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Archaeological and paleoecological evidence shows that by 10,000 BCE, all human societies employed varying degrees of ecologically transformative land use practices, including burning, hunting, species propagation, domestication, cultivation, and others that have left long-term legacies across the terrestrial biosphere. Yet, a lingering paradigm among natural scientists, conservationists, and policymakers is that human transformation of terrestrial nature is mostly recent and inherently destructive. Here, we use the most up-to-date, spatially explicit global reconstruction of historical human populations and land use to show that this paradigm is likely wrong. Even 12,000 y ago, nearly three quarters of Earth’s landwas inhabited and therefore shaped by human societies, including more than 95% of temperate and 90% of tropical woodlands. Lands now characterized as “natural,” “intact,” and “wild” generally exhibit long histories of use, as do protected areas and Indigenous lands, and current global patterns of vertebrate species richness and key biodiversity areas are more strongly associated with past patterns of land use than with present ones in regional landscapes now characterized as natural. The current biodiversity crisis can seldom be explained by the loss of uninhabited wildlands, resulting instead from the appropriation, colonization, and intensifying use of the biodiverse cultural landscapes long shaped and sustained by prior societies. Recognizing this deep cultural connection with biodiversity will therefore be essential to resolve the crisis.

Saltmarshes are extremely valuable but often overlooked ecosystems, contributing to livelihoods locally and globally through the associated ecosystem services they provide, including fish production, carbon storage and coastal protection. Despite their importance, knowledge of the current spatial distribution (occurrence and extent) of saltmarshes is incomplete. In light of increasing anthropogenic and environmental pressures on coastal ecosystems, global data on the occurrence and extent of saltmarshes are needed to draw attention to these critical ecosystems and to the benefits they generate for people. Such data can support resource management, strengthen decision-making and facilitate tracking of progress towards global conservation targets set by multilateral environmental agreements, such as the Aichi Biodiversity Targets of the United Nations' (UN's) Strategic Plan for Biodiversity 2011-2020, the Sustainable Development Goals of the UN's 2030 Agenda for Sustainable Development and the Ramsar Convention. Here, we present the most complete dataset on saltmarsh occurrence and extent at the global scale. This dataset collates 350,985 individual occurrences of saltmarshes and presents the first global estimate of their known extent. The dataset captures locational and contextual data for saltmarsh in 99 countries worldwide. A total of 5,495,089 hectares of mapped saltmarsh across 43 countries and territories are represented in a Geographic Information Systems polygon shapefile. This estimate is at the relatively low end of previous estimates (2.2-40 Mha), however, we took the conservative approach in the mapping exercise and there are notable areas in Canada, Northern Russia, South America and Africa where saltmarshes are known to occur that require additional spatial data. Nevertheless, the most extensive saltmarsh worldwide are found outside the tropics, notably including the low-lying, ice-free coasts, bays and estuaries of the North Atlantic which are well represented in our global polygon dataset. Therefore, despite the gaps, we believe that, while incomplete, our global polygon data cover many of the important areas in Europe, the USA and Australia.

Over the past decades, a number of national policies and international conventions have been implemented to promote the expansion of the world's protected area network, leading to a diversification of protected area strategies, types and designations. As a result, many areas are protected by more than one convention, legal instrument, or other effective means which may result in a lack of clarity around the governance and management regimes of particular locations. We assess the degree to which different designations overlap at global, regional and national levels to understand the extent of this phenomenon at different scales. We then compare the distribution and coverage of these multi-designated areas in the terrestrial and marine realms at the global level and among different regions, and we present the percentage of each county's protected area extent that is under more than one designation. Our findings show that almost a quarter of the world's protected area network is protected through more than one designation. In fact, we have documented up to eight overlapping designations. These overlaps in protected area designations occur in every region of the world, both in the terrestrial and marine realms, but are more common in the terrestrial realm and in some regions, notably Europe. In the terrestrial realm, the most common overlap is between one national and one international designation. In the marine realm, the most common overlap is between any two national designations. Multi-designations are therefore a widespread phenomenon but its implications are not well understood. This analysis identifies, for the first time, multi-designated areas across all designation types. This is a key step to understand how these areas are managed and governed to then move towards integrated and collaborative approaches that consider the different management and conservation objectives of each designation.

