Impact of Co-Management Strategies on Forest Ecosystems in Protected Areas of Bangladesh Using Remote Sensing and GIS Analysis

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Shafiqul Bari, Mahmuod Abubakar Bashir, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8418868/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 15 You are reading this latest preprint version Abstract The Protected Area (PA) concept has contributed significantly to forest conservation worldwide and has also contributed to the expansion of forest cover. Co-management of PAs has emerged as a strategy to make forest restoration and biodiversity conservation more effective by encouraging the active participation of local people. This study analyzed the co-management effects of PA in two protected areas of Dharmapur Shal Forest and Nawabganj National Park in Dinajpur District, Bangladesh. Land use and land cover change were monitored between 1990 and 2022 using Landsat images. The study considered four main categories; forests, encroached areas, barren lands, and water bodies. The findings indicated that forest cover diminished in both forests between 1990 and 2003 but experienced a significant recovery by 2022. The expanse of Dharmapur Shal forest diminished from 552.05 hectares in 1990 to 469.95 hectares in 2003, then rising to 550.41 hectares in 2022. While the forest cover in Nawabganj National Park declined from 454.18 hectares to 393.72 hectares, it recovered to 432.36 hectares in 2022, demonstrating the hopeful effectiveness of co-management strategies. The Barren land initially increased and decreased in both areas, while the waterbody remained almost stable. Ecosystem service values (ESVs) related to carbon sequestration, biodiversity, and water regulation also improved. Stakeholder perception analysis, including forest officials and local communities, revealed strong support for co-management, citing enhanced forest cover, increased native species, and reduced illegal extraction. However, challenges remain in achieving historical biodiversity levels. This study highlights the potential of co-management in forest restoration and sustainable land governance in developing countries and provides evidence-based insights to inform future policy and planning. Protected Area Co-management Land-use Change Ecosystem Services Forest Conservation Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Forests are critical natural resources that support biodiversity, mitigate climate change and provide essential ecosystem services (Salam, 2024 ; Azfar et al., 2019). Due to anthropogenic activities like deforestation, logging, and urbanization, along with climate change continue to pose serious threats to forest ecosystems (Rodríguez & Redondo, 2023 ; Daly & Bryant, 2013 ; Khan et al., 2009 ; Arshad et al., 2020 ; Noor et al., 2023 ). For a very long time, forests have been losing ground (Ullah et al., 2022 ). A report of United Nations suggested that about 12 million hectares of forest are eliminated each year. The current rapid deforestation rate in the tropics is nearly 6 million ha of forests lost between 2010 and 2015, which has raised serious concerns (FAO, 2016 ). On a global and national level, preventing or, at the very least, reducing deforestation requires specialized land-use regulations that address forest loss (Sahide & Giessen, 2015 ). Since the causes of deforestation vary at different temporal and spatial scales, land-use policies and forest conservation measures to prevent deforestation and lessen its effects are divisive (Geist et al., 2002; Pfaff et al., 2013 ; Rudel et al., 2009 ). The most often used land-use strategy to safeguard forests and preserve biodiversity is the creation of protected areas (Watson et al., 2014a , b ). This land-use policy is not new, but the number and coverage of protected areas increased significantly around the world over the past century from a small number of sites at the beginning of the 20th century to 258,608 designated protected areas covering 20.28 million square kilometers in 2020, or 15% of the earth's land surface (UNEP-WCMC, 2020 ; Watson et al., 2014a , b ). The concept of protected areas has been redefined, developed, and modernized. According to Butchart et al. ( 2012 ), Geldmann et al. ( 2013 ), Joppa and Pfaff ( 2010 ), and Naughton-Treves et al. ( 2005a ), protected areas have unquestionably retained biodiversity better than any other land-use policy. However, since the second half of the 20th century, protected areas and human settlements have rapidly expanded, increasing their interaction (Watson et al., 2014a , b ). Because a significant number of communities have grown near previously established Protected areas in remote locations, are now facing new challenges, and issues relating to the exclusion of local communities from Protected areas have grown to be a serious concern (Agrawal & Redford, 2009 ; Brockington et al., 2006 ). In response, the idea of including local populations in protected area management started to gain traction in the late 1970s and early 1980s (Lemos & Agrawal, 2006 ). The intellectual foundation for a shift towards decentralized environmental policies and community-based resource management was laid during the 1980s and later by extensive research by academics on common property, political ecology, community capacity, and resource management by other small-scale social formations (Lemos & Agrawal, 2006 ; Peluso, 2012 ). Nearly 15.3% of the world's forests are legally maintained by local communities, and more than 500 million people rely on these forests (Agrawal, 2007 ; RRI, 2017 ). Different names in different nations refer to these forest management methods; examples include social forestry, joint forest management (JFM), participatory forest management (PFM), co-management, community-based conservation, and community forestry (FAO, 2020 ). The term "co-management" is used in this paper as a general term to refer to the approaches mentioned above that take the form of various projects and programs in various nations. According to Matose ( 2006 ), co-management refers to government management of reserved and protected forests in which local communities actively participate in creating, planning, and implementing policy. Governments and international organizations have advocated for the conceptual and geographical development of co-management for the governance of protected areas throughout the past few decades, particularly among developing nations in the tropical region. Protected areas have now been established to preserve the forest and its environment and offer residents a means of subsistence (Anaya et al., 2018). However, on top of their already dubious effectiveness, this additional role of the protected area has increased the likelihood that it will fail to achieve its added objectives (Geldmann et al., 2013 a; Muench & Martnez-Ramos, 2016; Naughton-Treves et al., 2005b ). Lack of resources, particularly in poor and undeveloped nations, is the key factor undermining the success of protected area co-management (Balmford et al., 2003 ; Bruner et al., 2004 ; Leverington et al., 2010 ). Creating protected areas (PAs) often leads to socio-environmental conflicts, as it frequently involves the displacement of various groups from their ancestral lands. This phenomenon has resulted in "conservation refugees" (Geisler, 2003 ; Dowie, 2011 ). Therefore, there is a need to address the knowledge gap about the influence and efficiency of co-managed protected areas in conserving biodiversity because of the fast growth of protected areas, which has outpaced their monitoring and evaluation. This have to be achieved by understanding the impact of these protected areas on a global, national, and regional scale, which is required to conserve the forests by their respective communities. Only 11% of Bangladesh's territory is forest, and the remaining woods rapidly lose tree cover (Potapov et al., 2017 ). Bangladesh is a developing nation (Uddin & Taplin, 2006). The Bangladesh Forest Department (BFD) is the government agency responsible for maintaining all the country's natural forests. Compared to its neighbors Nepal and India, Bangladesh first implemented co-management of protected areas in 2004 (BFD, 2020). Co-management strategies have recently grown in popularity among locals who depend on forests and have also demonstrated some sound, long-term effects on biodiversity preservation (Mukul et al., 2012 ; Rashid et al., 2013b ). The effectiveness of the system to conserve forests, the lack of active participation from the local communities, the ambiguity regarding the roles and responsibilities of the stakeholders, and a gap in the implementation of policy frameworks are some of the serious concerns regarding these co-managed Protected areas, on the other hand (Mollick et al., 2018 ; Rahman et al., 2017 ; Rashid et al., 2013a ). The creation of additional Protected areas and the growth of co-management systems to govern and manage these Protected areas are deeply ingrained in Bangladesh's forestry policies, which seek to cover 30% of state-owned forests by 2035 (BFD, 2016). Nevertheless, the frequent revisions to forest policies, rules, and acts over the protected areas in the past decade have clarified that the current policy and legal frameworks are insufficient to sustain such expansion plans (Rahman et al., 2016b ). Through programs supported and aid from international donor organizations, the BFD is scaling up the current co-management model to new protected areas with minimal modifications (Rahman et al., 2016a ). Since there is no "one-size-fits-all" approach, replicating a co-management strategy that has appeared to be effective would not be the best option for all of Bangladesh's protected areas. The