The high rate of depredation of forest resources causes major climatic changes that affect the economic activities and health of populations, plunging them into poverty and social problems. The state is responsible for dealing with these problems, because it has the technical, legal, and economic power to do so. This research aims to identify the factors that limit the design and formulation of public policies for the conservation of natural resources at the level of local district and provincial governments in Peru. For this study, we used qualitative methodology and non-probabilistic sampling, as well as techniques such as unstructured interviews, focus groups, and documentary review; moreover, for data analysis, we applied the theoretical saturation design in grounded theory. The results show that the conservation of natural resources is not positioned as a priority public policy in municipal administrations; furthermore, the organic units of natural resources suffer financial restrictions, and not because of a lack of budget availability, but because of a lack of will and decision-making capacity of authorities and civil servants, as well as a lack of coordination between the different national governments. It concludes that there are conflicts of interest in public policy making, with abuse of power and corruption predominating. Furthermore, the complexity of addressing sustainability criteria and the inability to confront the environmental crisis mean that international summits and national norms are attenuated in the face of the problems of environmental degradation. Deforestation should be considered a major public priority problem because of its environmental, economic, social, and health impacts. These problems require a holistic approach that combines local, national, and international policies and fosters effective and participatory governance.

This systematic review examined how the Travel Cost Method (TCM) works together with other valuation methods, such as stated and declared preferences, to improve estimates of total economic value (TEV). Despite the widespread use of TCM, no systematic synthesis has examined how its integration with complementary methods enhances TEV estimation across different ecosystems and geographical contexts. Following PRISMA guidelines, we conducted searches in Scopus and Web of Science, identifying 245 records. After the screening process, 57 studies remained for analysis. Results show that 74% of the studies combined TCM with Contingent Valuation Method (CVM), and 12.3% with Choice Experiment (CEM). Three chronological phases were identified: early domination by the United States (1985–2000), international expansion and diversification (2001–2015), and recent methodological innovation led by China (2016–2024). Forest and recreational ecosystems accounted for 25% of applications, followed by marine-coastal (21%). Within cultural ecosystem services, the subcategory of physical and experiential interactions predominates with 63.1%. Comparative analysis indicates that TCM systematically produces higher and more variable monetary estimates than CVM, reflecting its sensitivity to travel behavior and spatial scale, while stated preference methods provide more stable estimates of non-use values. Persistent methodological limitations include non-probabilistic sampling and uneven ecosystem coverage. This review advances the literature by providing the first comprehensive synthesis of integrated TCM applications, demonstrating how methodological combinations strengthen TEV estimation beyond single-method approaches. The findings offer practical guidance for policymakers designing environmental impact assessments, environmental managers selecting valuation tools tailored to ecosystem and management objectives, and researchers seeking standardized and robust frameworks for integrated ecosystem service valuation.

Land use and land cover change (LULC) driven by agricultural expansion has become a major environmental challenge in tropical regions, particularly in coffee-producing landscapes, where economic growth often conflicts with forest conservation. This study integrates multi-temporal land cover analysis and future scenario modeling to assess LULC dynamics associated with coffee expansion in the district of Ocumal, in the Amazona Peru. Land cover classes were identified using a Random Forest classification approach applied to Landsat imagery from 2000, 2010, and 2020 processed in Google Earth Engine (GEE), while future scenarios for 2030 and 2040 were simulated using the MOLUSCE plugin in QGIS 2.18. Cross-tabulation matrices and annual rates of change were calculated using IDRISI SELVA 17.0. The results show increases of 12.6% and 7.4% in coffee crop area during 2000–2010 and 2010–2020, respectively, alongside a significant reduction in forest and grassland cover (−5.06% and −2.10% during 2010–2020), mainly driven by agricultural expansion facilitated by transportation infrastructure and market accessibility. This study contributes to the international literature by providing empirical evidence from the Peruvian Amazon on the long-term impacts of coffee expansion on land use and land cover, supporting land-use planning and sustainable agriculture in tropical regions.

Manilkara (Sapotaceae) includes tropical tree species of high ecological and socio-economic value, yet genetic and phylogenetic evidence remains uneven across taxa and eco-geographic regions. Here, we synthesize studies conducted between 1999 and 2025 which summarize the use of molecular markers to infer genetic diversity, connectivity, population structure, and evolutionary relationships within this genus. The studies are dominated by PCR-based marker systems, including dominant markers (like RAPD and SCoT) and microsatellites from the nuclear genome and plastid genome. Other studies rely on PCR-amplified sequence loci, such as ITS and chloroplast regions, while others use high-throughput technologies, including NGS-assisted SSR development, sequences of complete plastomes, and targeted nuclear sequencing. Overall, studies using SSRs provide the most informative estimates for within-species diversity and fine-scale structure, whereas plastid datasets (cpSSR/cpDNA) mainly support inference on maternal lineages and plastid-based relationships but can be constrained by uniparental inheritance and limited variation, especially under small sampling. Some limitations found include heterogeneous sampling, inconsistency in reporting the methodological parameters, and limited connection with ecological or phenotypic parameters which restricts chances of inferences on demography and adaptation. Based on this review, future research in Manilkara would benefit from setting up a broader taxonomic and geographic coverage, incorporating genome-wide technology where feasible to strengthen conservation management, and breeding opportunities in Manilkara.