Work on the post‐2020 global biodiversity framework is now well advanced and will outline a vision, goals, and targets for the next decade of biodiversity conservation and beyond. For the effectiveness of Protected areas and Other Effective area‐based Conservation Measures, an indicator has been proposed for “areas meeting their documented ecological objectives.” However, the Convention on Biological Diversity (CBD) has not identified or agreed on what data should inform this indicator. Here we draw on experiences from the assessment of protected area effectiveness in the CBD's previous strategic plan to provide recommendations on the essential elements related to biodiversity outcomes and management that need to be captured in this updated indicator as well as how this could be done. Our proposed protected area effectiveness indicators include a combination of remotely derived products for all protected areas, combined with data from monitoring of both protected area management and trends in species and ecosystems based on field observations. Additionally, we highlight the need for creating a digital infrastructure to operationalize national‐level data‐capture. We believe these steps are critical and urge the adoption of suitable protected area effectiveness indicators before the post‐2020 framework is agreed in 2021.

Aichi Target 11 of the CBD Strategic Plan for Biodiversity commits countries to the effective conservation of areas of importance for biodiversity, through protected areas and “other effective area‐based conservation measures” (OECMs). However, the prevalence and characteristics of OECMs are poorly known, particularly in sites of importance for biodiversity. We assess the prevalence of potential OECMs in 740 terrestrial Key Biodiversity Areas (KBAs) outside known or mapped protected areas across ten countries. A majority of unprotected KBAs (76.5%) were at least partly covered by one or more potential OECMs. The conservation of ecosystem services or biodiversity was a stated management aim in 73% of these OECMs. Local or central government bodies managed the highest number of potential OECMs, followed by local and indigenous communities and private landowners. There was no difference between unprotected KBAs with or without OECMs in forest loss or in a number of state‐pressure‐response metrics.

Area-based conservation is a widely used approach for maintaining biodiversity, and there are ongoing discussions over what is an appropriate global conservation area coverage target. To inform such debates, it is necessary to know the extent and ecological representativeness of the current conservation area network, but this is hampered by gaps in existing global datasets. In particular, although data on privately and community-governed protected areas and other effective area-based conservation measures are often available at the national level, it can take many years to incorporate these into official datasets. This suggests a complementary approach is needed based on selecting a sample of countries and using their national-scale datasets to produce more accurate metrics. However, every country added to the sample increases the costs of data collection, collation and analysis. To address this, here we present a data collection framework underpinned by a spatial prioritization algorithm, which identifies a minimum set of countries that are also representative of 10 factors that influence conservation area establishment and biodiversity patterns. We then illustrate this approach by identifying a representative set of sampling units that cover 10% of the terrestrial realm, which included areas in only 25 countries. In contrast, selecting 10% of the terrestrial realm at random included areas across a mean of 162 countries. These sampling units could be the focus of future data collation on different types of conservation area. Analysing these data could produce more rapid and accurate estimates of global conservation area coverage and ecological representativeness, complementing existing international reporting systems.

Humanity will soon define a new era for nature—one that seeks to transform decades of underwhelming responses to the global biodiversity crisis. Area-based conservation efforts, which include both protected areas and other effective area-based conservation measures, are likely to extend and diversify. However, persistent shortfalls in ecological representation and management effectiveness diminish the potential role of area-based conservation in stemming biodiversity loss. Here we show how the expansion of protected areas by national governments since 2010 has had limited success in increasing the coverage across different elements of biodiversity (ecoregions, 12,056 threatened species, ‘Key Biodiversity Areas’ and wilderness areas) and ecosystem services (productive fisheries, and carbon services on land and sea). To be more successful after 2020, area-based conservation must contribute more effectively to meeting global biodiversity goals—ranging from preventing extinctions to retaining the most-intact ecosystems—and must better collaborate with the many Indigenous peoples, community groups and private initiatives that are central to the successful conservation of biodiversity. The long-term success of area-based conservation requires parties to the Convention on Biological Diversity to secure adequate financing, plan for climate change and make biodiversity conservation a far stronger part of land, water and sea management policies. The long-term success of area-based conservation—including both protected areas and other effective area-based conservation measures—after 2020 will depend on governments securing adequate funding and prioritizing biodiversity in land, water and sea management.

