Inland fisheries are important for food security in communities around the world, especially in developing countries. In North Rupununi, Guyana, the state of exploited stocks is poorly understood, and fishery monitoring and assessment are challenging because diverse fishing gears and target species are distributed across a heterogeneous landscape. This complexity created an opportunity for community-based monitoring (CBM) to support data-limited assessment. Standardised CBM was established for the North Rupununi as part of a new inland fisheries management plan initiated by indigenous community groups with support from the government. Quantitative length-based assessments undertaken for target stocks suggested moderate levels of exploitation consistent with local perception. Our study highlights that local experts and community participants with different levels of training can collect accurate biodiversity data. Further development of CBM is important in North Rupununi. We recommend using local ecological knowledge indicators to track spatial and temporal patterns in exploitation and fish stock status.
Tag: assessment
Estimation of Aboveground Biomass in Agroforestry Systems over Three Climatic Regions in West Africa Using Sentinel-1, Sentinel-2, ALOS, and GEDI Data
Agroforestry systems (AFS) offer viable solutions for climate change because of the aboveground biomass (AGB) that is maintained by the tree component. Therefore, spatially explicit estimation of their AGB is crucial for reporting emission reduction efforts, which can be enabled using remote sensing (RS) data and methods. However, multiple factors including the spatial distributions within the AFS, their structure, their composition, and their variable extents hinder an accurate RS-assisted estimation of the AGB across AFS. The aim of this study is to (i) evaluate the potential of spaceborne optical, SAR and LiDAR data for AGB estimations in AFS and (ii) estimate the AGB of different AFS in various climatic regions. The study was carried out in three climatic regions covering Côte d’Ivoire and Burkina Faso. Two AGB reference data sources were assessed: (i) AGB estimations derived from field measurements using allometric equations and (ii) AGB predictions from the GEDI level 4A (L4A) product. Vegetation indices and texture parameters were generated from optical (Sentinel-2) and SAR data (Sentinel-1 and ALOS-2) respectively and were used as predictors. Machine learning regression models were trained and evaluated by means of the coefficient of determination (R2) and the RMSE. It was found that the prediction error was reduced by 31.2% after the stratification based on the climatic conditions. For the AGB prediction, the combination of random forest algorithm and Sentinel-1 and -2 data returned the best score. The GEDI L4A product was applicable only in the Guineo-Congolian region, but the prediction error was approx. nine times higher than the ground truth. Moreover, the AGB level varied across AFS including cocoa (7.51 ± 0.6 Mg ha−1) and rubber (7.33 ± 0.33 Mg ha−1) in the Guineo-Congolian region, cashew (13.78 ± 0.98 Mg ha−1) and mango (12.82 ± 0.65 Mg ha−1) in the Guinean region. The AFS farms in the Sudanian region showed the highest AGB level (6.59 to 82.11 Mg ha−1). AGB in an AFS was mainly determined by the diameter (R2 = 0.45), the height (R2 = 0.13) and the tree density (R2 = 0.10). Nevertheless, RS-based estimation of AGB remain challenging because of the spectral similarities between AFS. Therefore, spatial assessment of the prediction uncertainties should complement AGB maps in AFS.
Gender assessment study for improved fruit tree and Macadamia nuts value chains in Mzimba and Kasungu districts of Malawi
The growing national and export markets for improved fruit (including mango) and macadamia nuts in Malawi could offer promising opportunities for smallholder farmers if they are better integrated (with appropriate resources and training) within their respective value chains. While the macadamia value chain is highly structured, export oriented and dominated by large estates, the mango and improved fruits value chains are underdeveloped, with poor organization and very limited processing done in the country. This impacts the extent smallholder farmers can be engaged in these value chains. Women, in particular, have fewer opportunities to benefit than men due to local gender norms and barriers. These range from labour roles, control of land, assets, and income, as well as lower agency at household and collective organization levels. It is critical to better understand the gender dynamics at different nodes along the value chain and within the different local contexts, in order to design gender sensitive interventions that will positively engage and empower women smallholders.
