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AIM: To provide high‐resolution local, regional, national and global estimates of annual mangrove forest area from 2000 through to 2012 with the goal of driving mangrove research questions pertaining to biodiversity, carbon stocks, climate change, functionality, food security, livelihoods, fisheries support and conservation that have been impeded until now by a lack of suitable data. LOCATION: Global, covering 99% of all mangrove forests. METHODS: We synthesized the Global Forest Change database, the Terrestrial Ecosystems of the World database and the Mangrove Forests of the World database to extract mangrove forest cover at high spatial and temporal resolutions. We then used the new database to monitor mangrove cover at the global, national and protected area scales. RESULTS: Countries showing relatively high amounts of mangrove loss include Myanmar, Malaysia, Cambodia, Indonesia and Guatemala. Indonesia remains by far the largest mangrove‐holding nation, containing between 26% and 29% of the global mangrove inventory with a deforestation rate of between 0.26% and 0.66% per year. We have made our new database, CGMFC‐21, freely available. MAIN CONCLUSIONS: Global mangrove deforestation continues but at a much reduced rate of between 0.16% and 0.39% per year. Southeast Asia is a region of concern with mangrove deforestation rates between 3.58% and 8.08%, this in a region containing half of the entire global mangrove forest inventory. The global mangrove deforestation pattern from 2000 to 2012 is one of decreasing rates of deforestation, with many nations essentially stable, with the exception of the largest mangrove‐holding region of Southeast Asia. We provide a standardized spatial dataset that monitors mangrove deforestation globally at high spatio‐temporal resolutions. These data can be used to drive the mangrove research agenda, particularly as it pertains to monitoring of mangrove carbon stocks and the establishment of baseline local mangrove forest inventories required for payment for ecosystem service initiatives.

Mangrove forests store high densities of organic carbon, which, when coupled with high rates of deforestation, means that mangroves have the potential to contribute substantially to carbon emissions. Consequently, mangroves are strong candidates for inclusion in nationally determined contributions (NDCs) to the United Nations Framework Convention on Climate Change (UNFCCC), and payments for ecosystem services (PES) programmes that financially incentivize the conservation of forested carbon stocks. This study quantifies annual mangrove carbon stocks from 2000 to 2012 at the global, national and sub-national levels, and global carbon emissions resulting from deforestation over the same time period. Globally, mangroves stored 4.19 Pg of carbon in 2012, with Indonesia, Brazil, Malaysia and Papua New Guinea accounting for more than 50% of the global stock. 2.96 Pg of the global carbon stock is contained within the soil and 1.23 Pg in the living biomass. Two percent of global mangrove carbon was lost between 2000 and 2012, equivalent to a maximum potential of 316,996,250 t of CO2 emissions.

In this paper we estimate the living carbon lost from Ecuador's mangrove forests since the advent of export-focused shrimp aquaculture. We use remote sensing techniques to delineate the extent of mangroves and aquaculture at approximately decadal periods since the arrival of aquaculture in each Ecuadorian estuary. We then spatiotemporally calculate the carbon values of the mangrove forests and estimate the amount of carbon lost due to direct displacement by aquaculture. Additionally, we calculate the new carbon stocks generated due to mangrove reforestation or afforestation. This research introduces time and LUCC (land use / land cover change) into the tropical forest carbon literature and examines forest carbon loss at a higher spatiotemporal resolution than in many earlier analyses. We find that 80 percent, or 7,014,517 t of the living carbon lost in Ecuadorian mangrove forests can be attributed to direct displacement of mangrove forests by shrimp aquaculture. We also find that IPCC (Intergovernmental Panel on Climate Change) compliant carbon grids within Ecuador's estuaries overestimate living carbon levels in estuaries where substantial LUCC has occurred. By approaching the mangrove forest carbon loss question from a LUCC perspective, these findings allow for tropical nations and other intervention agents to prioritize and target a limited set of land transitions that likely drive the majority of carbon losses. This singular cause of transition has implications for programs that attempt to offset or limit future forest carbon losses and place value on forest carbon or other forest good and services.

