principally achieved through the protection of intact habitat or the restoration of degraded habitat. Restoration is generally considered a lower priority action than protection because protection is thought to provide superior outcomes, at lower costs, without the time delay required for restoration. Yet while it is broadly accepted that protected intact habitat safeguards more biodiversity and generates greater ecosystem services per unit area than restored habitat, conservation lacks a theory that can coherently compare the relative outcomes of the two actions. We use a dynamic landscape model to integrate these two actions into a unified conservation theory of protection and restoration. Using nonlinear benefit functions, we show that both actions are crucial components of a conservation strategy that seeks to optimise either biodiversity conservation or ecosystem services provision. In contrast to conservation orthodoxy, in some circumstances, restoration should be strongly preferred to protection. The relative priority of protection and restoration depends on their costs and also on the different time lags that are inherent to both protection and restoration. We derive a simple and easy-to-interpret heuristic that integrates these factors into a single equation that applies equally to biodiversity conservation and ecosystem service objectives. We use two examples to illustrate the theory: bird conservation in tropical rainforests and coastal defence provided by mangrove forests.

Trade-offs between data resolution, accuracy, and cost when choosing information to plan reserves for coral reef ecosystems.

Conservation planners must reconcile trade-offs associated with using biodiversity data of differing qualities to make decisions. Coarse habitat classifications are commonly used as surrogates to design marine reserve networks when fine-scale biodiversity data are incomplete or unavailable. Although finely-classified habitat maps provide more detail, they may have more misclassification errors, a common problem when remotely-sensed imagery is used. Despite these issues, planners rarely consider the effects of errors when choosing data for spatially explicit conservation prioritizations. Here we evaluate trade-offs between accuracy and resolution of hierarchical coral reef habitat data (geomorphology and benthic substrate) derived from remote sensing, in spatial planning for Kubulau District, Fiji. For both, we use accuracy information describing the probability that a mapped habitat classification is correct to design marine reserve networks that achieve habitat conservation targets, and demonstrate inadequacies of using habitat maps without accuracy data. We show that using more detailed habitat information ensures better representation of biogenic habitats (i.e. coral and seagrass), but leads to larger and more costly reserves, because these data have more misclassification errors, and are also more expensive to obtain. Reduced impacts on fishers are possible using coarsely-classified data, which are also more cost-effective for planning reserves if we account for data collection costs, but using these data may under-represent reef habitats that are important for fisheries and biodiversity, due to the maps low thematic resolution. Finally, we show that explicitly accounting for accuracy information in decisions maximizes the chance of successful conservation outcomes by reducing the risk of missing conservation representation targets, particularly when using finely classified data.

Replacing underperforming protected areas achieves better conservation outcomes.

Protected areas vary enormously in their contribution to conserving biodiversity, and the inefficiency of protected area systems is widely acknowledged. However, conservation plans focus overwhelmingly on adding new sites to current protected area estates. Here we show that the conservation performance of a protected area system can be radically improved, without extra expenditure, by replacing a small number of protected areas with new ones that achieve more for conservation. Replacing the least cost-effective 1% of Australia's 6,990 strictly protected areas could increase the number of vegetation types that have 15% or more of their original extent protected from 18 to 54, of a maximum possible of 58. Moreover, it increases markedly the area that can be protected, with no increase in overall spending. This new paradigm for protected area system expansion could yield huge improvements to global conservation at a time when competition for land is increasingly intense.

Achieving the triple bottom line in the face of inherent trade-offs among social equity, economic return, and conservation.

Triple-bottom-line outcomes from resource management and conservation, where conservation goals and equity in social outcomes are maximized while overall costs are minimized, remain a highly sought-after ideal. However, despite widespread recognition of the importance that equitable distribution of benefits or costs across society can play in conservation success, little formal theory exists for how to explicitly incorporate equity into conservation planning and prioritization. Here, we develop that theory and implement it for three very different case studies in California (United States), Raja Ampat (Indonesia), and the wider Coral Triangle region (Southeast Asia). We show that equity tends to trade off nonlinearly with the potential to achieve conservation objectives, such that similar conservation outcomes can be possible with greater equity, to a point. However, these case studies also produce a range of trade-off typologies between equity and conservation, depending on how one defines and measures social equity, including direct (linear) and no trade-off. Important gaps remain in our understanding, most notably how equity influences probability of conservation success, in turn affecting the actual ability to achieve conservation objectives. Results here provide an important foundation for moving the science and practice of conservation planning-and broader spatial planning in general-toward more consistently achieving efficient, equitable, and effective outcomes.