success of Protected areas must shift from number to quality while their rapid global expansion continues (Pringle, 2017 ; Watson et al., 2016 ). It is critical to assess the influence and results of the current ones to enhance the protection area's effectiveness and quality in the future. There are a few studies that look at significant populations and worldwide scales to determine the effects and results of protected area conservation of biodiversity (Hajjar et al., 2020 ; Oldekop et al., 2019 ; Watson et al., 2014a , 2014b ; Yang et al., 2021 ). In-depth micro-level studies are equally as significant as global and national-scale research because they can thoroughly understand the effects of protected areas at the local and regional levels. The findings of this research may play a crucial role in closing the governance gap between the protected area's management plan and the practical reality gap. This study addresses the knowledge gap in evaluating the ecological and social outcomes of co-managed PAs at the micro-level. Specifically, we assess forest cover change, stakeholder perceptions, and ecosystem service trends in two co-managed forests referred to as the Nawabganj National Park and Dharmapur Sal Forest, Dinajpur District, located in the northern region of Bangladesh, where continued deforestation has been occurring for years (Islam et al., 2019a , 2019b ; Moslehuddin et al., 2018 ). The results provide empirical evidence to inform forest policy, conservation planning, and sustainable land governance elsewhere in a similar geographic context. Materials and methods Study Area Profile This study was conducted at Dharmapur Sal forest, Birol in Dinajpur, which lies in the northwestern part of Bangladesh (88° 42'- 89° E, 25° 18'N-25° 29'N). The forest covers 1104.5 ha. The annual rainfall is 1726mm throughout the area, and Nawabganj National Park, Dinajpur, also lies in the northwestern part of Bangladesh (25°25'0.12" N, 89°04'59.88" E) (Islam et al., 2019a ; BFD, 2020). The forest covers 517.61 ha (Fig. 1 ). The land's topography is generally flat with a gentle southward slope. The "Barind tract" is formed on the old alluvium of the Pleistocene period. The general level of this tract is above flood level and intersected by numerous gentle depressions. The highest point in this tract does not exceed 20 feet above the surrounding land (Moslehuddin et al., 2018 ). All the areas were in designated compartments (permanent management units set by the forest department) under natural forest cover. The dominant floras are Shorea robusta and teak. There are also Gmelina arborea, Eucalyptus regnans, Syzygium cumini, Acacia auriculiformis , and a few types of Orchidaceae (Mukul et al., 2012 ; Nath et al., 2016 ). Wild animals include Bengal foxes, jungle cats, fishing cats, and snakes (Islam et al., 2019b ). Detection of Land Use and Land Cover Change This study also uses spatial analysis to make the findings more comprehensive (Madnee et al., 2025 ). Landsat images with 30m resolution from 1990, 2003, and 2022 were collected from the USGS Earth Explorer website (Table 1 ). These images were taken during the dry season (October, November, and December) to ensure minimum cloud cover and water level stability. Radiometric and atmospheric corrections are applied to eliminate potential inconsistencies in the data due to various atmospheric and geological differences. The geo-referencing accuracy of the 2022 image is improved with the help of ground control points and Google Earth images collected in the field in March 2023. Images are co-registered in ArcGIS Pro and are projected using 30m resolution and the UTM coordinate system (UTM-WGS 1984 Zone 46). Land use land cover (LULC) classification is done using the modified FAO (FAO, 2011 ) method and maximum likelihood algorithm, where classifications include barren land, encroached area/agriculture, forest, and waterbody (Nurrochmat et al., 2024 ) (Fig. 2 ). The post-classification comparison (PCC) method was applied to analyze LULC change over time and the data was analyzed in Excel. Time series analysis was also done to find some important patterns of the land use/land cover changes (Madnee et al., 2025 ). Table 1 Characteristics of Landsat Satellite image data used for the study Satellite Name Sensor ID Row / Path Data Acquisition Date Resolution Source Landsat 5 TM 138/42 29 Oct 1990 30m USGS Landsat 5 TM 138/42 29 Oct 1990 30m USGS Landsat 5 TM 139/42 18 Nov 2003 30m USGS Landsat 5 TM 139/42 18 Nov 2003 30m USGS Landsat 9 OLI_TIRS 138/42 30 Nov 2022 30m USGS Landsat 9 OLI_TIRS 138/42 07 Dec 2022 30m USGS Stakeholder Perceptions of Co-Management Outcomes The study surveyed local stakeholders about their perspectives on conservation; who participated in protected areas (PAs) management (Engen et al., 2019 ). The relationship between perceived risks to conservation values, prioritized