Evidence suggests that mangroves protect economic activity in coastal areas. We estimate this protection from mangroves and coastal elevation globally, examining both “direct” and “indirect” exposure events (< 100 km vs. ≥ 100 km distance from a cyclone’s “eye”, respectively). We find that higher elevation (≥ 50 m) or wide mangroves (≥ 10 m seaward width) alone shelter economic activity from indirect cyclone exposure, whereas protection from direct cyclone exposure occurs only in high elevation communities with wide mangroves. Our results reveal that the majority of these “safe havens” are in upper middle-income countries but provide significant benefits to populations in lower middle-income countries.

Background Waterborne diseases are one of the leading causes of mortality in developing countries, and diarrhea alone is responsible for over 1.5 million deaths annually. Such waterborne illnesses most often affect those in impoverished rural communities who rely on rivers for their supply of drinking water. Deaths are most common among infants and the elderly. Without knowledge of which communities are upstream of a community, upstream sanitary and bathing behaviors can never be directly linked to downstream health outcomes including disease outbreaks. Although current GIS technologies can answer the upstream question for a limited number of downstream communities, no systematic way existed of labeling each downstream village with all its upstream contributing villages along river networks or within basins at the large national scale, such as in Indonesia. This limitation prohibits macro analyses of waterborne illness across developing world communities globally. Results This novel method approach combines parallel computing, big data, community data, and open source GIS to create a database of upstream communities for 50,000–70,0000 villages in Indonesia across four differing periods. The resultant village database provides information that can be tied to the Indonesian PODES health and behavior surveys in each village to connect upstream sanitary behaviors to downstream health outcomes. We find that the approximately 250,000 communities analyzed across the four periods in Indonesia have a combined total of 13.7 million upstream villages. The average number of upstream villages per village was almost 55, the maximum number of upstream villages for any single village was over 5300. Conclusions Advances in big-data availability, particularly high-resolution elevation data, the lowering of the cost of parallel computing options, mass survey data, and open source GIS algorithms that can utilize parallel processing and big-data, open new opportunities for the study of human health at micro granularities but across entire nations. The database generated has already been used by health researchers to compute the influence of upstream behaviors on downstream diarrhea outbreaks and to monitor avoidance behaviors to upstream water behaviors across all downstream 250,000 Indonesian villages over 4 years, and further waterborne health analyses are underway.

The unique ecological conditions of the mangrove forests in the Rio Preguiças Estuary, Maranhão, Brazil, support a culturally isolated population of bearded capuchin monkeys (Sapajus libidinosus) and contribute to the livelihoods and economy of the local community. In this location, the capuchins survive solely within the mangrove forests, primarily feeding on the mangrove crab (Ucides cordatus), often using wooden tools to crack them open. These mangrove forests serve as fish nurseries and support economically valuable crustaceans, sustaining local food resources and a thriving fishery. Given the multifaceted role of these mangrove forests as a habitat for this unique capuchin population and as a resource for the local community, our study assesses these forests' past, present and projected future status. We conducted a multiscale land‐use change analysis of the Rio Preguiças watershed and at the site of the isolated population of bearded capuchin monkeys. Using Sentinel imagery and high‐resolution images collected from unoccupied aerial vehicles, we tracked land cover changes from 2017 to 2023 and projected mangrove forest changes 5 years into the future. Remote sensing and GIS techniques revealed substantial and significant mangrove loss at the culturally important Capuchin mangrove site and substantial and significant forest transitions across the broader watershed. Both regions showed reduced natural land cover and increased human‐induced changes, which impacted the forests. Sand dune overwash in mangrove forests alters the mudflat dynamics, reshaping vegetation physiognomies within the mangroves and potentially leading to a decline in the crab population, a primary food source for capuchins and a source of protein and income for the local community. These findings underscore the need for conservation plans to ensure the long‐term survival of the mangrove forests, the local fisheries‐based livelihoods and the culturally unique isolated population of bearded capuchin monkeys at Morro do Boi. Short The unique ecological conditions of the mangrove forests in the Rio Preguiças Estuary, Maranhão, Brazil, support a culturally isolated population of bearded capuchin monkeys and contribute significantly to the livelihoods and economy of the local community. This study uses Sentinel imagery and high‐resolution images collected from unoccupid aerial vehicles to track land cover changes from 2017 to 2023 and project mangrove forest changes 5 years into the future, showing significant forest loss at the site and underscoring the need for conservation plans to ensure the long‐term survival of the mangroves.

