Examinando por Autor "Veneros, Jaris"

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Effectiveness of protected areas in containing the loss of Peruvian Amazonian forests
(Elsevier, 2025-01-11) Rojas Briceño, Nilton B.; Cajas Bravo, Verónica; Pasquel Cajas, Alexander; Guzman Valqui, Betty Karina; Silva López, Jhonsy O.; Veneros, Jaris; García, Ligia
Peruvian Amazonian Forests (PAF), vital for biodiversity, climate, and human well-being, lost 2.92M ha during 2001-2022, mainly due to anthropogenic activities. This prompted strategies to conserve and protect the PAF, such as land use and natural resource restrictions, with natural protected areas (NPAs) being the main strategy. This study evaluated the effectiveness of 41 NPAs in containing deforestation in the PAF by analyzing national spatial data. An Effectiveness Index (EI) was constructed by adding five standardized parameters: (1) the percentage of deforested area (DA%) and (2) its annual rate of change (DAr) between 2000 and 2022 inside each NPA, (3) the difference in DAr between NPAs and their surrounding areas, (4) their corresponding ecoregions, and (5) the entire PAF. In 2000, the DA% was 7.15% of the PAF, increasing to 10.88% in 2022. NPAs showed lower DAr than their surrounding areas and ecoregions, except for five NPAs. Of the 41 NPAs, nine were non-effective (EI≤3), 31 moderately effective (3
Forest structure and fragmentation dynamics in cacao-producing landscapes of Amazonas, Peru, revealed by multi-temporal land-use change and spaceborne LiDAR
(Springer Science+Business Media, LLC, part of Springer Nature, 2026-05-27) Cotrina Sanchez, Alexander; Barboza, Elgar; Veneros, Jaris; Huaman Pilco, Angel Fernando; García, Ligia; Guzman Valqui, Betty Karina; Oliva, Manuel; Rojas Briceño, Nilton B.; Torresani, Michele
The ongoing loss and degradation of tropical forests poses a significant threat to biodiversity, carbon storage, and ecosystem services throughout the Amazon Basin. Agroforestry systems such as cacao cultivation can help balance production and conservation, yet integrated analyses combining spatial and structural forest data remain limited. This study integrates multi-temporal land-use/land-cover (LULC) data, fragmentation metrics, and canopy indicators from the Global Ecosystem Dynamics Investigation (GEDI) mission to assess forest transformation across two contrasting cacao-producing landscapes in the Amazonas region of Peru. LULC dynamics (1985–2020) were derived from the 30m Global Land Cover Change Dataset (GLC_FCS30D), with 2020 used as a baseline consistent with the European Union Deforestation Regulation (EUDR). The 2020 forest/non-forest map was compared with the 10m Global Forest Cover 2020 product to quantify fragmentation across multiple grid sizes. GEDI L2A and L2B data provided structural metrics, including relative height (RH25–RH98), plant area index (PAI), foliage height diversity (FHD), and canopy cover, which were linked to fragmentation indicators. In the indigenous territories of Condorcanqui, cacao landscapes maintained stable forest cover, while rural areas in Bagua and Utcubamba showed greater forest loss and landscape modification. Fine-scale (10m) data revealed localised zones of conservation and degradation, particularly in lowland cacao areas. Taller, more structurally complex canopies were associated with less fragmented forests, whereas shorter and more heterogeneous structures reflected long-term disturbance. Integrating spaceborne LiDAR with multi-scale fragmentation metrics provides robust indicators of forest integrity, supporting sustainable cacao agroforestry management and conservation plannin.
Geographic information system applications in bee research
(MDPI, 2026-05-29) Rojas Briceño, Nilton B.; Silva López, Jhonsy O.; Guzman Valqui, Betty Karina; Ix Balam, Manuel A.; Ramos Tejeda, José L.; Oliva Cruz, Manuel; Veneros, Jaris; García, Ligia
Bees play crucial ecological, economic, and environmental roles, and research on them increasingly includes a spatial dimension. Geographic Information Systems (GISs) enable the acquisition, storage, analysis, management, and visualization of spatial data. However, GIS applications in bee research have expanded while remaining dispersed across topics, tools, taxa, and methodological approaches. This study provides a comprehensive and updated review of GIS applications in bee research by integrating bibliometric analysis with a structured synthesis of GIS purposes and techniques. A total of 228 publications were analyzed to assess publication trends, co-authorship patterns, keyword themes, study areas, taxonomic coverage, GIS application themes, and methodological tools. GIS was used to select suitable apiary sites, map floral resources, analyze bee behavior, assess diseases and pests, monitor bee products, evaluate urban and landscape contexts, and predict climate change effects. The main GIS-related approaches included multicriteria decision analysis (MCDA), remote sensing, species distribution models (SDMs), spatial interpolation, WebGIS platforms, and emerging machine-learning applications. The review also identified underrepresented taxa, especially wild bees, stingless bees, and other Apis species. Future advances should integrate MCDA with data-driven models, improve floral-resource mapping with remote sensing, and strengthen reproducibility through standardized spatial data and workflows.