management initiatives, and faith in PAs governance was examined, and it was determined whether these perceptions aligned with the stakeholders' chosen principal conservation strategy and their support for PAs (Engen et al., 2019 ). Data were gathered through focus groups with members of several stakeholder groups, including local forest department officials, forest managers, and group leaders living within the national park. Altogether, four focus group discussions (FGD) were arranged. During these discussions, both the local experts and two of the authors participated in performing the scoring exercise. Before starting the participatory scoring exercise, a briefing was given to the local experts about each ecological integrity and ES component. Several field trips with the local experts were arranged to different LULC types of both forest areas to get an idea about the conditions of the different ES components before the interviews. Photographs of each LULC class were taken during the field trips and used during the participatory scoring exercise. Three FGDs were first conducted as a “warm-up” exercise of scoring before the final scoring. The last (i.e., fourth) FGD was then used for the final ES scoring. All methods were performed in accordance with the relevant guidelines and regulations and approved by the Research Ethics Committee of Hajee Mohammad Danesh Science and Technology University (HSTU), Bangladesh, in compliance with the Declaration of Helsinki (World Medical Association). Calculation process of Ecosystem Service Value In this study, we referred to Costanza's ESV model to calculate the total ecosystem service valuation of the study area (Costanza et al., 1997 , 2014 ) as well used in other studies (Zhao et al., 2004 ; Arowolo A. O. et al., 2018; Yi et al., 2017 ; Akbera et al., 2018 ; Mamat, Halik, and Rouzi 2010 ; Uta et al., 2017 ; Costanza et al., 2017 ; Jalal et al., 2020 ) as follows – ESV t = \(\:{\sum\:}_{\text{i}=1}^{\text{n}}{\text{A}}_{\text{i}}\times\:{\text{E}\text{S}\text{V}}_{\text{i}}\) ……… EQ. (i) ESV -1 ha = \(\:\frac{{\text{E}\text{S}\text{V}}_{\text{t}}}{\text{T}\text{o}\text{t}\text{a}\text{l}\:\text{a}\text{r}\text{e}\text{a}\:(\text{i}\text{n}\:\text{h}\text{a}.)}\) ………EQ. (ii) Whereas; ESV t ​: Total ecosystem service value for the entire study area (e.g., Dharmapur or Nawabganj). Ai: Area (in hectares) of land use type iii (e.g., forest, waterbody, barren land, encroached area). Vi: Ecosystem service value coefficient per hectare for land use type, typically derived from previous studies such as Costanza et al. ( 1997 , 2014 ). ESV − 1 ha : Ecosystem service value per hectare for land use type. ESVi: Total ecosystem service value for land use type Equation (i) adds the ESVs of all land use categories to determine the total value of ecosystem services provided by the entire landscape. Equation (ii) isolates the value of ecosystem services per unit area (hectare) for each land use type, useful for spatial comparison and scenario modeling. The change in the value of the ecosystem services was estimated by calculating the differences in the estimated values for each land-use type in 1990, 2003, and 2022. Results Land Use and Land Cover Change from 1990 to 2022 The classified maps reveal significant temporal changes in land cover in both Dharmapur Sal Forest and Nawabganj National Park (Figs. 3 & 4). Between 1990 and 2003, both areas experienced a decline in forest cover and an increase in barren land. By 2022, forest cover showed substantial recovery; suggesting the effectiveness of co-management and restoration interventions. Water bodies remained relatively stable, while encroached areas slightly decreased. These findings are based on a consistent classification approach using Landsat data and maximum likelihood algorithms To ensure the reliability of the land use and land cover (LULC) classification results, an accuracy assessment was conducted using stratified random sampling and ground-truth data for the year 2022, complemented by historical imagery and ancillary data for 1990 and 2003. The results revealed high classification performance across all study years. The overall accuracy for 1990, 2003, and 2022 was 89.25%, 87.65%, and 91.45%, respectively. Correspondingly, the kappa coefficients (κ), which account for agreement beyond chance, were 0.864 for 1990, 0.843 for 2003, and 0.892 for 2022. These values indicate strong to almost perfect agreement between the classified maps and reference data. The highest accuracy in 2022 can be attributed to field-collected GPS points and high-resolution Google Earth validation. The consistent performance across all years confirms the robustness of the LULC classification and supports the validity of the temporal change analysis conducted in this study. The amount of transition in various land use land cover (LULC) categories from 1990 to 2022 in Dharmapur Sal