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Mangrove area loss is increasing globally, and drivers of loss differ depending not only on natural conditions but also on national and regional policies. Some countries with the most mangrove area, for instance, Brazil, lack broad systematic quantification of specific drivers of mangrove land‐use and land‐cover (LULC) change dynamics. We investigated the direct conversion (i.e., replacement) of mangrove forests due to changes in 21 types of LULC across Brazil from 2000 to 2020 based on annual LULC maps developed by the MapBiomas project. We quantified the area changes at national, regional, and state scales. We also determined and quantified mangrove forest conversion for each of the 21 LULC types with a pixel comparison analysis and identified temporal trends with a time‐series analysis. The total conversion of mangrove area (3429 km2) was offset by a gain that was twice as large (6776 km2). Forest formations and water bodies, which may be interpreted as natural or indirect anthropogenic changes, were associated with most of the areas where mangrove cover was lost. Land‐use modifications, mainly creation of pastures, accounted for 4% of direct mangrove conversions. We found that changes in LULC categories and patterns of gain and loss of mangrove areas differed among Brazilian states and regions. Based on other research, they also differ between Brazil and other countries. Thus, integrated mangrove forest conservation and management efforts that transcend political boundaries are essential to effectively address negative impacts on mangrove forests. We provide an interactive map to allow qualitative assessments of mangrove conversion drivers by different stakeholders, such as managers, policymakers, and nongovernmental organizations. [ABSTRACT FROM AUTHOR]

Emerging technology has immense potential to increase the scale and efficiency of marine conservation. One such technology is large‐area imaging (LAI), which relies on structure‐from‐motion photogrammetry to create composite products, including 3‐dimensional (3‐D) environmental models, that are larger in spatial extent than the individual images used to create them. Use of LAI has become widespread in certain fields of marine science, primarily to measure the 3D structure of benthic ecosystems and track change over time. However, the use of LAI in the field of marine conservation appears limited. We conducted a review of the coral reef literature on the use of LAI to identify research themes and regional trends in applications of this technology. We also surveyed 135 coral reef scientists and conservation practitioners to determine community familiarity with LAI, evaluate barriers practitioners face in using LAI, and identify applications of LAI believed to be most exciting or relevant to coral conservation. Adoption of LAI was limited primarily to researchers at institutions based in advanced economies and was applied infrequently to conservation, although conservation practitioners and survey respondents from emerging economies indicated they expect to use LAI in the future. Our results revealed disconnect between current LAI research topics and conservation priorities identified by practitioners, highlighting the need for more diverse, conservation‐relevant research using LAI. We provide recommendations for how early adopters of LAI (typically Global North scientists from well‐resourced institutions) can facilitate access to this conservation technology. These recommendations include developing training resources, creating partnerships for data storage and analysis, publishing standard operating procedures for LAI workflows, standardizing methods, developing tools for efficient data extraction from LAI products, and conducting conservation‐relevant research using LAI. [ABSTRACT FROM AUTHOR]

Development and implementation of effective protected area management to reduce deforestation depend in part on identifying factors contributing to forest loss and areas at risk of conversion, but standard land‐use‐change modeling may not fully capture contextual factors that are not easily quantified. To better understand deforestation and agricultural expansion in Amazonian protected areas, we combined quantitative land‐use‐change modeling with qualitative discourse analysis in a case study of Brazil's Jamanxim National Forest. We modeled land‐use change from 2008 to 2018 and projected deforestation through 2028. We used variables identified in a review of studies that modeled land‐use change in the Amazon (e.g., variables related to agricultural suitability and economic accessibility) and from a critical discourse analysis that examined documents produced by different actors (e.g., government agencies and conservation nonprofit organizations) at various spatial scales. As measured by analysis of variance, McFadden's adjusted pseudo R2, and quantity and allocation disagreement, we found that including variables in the model identified as important to deforestation dynamics through the qualitative discourse analysis (e.g., the proportion of unallocated public land, distance to proposed infrastructure developments, and density of recent fires) alongside more traditional variables (e.g., elevation, distance to roads, and protection status) improved the predictive ability of these models. Models that included discourse analysis variables and traditional variables explained up to 19.3% more of the observed variation in deforestation probability than a model that included only traditional variables and 4.1% more variation than a model with only discourse analysis variables. Our approach of integrating qualitative and quantitative methods in land‐use‐change modeling provides a framework for future interdisciplinary work in land‐use change. [ABSTRACT FROM AUTHOR]