Drivers of success in collaborative monitoring in forest landscape restoration: An indicative assessment from Latin America
Despite growing global attention on forest landscape restoration (FLR) as an integrated approach to enhancing environmental and human well-being, the potential for leveraging monitoring to catalyze learning and improve management outcomes is not being fully realized. We assessed the extent to which collaborative monitoring, a process that embraces cross-scale multi-level actors and interactions in the collection and use of information, is considered across FLR projects in Latin America by applying a diagnostic of 54 “success factors” scored from 1 (factor not in place) to 5 (factor fully in place). Responses were collected from 36 projects across 12 countries. Although respondents generally understood monitoring as crucial to FLR success, local participation scored as insufficient. Several of the lowest-ranked success factors related to training for local people in the use of tools, forms and technology for data collection, and to interpreting data to promote understanding of management outcomes. The most notable finding related to the paucity of networks or entities to leverage information into knowledge-sharing and learning opportunities from the top-down and the bottom-up. Our results provide a preliminary indication of how to promote collaborative monitoring approaches in the context of FLR projects in Latin America. First, it requires enhanced integration among academics, local communities and governmental and non-governmental organizations. Second, it requires a minimum level of harmonization with current policy and normative forest conservation and restoration instruments. Finally, it needs bridging organizations or individuals to share results and learning as well as dedicated resources for information infrastructures to facilitate knowledge sharing.
Measuring agroecology and its performance: An overview and critical discussion of existing tools and approaches
Agricultural and food systems (AFSs) are inherently multifunctional, representing a major driver for global crises but at the same time representing a huge potential for addressing multiple challenges simultaneously and contributing systemically to the achievement of sustainable development goals. Current performance metrics for AFS often fail to take this multifunctionality into account, focusing disproportionately on productivity and profitability, thereby excluding “externalities,” that is, key environmental and social values created by AFS. Agroecology is increasingly being recognized as a promising approach for AFS sustainability, due to its holistic and transformative nature. This growing interest in and commitment to agroecology by diverse actors implies a need for harmonized approaches to determine when a practice, project, investment, or policy can be considered agroecological, as well as approaches that ensure the multiple economic, environmental, and social values created by AFS are appropriately captured, hence creating a level playing field for comparing agroecology to alternatives. In this contribution to the special issue on agroecology, we present an overview of existing tools and frameworks for defining and measuring agroecology and its performance and critically discuss their limitations. We identify several deficiencies, including a shortage of approaches that allow for measuring agroecology and its performance on landscape and food system scale, and the use of standardized indicators for measuring agroecology integration, despite its context-specificity. These insights highlight the need for assessments focused on these overlooked scales and research on how best to reconcile the need for globally comparable approaches with assessing agroecology in a locally relevant manner. Lastly, we outline ongoing initiatives on behalf of the Agroecology Transformative Partnership that aim to overcome these shortcomings and offer a promising avenue for working toward harmonization of approaches. All readers are invited to contribute to these collaborative efforts in line with the agroecology principle of participation and co-creation of knowledge.
Assessing Sumatran Peat Vulnerability to Fire under Various Condition of ENSO Phases Using Machine Learning Approaches
In recent decades, catastrophic wildfire episodes within the Sumatran peatland have contributed to a large amount of greenhouse gas emissions. The El-Nino Southern Oscillation (ENSO) modulates the occurrence of fires in Indonesia through prolonged hydrological drought. Thus, assessing peatland vulnerability to fires and understanding the underlying drivers are essential to developing adaptation and mitigation strategies for peatland. Here, we quantify the vulnerability of Sumatran peat to fires under various ENSO conditions (i.e., El-Nino, La-Nina, and Normal phases) using correlative modelling approaches. This study used climatic (i.e., annual precipitation, SPI, and KBDI), biophysical (i.e., below-ground biomass, elevation, slope, and NBR), and proxies to anthropogenic disturbance variables (i.e., access to road, access to forests, access to cities, human modification, and human population) to assess fire vulnerability within Sumatran peatlands. We created an ensemble model based on various machine learning approaches (i.e., random forest, support vector machine, maximum entropy, and boosted regression tree). We found that the ensemble model performed better compared to a single algorithm for depicting fire vulnerability within Sumatran peatlands. The NBR highly contributed to the vulnerability of peatland to fire in Sumatra in all ENSO phases, followed by the anthropogenic variables. We found that the high to very-high peat vulnerability to fire increases during El-Nino conditions with variations in its spatial patterns occurring under different ENSO phases. This study provides spatially explicit information to support the management of peat fires, which will be particularly useful for identifying peatland restoration priorities based on peatland vulnerability to fire maps. Our findings highlight Riau’s peatland as being the area most prone to fires area on Sumatra Island. Therefore, the groundwater level within this area should be intensively monitored to prevent peatland fires. In addition, conserving intact forests within peatland through the moratorium strategy and restoring the degraded peatland ecosystem through canal blocking is also crucial to coping with global climate change.