Forest and Nawabganj National Park is shown in Table 2 . Table 2 The amount of transition in various land use land cover (LULC) categories from 1990 to 2022 in Dharmapur Sal Forest and Nawabganj National Park. Land Use Land Cover (LULC) Categories 1990 2003 2022 Comparative Change (1990–2022) Area (ha) Area (ha) Area (ha) Area (ha) Dharmapur Sal Forest, Birol, Dinajpur Forest Area 552.05 469.95 550.41 -1.64 Encroached Area 412.58 420.83 381.47 -31.11 Barren Land 7.54 101.08 56.69 49.14 Water Body 23.94 4.76 7.64 -16.31 Total 996.11 996.62 996.20 0.0 Nawabganj National Park, Dinajpur Forest Area 454.18 393.72 432.36 -21.82 Encroached Area 54.63 49.05 69.82 15.18 Barren Land 17.35 85.83 23.31 5.96 Water Body 6.76 3.23 6.75 -0.01 Total 532.93 531.82 532.23 0.0 The Table 2 presents land cover data for two forest areas, Dharmapur Sal Forest, Birol, and Nawabganj National Park, for 1990, 2003, and 2022. Changes in forest cover, encroached areas, barren land, and water bodies are noted. In Dharmapur Sal Forest, Birol, the forest cover decreased from 552.048 hectares in 1990 to 469.95 hectares in 2003. However, by 2022, forest cover will rebound, reaching 550.41 ha. This could indicate a possible restoration of forested areas after a period of decline. The encroached agricultural area experienced fluctuations but ultimately decreased from 412.58 hectares in 1990 to 381.47 hectares in 2022, possibly suggesting a change in agricultural practices or land use policies. Barren land in Dharmapur Sal Forest, Birol, increased notably from 7.55 hectares in 1990 to 101.08 hectares in 2003, decreasing to 56.69 hectares in 2022. This could be due to factors like deforestation or changes in land management. Water bodies remained relatively stable, with some minor fluctuations over the years. In Nawabganj National Park, forest cover decreased from 454.18 hectares in 1990 to 393.72 hectares in 2003 but increased slightly to 432.36 hectares by 2022. Encroached agricultural areas fluctuated, slightly increasing from 54.63 hectares in 1990 to 69.82 hectares in 2022. Barren land experienced a substantial increase from 17.35 hectares in 1990 to 85.83 hectares in 2003 before declining to 23.31 hectares in 2022. Water bodies saw small fluctuations over the years. Change detection of land use and land cover The analysis delves comprehensively into the intricate shifts in land cover percentages over successive periods within Dharmapur Sal Forest, Birol, and Nawabganj National Park. Both forest areas exhibit dynamic fluctuations, initially decreasing from 1990 to 2003 and rebounding by 2022. The forest cover in Dharmapur Sal Forest, Birol, dropped from 55.42% in 1990 to 47.17% in 2003, marking a reduction of 8.25%. A subsequent resurgence was observed, with forest cover ascending from 47.17% in 2003 to 55.25% in 2022, resulting in an augmentation of 8.08%. The encroached agricultural area, conversely, witnessed an incremental rise from 41.42% in 1990 to 42.24% in 2003, indicating a marginal increase of 0.82%, followed by a downturn to 38.29% in 2022, signifying a decrement of 3.95%. Barren land in Dharmapur Sal Forest, Birol, experienced a notable surge from 0.76% in 1990 to 10.15% in 2003, denoting an elevation of 9.39%. This trend shifted as barren land diminished from 10.15% in 2003 to 5.69% in 2022, revealing a reduction of 4.46%. Correspondingly, water coverage in Dharmapur Sal Forest, Birol, declined from 2.41% in 1990 to 0.48% in 2003, illustrating a contraction of 1.93%, and subsequently increased to 0.77% in 2022, marking a growth of 0.29%. Conversely, in the context of Nawabganj National Park, the forest cover dwindled from 85.34% in 1990 to 73.97% in 2003, signifying a decline of 11.37%, before reclaiming ground to reach 81.23% in 2022, reflecting an ascent of 7.26%. The encroached agricultural area in Nawabganj National Park declined from 10.26% in 1990 to 9.22% in 2003, marking a decrease of 1.04%, and then escalated to 13.12% in 2022, indicating an increase of 3.90%. Barren land exhibited a pronounced escalation from 3.26% in 1990 to 16.13% in 2003, portraying an increase of 12.87%, followed by a decrease to 4.38% in 2022, reflecting a reduction of 11.75%. Notably, water coverage in Nawabganj National Park maintained relative constancy at 1.27% throughout all three years. These meticulous calculations offer profound insights into the intricate fluctuations that underscore land cover dynamics over the observed years in Dharmapur Sal Forest, Birol, and Nawabganj National Park. The analysis unveils the dynamic ebb and flow in the composition of these forests, characterized by periods of both augmentation and reduction across varied land cover categories. Socioeconomic features of the Stakeholder The Table 3 presents the characteristics of the study's participants, non-participants, and stakeholders. The data was divided into various categories, and the