Keywords: big data; critical data studies; data justice; datification; equity; global analyses; political ecology; remote sensing; análisis globales; datificación; ecología política; estudios críticos de datos; justicia informativa; teledetección; ; ; ; ; ; ; ; EN big data critical data studies data justice datification equity global analyses political ecology remote sensing análisis globales datificación ecología política estudios críticos de datos justicia informativa teledetección 1 10 10 10/04/22 20221001 NES 221001 INTRODUCTION The nature and use of data in conservation have changed profoundly in recent years (Bakker & Ritts, 2018). THE NEED FOR CRITICAL PERSPECTIVES ON CONSERVATION DATA Data, conservation data included, are never neutral because they are derived and used by people (Dencik et al., 2019). In this essay, we reflect on the urgent need for more critical perspectives on conservation data, review theories of data justice developed for other contexts, and consider how these theories could be applied to the context of conservation. By proposing a framework to think through the justice dimensions of conservation data, we hope to motivate further work toward developing new understandings of the nature and impacts of conservation data. [Extracted from the article]

First, with our use of IUCN range maps to estimate the number of species per watershed, as in other broad-scale biodiversity assessments, we assumed that a given species is present across its entire range. Prioritizing conservation in sub-Saharan African lakes based on freshwater biodiversity and algal bloom metrics Keywords: algal blooms; freshwater biodiversity; Google Earth Engine; lakes; remote sensing; species richness; sub-Saharan Africa; África sub-sahariana; biodiversidad de aguas dulces; floración de algas; Google Earth; lagos; riqueza de especies; teledetección; ; ; ; ; ; ; EN algal blooms freshwater biodiversity Google Earth Engine lakes remote sensing species richness sub-Saharan Africa África sub-sahariana biodiversidad de aguas dulces floración de algas Google Earth lagos riqueza de especies teledetección 1 13 13 10/04/22 20221001 NES 221001 INTRODUCTION As the global human population and associated food demand continue to increase, so does the need to use land for agriculture (Tscharntke et al., 2012). Watershed colors are based on level 3 and level 4 HydroBASINS (see Lehner & Grill, 2013) gl Measuring freshwater biodiversity For both obligate freshwater species and freshwater-dependent vertebrate species in each country, we used the HydroBASINS data set (format 2 [i.e., inserted lakes]) and International Union for the Conservation of Nature (IUCN) datasets. [Extracted from the article]

Very high‐resolution (VHR) satellite sensors can be used to estimate the size of animal populations, a critical factor in wildlife management, and acquire animal spatial distributions in an economical, easy, and precise way. We developed a method for satellite population size estimation that includes a noninvasive photogrammetry, from which the animal's average orthographic area is calculated, and an imagery interpretation method that estimates population size based on the ratio of an observed animal population area to the average individual area. As a proof of concept, we used this method to estimate the population size of Whooper Swans (Cygnus cygnus) in a national nature reserve in China. To reduce errors, the reserve was subdivided into regions of interest based on locations of Whooper Swan and background brightness. Estimates from the satellite pixels were compared with manual counts made over 2 years, at 3 locations, and in 3 land‐cover types. Our results showed 1124 Whooper Swans occupied a national nature reserve on 15 February 2013, and the average percent error was 3.16% (SE = 1.37). These results demonstrate that our method produced robust data for population size estimation that were indistinguishable from manual count data. Our method may be used generally to estimate population sizes of visible and gregarious animals that exhibit high contrast relative to their environments and may inform estimations of populations in complex backgrounds. Article impact statement: Robust estimates of animal population size can be made with VHR satellite imagery. [ABSTRACT FROM AUTHOR]