Nations of the world have committed to a number of goals and targets to address global environmental challenges. Protected areas have for centuries been a key strategy in conservation and play a major role in addressing current challenges. The most important tool used to track progress on protected-area commitments is the World Database on Protected Areas (WDPA). Periodic assessments of the world’s protected-area estate show steady growth over the last 2 decades. However, the current method, which uses the latest version of the WDPA, does not show the true dynamic nature of protected areas over time and does not provide information on sites removed from the WDPA. In reality, this method can only show growth or remain stable. We used GIS tools in an approach to assess protected-area change over time based on 12 temporally distinct versions of the WDPA that quantify area added and removed from the WDPA annually from 2004 to 2016. Both the narrative of continual growth of protected area and the counter-narrative of protected area removal were overly simplistic. The former because growth was almost entirely in the marine realm and the latter because some areas removed were reprotected in later years. On average 2.5 million km² was added to the WDPA annually and 1.1 million km² was removed. Reasons for the inclusion and removal of protected areas in the WDPA database were in part due to data-quality issues but also to on-the-ground changes. To meet the 17% protected-area component of Aichi Biodiversity Target 11 by 2020, which stood at 14.7% in 2016, either the rate of protected-area removal must decrease or the rate of protected-area designation and addition to the WDPA must increase. Países alrededor del mundo se han comprometido con un número de metas y objetivos para tratar los retos ambientales mundiales. Las áreas protegidas han funcionado durante siglos como una estrategia clave en la conservación y juegan un papel importante en cómo se manejan los retos actuales. La herramienta más importante que se usa para rastrear el progreso de los compromisos con las áreas protegidas es la Base de Datos Mundial de las Áreas Protegidas (WDPA, en inglés). Las evaluaciones periódicas de los bienes de las áreas protegidas muestranun crecimiento constante durante las últimas dos décadas. Sin embargo, el método actual, que usa la versión más reciente de la WDPA, no muestra la verdadera naturaleza dinámica de las áreas protegidas a lo largo del tiempo y no proporciona informaciónsobre sitiosquehan sidoremovidos dela WDPA. En realidad este método sólo puede mostrar crecimiento o permanecer estable. Usamos herramientas de SIG en una estrategia para evaluar el cambio de las áreas protegidas a lo largo del tiempo con base en doce versiones temporalmente distintas de la WDPA que cuantifican las áreas añadidas o removidas de la WDPA anualmente desde 2004 hasta 2016. Tanto la narrativa del crecimiento continuo de un área protegida como la contra-narrativa de la eliminación de un área protegida fueron exageradamente simplistas. La primera se debe a que el crecimiento ocurrió casi en su mayoría en el dominio marino y la segunda a que algunas áreas eliminadas fueron reprotegidas años después. En promedio se añadieron 2.5 millones de km² a la WDPA anualmente y 1.1 millones de km² fueron removidos. Las razones para la inclusión y la eliminación de las áreas protegidas de la base de datos de la WDPA se debieron en parte a temas de calidad de datos pero también a cambios hechos sobre la marcha. Para lograr el 17% del componente de áreas protegidas del Objetivo 11 de Biodiversidad de Aichi para el 2020, el cual se encontraba al 14.7% en 2016, se debe disminuir la tasa de eliminación de áreas protegidas o se debe incrementar la tasa de designación y suma de áreas protegidas a la WDPA. 世界各国都在致力于实现一系列目标以应对全球环境变化的挑故。几个世纪以来保护区一直是实施保 护的重要策略，在应对目前的挑战中也起到重要作用。要追踪对保护区建设实施的进展，最重要的工具就是世界 保护区数据库(World Database on Protected Areas, WDPA)。对全球保护区的周期性评估显示，过去二十年来 受保护的区域在稳定增加。然而，目前使用最新版本 WDPA 数据库的方法并不能体现保护区随时间变化的真实 动态，也不能提供那些从 WDPA 中去除的位点的信息。事实上这个方法只能显示增长或保持稳定的动态。我 们用GIS工具根据12十不同时期的 WDPA 版本评估了保护区随时间的变化这ー方法定量7 2004 年到 2016 年 WDPA 毎年新增和去除的地区。保护区的持续增加和保护区的去除的描述都过于简单化。前者是因为増加 的地区几乎都是海洋，后者则是因为ー些被去除的地区随后几年又重新得到了保护。WDPA 中保护区平均毎年 増加 250 万平方公里，去除110万平方公里。WDPA 数据库中保护区新增和去除的原因有的是数据质量问题， 有的则是发生了真实的变化。为7在 2020 年达到爱知生物多样性目标U 中保护区覆盖17%的S 标 (2016 年 为14.7%) ス必须降低保护区被去除的速率，或增加划定保护区并加入 WDPA 数据库的速率。