percentages of respondents falling into each category are provided. The study involved 54 respondents, 21 participants, 27 non-participants, and six forest staff members. The participants engaged in a specific activity or program being studied, while non-participants did not participate. Forest staff refers to the employees or personnel associated with the forest area under investigation. The data highlights notable differences between the groups. While participants and non-participants exhibit variations in gender distribution, with 59% male participants and 74% male non-participants, forest staff exclusively comprises males. Education-wise, a higher percentage of non-participants (46%) have education below SSC level compared to participants (37%), whereas forest staff members are well-educated, with 67% having completed SSC to HSC. The income distribution reveals that most participants and non-participants have incomes below 100,000 Tk. Meanwhile, forest staff see a significant 67% with incomes exceeding 200,000 Tk. Proximity to the protected area (PA) shows that participants live mainly on the PAs boundary (37%), while forest staff reside outside the PAs. Finally, years of experience indicate that participants and non-participants possess similar experience durations, with forest staff members displaying varying experience levels. Table 3 Socioeconomic Features of the stakeholder in Dharmapur Sal Forest, Birol and Nawabganj National Park, Dinajpur Selected Characteristics Descriptions Respondents (%) Participants (N = 21) Non-participants (N = 27) Forest staff (N = 6) Gender Male 59 74 100 Female 41 26 0 Education Illiterate 30 27 0 HSC 14 12 33 Income 200000 0 0 67 Residence Inside PAs 23 13 0 On PAs boundary 37 41 0 Outside PAs 40 46 0 Experience 30 years 31 33 0 Stakeholders’ perception of outcomes of PAs Co-management Table 4 illustrates the diverse impacts of co-management on selected forest attributes, as assessed by Participants, Non-participants, and Forest Staff. A pattern emerges where co-management positively influences forest cover enhancement, evident in high percentages among all groups; 82% for Participants, 76% for Non-participants, and a remarkable 100% for Forest Staff. Contrarily, forest cover decreases register much lower percentages (Participants: 18%, Non-participants: 24%, Forest Staff: 0%). A similar trend is observed for the native tree population increase, with participants at 73%, non-participants at 66%, and forest staff at 69%. Conversely, the decrease in the native tree population appears at 27%, 44%, and 31%, respectively (Table 4 ). Table 4 Stakeholders’ perception on outcomes of PAs Co-management in Dharmapur Sal Forest, Birol and Nawabganj National Park, Dinajpur. Selected Attributes Impacts of Co-management Discussant (%) Participants (N = 21) Non-Participants (N = 27) Forest Staff (N = 6) Forest Cover Increasing 82 76 100 Decreasing 18 24 0 Native Tree population Increasing 73 66 69 Decreasing 27 44 31 Exotic tree population Increasing 58 62 50 Decreasing 42 38 50 Natural regeneration Increasing 73 64 67 Decreasing 27 36 33 Awareness on Biodiversity Increasing 87 72 100 Decreasing 13 28 0 Wildlife Diversity Increasing 37 41 50 Decreasing 67 59 50 Hunting Increasing 16 32 0 Decreasing 84 68 100 Ecotourism Increasing 92 87 100 Decreasing 8 13 0 Timber Collection Increasing 24 19 0 Decreasing 76 81 100 Fuel wood Collection Increasing 3 15 17 Decreasing 97 85 83 NTFPs collection Increasing 32 42 50 Decreasing 68 58 50 Ecosystem Service trend in Dharmapur Sal Forest, Birol, and Nawabganj National Park The Fig. 7 presents ecosystem service information for two locations, "Dharmapur" and "Nawabganj," for 1990, 2003, and 2022. In 1990, Dharmapur produced an ecosystem service value of 93.05, whereas Nawabganj contributed a somewhat higher value of 122.11. By 2003, Dharmapur's and Nawabganj's ecosystem service values had decreased, with Dharmapur's falling to 83.68 and Nawabganj's falling to 113.94. Discussion The temporal shifts in land cover observed across Dharmapur Sal Forest, Birol, and Nawabganj National Park reflect the interplay between human-induced pressures and ecological processes. Anthropogenic activities particularly deforestation, agricultural expansion, and urbanization were the primary drivers of forest loss, while natural regeneration and conservation initiatives contributed to recovery in later decades (Asner et al., 2005 ; Patel et al., 2019 ; Noor et al., 2023 ). Distinguishing human-induced land-use change from natural successional dynamics remains crucial to understanding forest transitions (Joshi et al., 2016 ). Over the 1990–2022 period, land cover fluctuated in response to policy interventions, community participation, and restoration projects, underscoring the adaptive nature of forest ecosystems within socio-ecological systems (ASEAN, 2007 ; FAO, 2010; Geist & Lambin, 2002 ). From