GLO:FQU/01apr20:cobi13409-fig-0001.jpg PHOTO (COLOR): Map of Falcataria moluccana (FM) change from 2009 to 2016 in the Puna District of Hawaii (red, increase in FM distributions; blue, decrease in FM distributions; yellow, areas where FM remains the same). We assumed an area with FM in 2009 that did not have FM in 2016 was an area where FM died due to natural causes (e.g., blow over and old age) or landowners engaged in effective transformative management (i.e., landowners controlled preexisting invader populations). If the first explanation is correct, then while certain types of landowners are engaging in transformative management actions to remove FM, these same landowners may not be engaging in effective preventative actions to stop increases of FM. This landowner focus on transformative management to control existing FM may have occurred in response to the damage caused by FM when Tropical Storm Iselle affected the Puna District in 2014. [Extracted from the article]

The IUCN (International Union for Conservation of Nature) Red List categories and criteria are the most widely used framework for assessing the relative extinction risk of species. The criteria are based on quantitative thresholds relating to the size, trends, and structure of species' distributions and populations. However, data on these parameters are sparse and uncertain for many species and unavailable for others, potentially leading to their misclassification or classification as data deficient. We devised an approach that combines data on land‐cover change, species‐specific habitat preferences, population abundance, and dispersal distance to estimate key parameters (extent of occurrence, maximum area of occupancy, population size and trend, and degree of fragmentation) and hence predict IUCN Red List categories for species. We applied our approach to nonpelagic birds and terrestrial mammals globally (∼15,000 species). The predicted categories were fairly consistent with published IUCN Red List assessments, but more optimistic overall. We predicted 4.2% of species (467 birds and 143 mammals) to be more threatened than currently assessed and 20.2% of data deficient species (10 birds and 114 mammals) to be at risk of extinction. Incorporating the habitat fragmentation subcriterion reduced these predictions 1.5–2.3% and 6.4–14.9% (depending on the quantitative definition of fragmentation) for threatened and data deficient species, respectively, highlighting the need for improved guidance for IUCN Red List assessors on the application of this aspect of the IUCN Red List criteria. Our approach complements traditional methods of estimating parameters for IUCN Red List assessments. Furthermore, it readily provides an early‐warning system to identify species potentially warranting changes in their extinction‐risk category based on periodic updates of land‐cover information. Given our method relies on optimistic assumptions about species distribution and abundance, all species predicted to be more at risk than currently evaluated should be prioritized for reassessment. Article impact statement: Automatic screening to prioritize species reassessments optimizes the use of resources and keeps the IUCN Red List up to date. [ABSTRACT FROM AUTHOR]

Conservation actions need to be prioritized, often taking into account species' extinction risk. The International Union for Conservation of Nature (IUCN) Red List provides an accepted, objective framework for the assessment of extinction risk. Assessments based on data collected in the field are the best option, but the field data to base these on are often limited. Information collected through remote sensing can be used in place of field data to inform assessments. Forests are perhaps the best-studied land-cover type for use of remote-sensing data. Using an open-access 30-m resolution map of tree cover and its change between 2000 and 2012, we assessed the extent of forest cover and loss within the distributions of 11,186 forest-dependent amphibians, birds, and mammals worldwide. For 16 species, forest loss resulted in an elevated extinction risk under red-list criterion A, owing to inferred rapid population declines. This number increased to 23 when data-deficient species (i.e., those with insufficient information for evaluation) were included. Under red-list criterion B2, 484 species (855 when data-deficient species were included) were considered at elevated extinction risk, owing to restricted areas of occupancy resulting from little forest cover remaining within their ranges. The proportion of species of conservation concern would increase by 32.8% for amphibians, 15.1% for birds, and 24.7% for mammals if our suggested uplistings are accepted. Central America, the Northern Andes, Madagascar, the Eastern Arc forests in Africa, and the islands of Southeast Asia are hotspots for these species. Our results illustrate the utility of satellite imagery for global extinction-risk assessment and measurement of progress toward international environmental agreement targets. [ABSTRACT FROM AUTHOR]