Accurate global mangrove soil carbon estimates are essential, considering the critical role mangroves play in the coastal carbon cycle. However, current global estimates vary widely, ranging from 2.26 to 10.2 Pg C. Large uncertainties in carbon stocks can be challenging for effective policymaking and inaccurately estimate climate mitigation potential. Here, we identify factors driving spatial and landscape variability by comparing five global mangrove soil carbon stock models. Using the ensemble mean, we generate a global soil carbon stock estimate of 4.13 ± 0.89 Pg C (to 1 m depth). Significant (P < 0.001) spatial variability occurred in Africa and Asia, with high standard deviation between models and limited data representation. High standard deviation occurred in specific geomorphic settings, including terrigenous, deltaic, carbonate and open coasts, within microtidal sites and regions of low and high species diversity. Our findings can help guide future research and reduce uncertainties in carbon stock estimates.

HRBS-GLWNB 2020 presents the first open-source and high-resolution bathymetry, shoreline, and water level data for Lakes Victoria, Albert, Edward, and George in East Africa. For each Lake, these data have three primary products collected for this project. The bathymetric datasets were created from approximately 18 million acoustic soundings. Over 8,200 km of shorelines are delineated across the three lakes from high-resolution satellite systems and uncrewed aerial vehicles. Finally, these data are tied together by creating lake surface elevation models collected from GPS and altimeter measures. The data repository includes additional derived products, including surface areas, water volumes, shoreline lengths, lake elevation levels, and geodetic information. These data can be used to make allocation decisions regarding the freshwater resources within Africa, manage food resources on which many tens of millions of people rely, and help preserve the region’s endemic biodiversity. Finally, as these data are tied to globally consistent geodetic models, they can be used in future global and regional climate change models. Measurement(s) bathymetry • shorelines Technology Type(s) echo soundings • remote sensing Sample Characteristic - Environment lake bed • lake shore Sample Characteristic - Location Africa • East Africa • Uganda • • Tanzania • Democratic Republic of the Congo • Lake Victoria • Lake Edward • Lake Albert • Lake George

Global and spatially explicit information about the interaction between habitat and wildlife species is critical to enhancing conservation efforts. Despite the recognized importance of mangrove forests to non-human primates, the relationship between the two lacks understanding. To counter this, we created the MangPrim-21 database to map and measure the locations of interactions between all non-human primates and all mangrove forests globally. We report our findings across the global, national, and local scales for all inventoried non-human primates and all inventoried mangrove forests. Globally, we find that half of all non-primates potentially use mangrove forests, and more than half of the global mangrove forest falls within the delineated range of at least one non-human primate species. Nationally, we find that Indonesia, Madagascar, Brazil, Cameroon, and Malaysia likely have the most non-human primate and mangrove forest interactions. At the subnational level, we find that several discrete locations in Kalimantan are critical to both mangrove forests and non-human primates. The MangPrim-21 database provides a globally consistent and locally applicable database of non-human primate and mangrove forest interactions. The results presented have broader implications for non-human primate and mangrove conservation and global actions to protect both. Additionally, our results raise questions about the idea that non-human primates primarily use mangrove forests as a refuge from human encroachment and habitat degradation.

This manuscript presents a new global database that tracks annual global mangrove forest change rates since 2000. By synthesizing several remotely sensed databases such as Mangrove Forests of the World, Global Mangrove Watch, and High-Resolution Global Maps of 21st-Century Mangrove Forest Cover Change, this database provides mangrove forest change information at approximately 30 m annually and globally. It is a consistent and systematic mangrove forest change database across all years. Between 2000 and 2020, mangrove forests lost 3.42% of their original global area, shrinking from approximately 139,716 km2 in 2000 to 134,383 km2 in 2020, resulting in an annual loss rate of 0.17%. As of 2020, Indonesia, Brazil, Australia, Nigeria, and Malaysia are the top five mangrove-holding countries, containing slightly over 50% of the global mangrove holdings. Indonesia alone contains 22% of global mangrove forests.