the governance perspective, these dynamics illustrate that co-management frameworks can act as catalysts for forest recovery, provided they are embedded in participatory and adaptive mechanisms (Berkes, 2009; Ostrom, 1990; Plummer et al., 2012). The integration of local knowledge through participatory forest committees appears to have fostered stewardship and accountability, which are core principles of adaptive co-management (Olsson et al., 2004). In this study, GIS-based evidence of forest cover increase in the 2000s and 2010s coincides with the institutionalization of co-management projects such as Nishorgo and CREL, suggesting that decentralized governance arrangements can positively influence land cover outcomes. This aligns with global findings showing that co-management enhances biodiversity conservation when local users are granted decision-making power and benefit-sharing mechanisms (Cinner et al., 2012; Sunderlin et al., 2005; Persha et al., 2011). The focus group results reveal exact social-ecological interactions within these frameworks. High participation rates in ecotourism (participants: 92%; non-participants: 87%; staff: 100%) and low engagement in hunting (participants: 16%; non-participants: 32%) suggest a shift in livelihood orientation from extractive to conservation-compatible activities. Yet, mixed outcomes for timber and fuelwood collection (24% and 3% among participants, respectively) indicate persistent livelihood dependence on forest resources. These findings demonstrate that co-management does not eliminate resource extraction pressures but rather reconfigures them within negotiated boundaries (Chakraborty & Joshi, 2018; Ghimire et al., 2015; Poteete & Ostrom, 2004). Effective governance therefore depends on continuous dialogue, enforcement, and benefit redistribution. Importantly, the findings contribute to broader theoretical debates by emphasizing the dual role of co-management as both a governance mechanism and a social learning process. The observed recovery of native species and natural regeneration reported by a majority of stakeholders illustrates how shared management can foster collective ecological literacy. This supports the proposition that co-management systems function best when they cultivate adaptive capacities and learning networks among stakeholders (Dietz et al., 2003; Pretty, 2003). However, the heterogeneity of responses among participant groups also indicates uneven perceptions of benefits and responsibilities, echoing global critiques that co-management success often depends on equity and institutional resilience (Agrawal & Gibson, 1999; Gutiérrez et al., 2011). The recovery trends observed in this study resonate with international experiences. In Nepal, community forestry user groups have managed over two million hectares, reversing deforestation while improving livelihoods (Oldekop et al., 2019 ). Similarly, Indonesia’s Hutan Kemasyarakatan program demonstrates how tenure security and capacity building can sustain forest recovery (Sahide et al., 2016 ). The parallel with Bangladesh’s model is instructive: while legal frameworks exist to promote co-management, site-specific governance challenges such as overlapping jurisdiction and weak incentive structures must be addressed for lasting success. These lessons suggest that Bangladesh’s co-management framework is entering a “second generation” phase, where institutional maturity, ecological monitoring, and equitable benefit sharing are central to resilience. Ultimately, this study extends existing literature by empirically linking spatial forest recovery patterns with social governance processes, providing a rare longitudinal perspective (1990–2022) on co-management effectiveness. By integrating GIS analysis with stakeholder perceptions, it demonstrates how hybrid methodologies can validate ecological outcomes while revealing governance dynamics. The results reinforce that sustainable forest management is not merely an ecological or technical challenge but a negotiated social process shaped by learning, trust, and policy coherence. Strengthening these feedback loops will be critical to scaling co-management across Bangladesh’s protected areas and contributing to global targets for forest restoration and biodiversity conservation. Conclusion In conclusion, the study comprehensively analyzes land-cover changes, co-management impacts, socio-economic characteristics, and ecosystem service trends in the Dharmapur Sal Forest, Birol and Nawabganj National Park, Dinajpur. The findings underscore the dynamic nature of these ecosystems and the importance of sustainable management practices. Both forest areas exhibit dynamic fluctuations, initially decreasing from 1990 to 2003 and recovering by 2022. The research provides valuable insights into forest management's complex interplay between ecological, social, and economic factors. The need for