Vegetation is sparsely distributed over Antarctica's ice-free ground, and distinct plant communities are present in each of the continent's 15 recently identified Antarctic Conservation Biogeographic Regions (ACBRs). With rapidly increasing human activity in Antarctica, terrestrial plant communities are at risk of damage or destruction by trampling, overland transport, and infrastructure construction and from the impacts of anthropogenically introduced species, as well as uncontrollable pressures such as fur seal (Arctocephalus gazella) activity and climate change. Under the Protocol on Environmental Protection to the Antarctic Treaty, the conservation of plant communities can be enacted and facilitated through the designation of Antarctic Specially Protected Areas (ASPAs). We examined the distribution within the 15 ACBRs of the 33 ASPAs whose explicit purpose includes protecting macroscopic terrestrial flora. We completed the first survey using normalized difference vegetation index (NDVI) satellite remote sensing to provide baseline data on the extent of vegetation cover in all ASPAs designated for plant protection in Antarctica. Large omissions in the protection of Antarctic botanical diversity were found. There was no protection of plant communities in 6 ACBRs, and in another 6, <0.4% of the ACBR area was included in an ASPA that protected vegetation. Protected vegetation cover within the 33 ASPAs totaled 16.1 km2 for the entire Antarctic continent; over half was within a single protected area. Over 96% of the protected vegetation was contained in 2 ACBRs, which together contributed only 7.8% of the continent's ice-free ground. We conclude that Antarctic botanical diversity is clearly inadequately protected and call for systematic designation of ASPAs protecting plant communities by the Antarctic Treaty Consultative Parties, the members of the governing body of the continent. [ABSTRACT FROM AUTHOR]

The Tibetan sacred mountains (TSMs) cover a large area and may represent a landscape-scale conservation opportunity. We compared the conservation value of forests in these mountains with the conservation value of government-established nature reserves and unmanaged open-access areas in Danba County, southwestern China. We used Landsat satellite images to map forest cover and to estimate forest loss in 1974-1989, 1989-1999, and 1999-2013. The TSMs (n = 41) and nature reserves (n = 4) accounted for 21.6% and 29.7% of the county's land area, respectively. Remaining land was open-access areas (i.e., areas without any restrictions on resource use) (56.2%) and farmlands (2.2%). Within the elevation range suitable for forests, forest cover did not differ significantly between nature reserves (58.8%) and open-access areas (58.4%), but was significantly higher in TSMs (65.5%) after controlling for environmental factors such as aspect, slope, and elevation. The TSMs of great cultural importance had higher forest cover, but patrols by monastery staff were not necessarily associated with increased forest cover. The annual deforestation rate in nonsacred areas almost tripled in 1989-1999 (111.4 ha/year) relative to 1974-1989 (40.4 ha/year), whereas the rate in TSMs decreased in the later period (19.7 ha/year vs. 17.2 ha/year). The reduced forest loss in TSMs in 1989-1999 was possibly due to the renaissance of TSM worship and strengthened management by the local Buddhist community since late 1980s. The annual deforestation rate in Danba decreased dramatically to 4.4 ha/year in 1999-2013, which coincided with the implementation of a national ban on logging in 1998. As the only form of protected area across the Tibetan region during much of its history, TSMs have positively contributed to conserving forest at a landscape scale. Conservation of TSM forests largely relied on the strength of local religious institutions. Integrating community-based conservation of TSMs within the government conservation network would benefit the conservation of the Tibetan region. [ABSTRACT FROM AUTHOR]

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners' use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions? [ABSTRACT FROM AUTHOR]