Fragmentation of natural habitats can increase numbers of rare species. Conservation of rare species requires experts and resources, which may be lacking for many species. In the absence of regular surveys and expert knowledge, historical sighting records can provide data on the distribution of a species. Numerous models have been developed recently to make inferences regarding the threat status of a taxon on the basis of variation in trends of sightings over time. We applied 5 such models to national and regional (county) data on 3 red-listed orchid species (Cephalanthera longifolia, Hammarbya paludosa, and Pseudorchis albida) and 1 species that has recently come to the attention of conservation authorities (Neotinea maculata) in the Republic of Ireland. In addition, we used an optimal linear estimate to calculate the time of extinction for each species overall and within each county. To account for bias in recording effort over time, we used rarefaction analysis. On the basis of sighting records, we inferred that these species are not threatened with extinction and, although there have been declines, there is no clear geographical pattern of decline in any species. Most counties where these orchid species occurred had a low number of sightings; hence, we were cautious in our interpretation of output from statistical models. We suggest the main drivers of decline in these species in Ireland are modification of habitats for increased agricultural production and lack of appropriate management. Our results show that the application of probabilistic models can be used even when sighting data are scarce, provided multiple models are used simultaneously and rarefaction is used to account for bias in recording effort among species over time. These models could be used frequently when making an initial conservation assessment of species in a region, particularly if there is a relatively constant recording rate and some knowledge of the underlying recording process. Regional-scale analyses, such as ours, complement World Conservation Union criteria for assessment of the extinct category and are useful for highlighting areas of under recording and focusing conservation efforts of rare and endangered species.

Protected areas (PAs) are at the forefront of conservation efforts, and yet despite considerable progress towards the global target of having 17% of the world's land area within protected areas by 2020, biodiversity continues to decline. The discrepancy between increasing PA coverage and negative biodiversity trends has resulted in renewed efforts to enhance PA effectiveness. The global conservation community has conducted thousands of assessments of protected area management effectiveness (PAME), and interest in the use of these data to help measure the conservation impact of PA management interventions is high. Here, we summarize the status of PAME assessment, review the published evidence for a link between PAME assessment results and the conservation impacts of PAs, and discuss the limitations and future use of PAME data in measuring the impact of PA management interventions on conservation outcomes. We conclude that PAME data, while designed as a tool for local adaptive management, may also help to provide insights into the impact of PA management interventions from the local-to-global scale. However, the subjective and ordinal characteristics of the data present significant limitations for their application in rigorous scientific impact evaluations, a problem that should be recognized and mitigated where possible.