Asia-Pacific roadmap for primary forest conservation
Primary forests and natural landscapes in Asia and the Pacific are under increasing pressure and threats driven by population growth, migration and conflict, globalization and economic growth, urbanization, mining and infrastructure development, agriculture and planted forest expansion, forest fires and invasive species. Many of these threats are increasingly exacerbated by climate change. To address these threats, FAO and the Center for International Forestry Research (CIFOR), lead center of the CGIAR research programme on Forests, Trees and Agroforestry (FTA), have developed a roadmap for the conservation of primary forests in Asia and the Pacific, building upon state-of-the-art knowledge and extensive consultation of key regional stakeholders. This publication uses a remote-sensing methodology to accurately and consistently identify and delineate the remaining ‘intact forests’ and ‘contiguous intact forests’ in the Asia-Pacific region over large areas, over long periods of time, and at reasonable costs. It illustrates the huge diversity of forest formations in Asia and the Pacific and calls for a better understanding of the dynamic at stake in forest ecosystems and surrounding landscapes at finer scale. It proposes a set of recommendations, inviting policymakers and other relevant stakeholders to adopt an integrated landscape perspective and to combine different mechanisms and tools at different scales, including protected areas and other area-based conservation measures, to support effective primary forest conservation.
The Women Shellfishers and Food Security Project: Multivariate analysis of the theory of change model
This report is a summary of a multivariate analysis of the theory of change model of the USAID Women Shellfishers and Food Security Project, which is a co-creation of the University of Rhode Island (URI) and partners from West Africa – the University of Cape Coast (UCC) in Ghana, the University of Ghana (UG), TRY Oyster Women’s Association (TRY) in The Gambia, World Agroforestry (ICRAF), and the US Agency for International Development (USAID). This project seeks to address the need for greater attention to food security for women shellfishers and their families while improving biodiversity conservation of the ecosystems on which their livelihoods depend. The key project components are to: 1) Conduct the first-ever participatory regional assessment of the situation, unmet needs, and promising approaches to shellfish co-management led by women across the eleven countries in West Africa. 2) Elaborate and test elements of models based on existing approaches through site-based research in The Gambia and Ghana to strengthen the evidence base for successful elements of the model. 3) Foster a community of practice around the development and dissemination of a toolkit on a rights-based,ecosystem-based, participatory co-management of shellfish by women in mangrove ecosystems in West Africa.
Advancing research on ecosystem service bundles for comparative assessments and synthesis
Social-ecological interactions have been shown to generate interrelated and reoccurring sets of ecosystem services, also known as ecosystem service bundles. Given the potential utility of the bundles concept, along with the recent surge in interest it is timely to reflect on the concept, its current use and potential for the future. Based on our ecosystem service bundle experience, expertise, and ecosystem service bundle analyses, we have found critical elements for advancing the utility of ecosystem service bundle concept and deepening its impact in the future. In this paper we 1) examine the different conceptualizations of the ecosystem service bundle concept; 2) show the range of benefits of using a bundles approach; 3) explore key issues for improving research on ecosystem service bundles, including indicators, scale, and drivers and relationships between ecosystem services; and 4) outline priorities for the future by facilitating comparisons of ecosystem service bundle research.
Taking stock of national climate action for forests: 2021 NYDF Assessment report
The original aim of Goal 7 of New York Declaration on Forests (NYDF) has been met: the Paris Agreement confirms forests’ pivotal role in the international climate agenda. But at a time when the protection, restoration, and sustainable management of forests have never been more urgent, global forest loss is in a worrying upward trend. It is still too early to assess country’s progress on their commitments under the Paris Agreement because countries will only report the status of NDC implementation few years from now. In the meantime, we take stock of governments’ existing domestic efforts and policies, and offer recommendations on what governments can do to accelerate forest-based mitigation outcomes.