context-specific strategies, stakeholder engagement, and ongoing monitoring is emphasized to ensure the preservation of forest ecosystems and the delivery of essential ecosystem services. Policy Recommendations Based on the results of forest cover change, ecosystem service improvements, and stakeholder perceptions, the following policy reforms and management guidelines are recommended for improving forest co-management in Bangladesh: Establish a national framework for periodic forest and ecosystem service monitoring using remote sensing, GIS tools, and participatory methods. Amend the Forest Act to define the rights, roles, and responsibilities of local communities and co-management committees in protected area governance. Develop location-specific co-management plans that reflect the ecological, social, and economic characteristics of each protected area. Provide training, capacity development, and financial incentives to local stakeholders for sustained participation. Use ESV data in national land-use planning, investment allocation, and conservation priority setting. Promote income diversification strategies such as agroforestry, non-timber forest product (NTFP) harvesting, and ecotourism to reduce pressure on forests. Encourage collaboration between the Forest Department, Ministry of Environment, local governments, and NGOs for unified conservation planning and policy execution. Implement continuous education and outreach programs to raise awareness about the ecological and economic importance of co-managed forests among local communities and the general public. Declarations Funding No funding was received for this study. Conflicts of interest / Competing interests The authors declare that they have no competing interests. Ethical Approval and Accordance with Guidelines Ethical approval for this study was obtained from the Research Ethics Committee, Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur, Bangladesh. All methods were performed in accordance with the relevant guidelines and regulations and approved by the Research Ethics Committee of Hajee Mohammad Danesh Science and Technology University (HSTU), Bangladesh, in compliance with the Declaration of Helsinki (World Medical Association). Consent to participate Verbal informed consent was obtained from all individual participants prior to the focus group discussions and interviews. Consent to publish Not applicable. Data availability The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Authors’ contribution statements: Conceptualization, Md. Manik Ali, Sudipto Saha Dipto; methodology, Sudipto Saha Dipto and Md. Manik Ali and Muhammad Madnee; software, Md. Manik Ali and Nazmin Akter; validation, Mahmuod Abubakar Bashir, Md. Farid Hasan, and Mst Mow; formal analysis, Md. Manik Ali, Sujan Kumar Shil and Md. Asif Adnan Prince; investigation, Mst. Mow; resources, Md. Shafiqul Bari; data curation, Mst. Mow; writing—original draft preparation, Sudipto Saha Dipto ; writing—review and editing, Md. Manik Ali Muhammad Madnee, Mahmuod Abubakar Bashir and Sujan Kumar Shil ; visualization, Md. Asif Adnan Prince and Sujan Kumar Shil; supervision, Md. Manik Ali and Md Shafiqul Bari; project administration, Md. Manik Ali and Md Shafiqul Bari. All authors have read and agreed to the published version of the manuscript . References Agrawal A. Forests, governance, and sustainability: Common property theory and its contributions. Int J Commons. 2007;1:111. https://doi.org/10.18352/ijc.10 . Agrawal A, Redford K. Conservation and displacement: An overview. Conserv Soc. 2009;7(1):1–10. https://doi.org/10.4103/0972-4923.54790 . Akbera MA, Khan MWR, Islam MA, Rahman MM, Rahman MR. (2018). Impact of land use change on ecosystem services of southwest coastal Bangladesh—Journal of Land Use Science . Anaya FC, Espírito-Santo MM. (2018). 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15:49:45","extension":"xml","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":198388,"visible":true,"origin":"","legend":"","description":"","filename":"849cf8bd0b9a4357a66f325eaad3517a1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8418868/v1/4a780f7d6dfedcb93cb2e433.xml"},{"id":100547387,"identity":"4216cc4c-2da0-4143-bf39-c49d52bf9248","added_by":"auto","created_at":"2026-01-19 08:15:23","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":216212,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8418868/v1/4523a0a1075d3ddd8d3e1ee1.html"},{"id":100546510,"identity":"d3e50f13-7c30-436d-9ed3-20eaa1bc80bd","added_by":"auto","created_at":"2026-01-19 08:10:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2795715,"visible":true,"origin":"","legend":"\u003cp\u003eLocation map of the study sites: Dharmapur Sal Forest and Nawabganj National Park in the Dinajpur District, northwestern Bangladesh.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8418868/v1/3d0ab3e2e641d7ab59e74791.png"},{"id":100436900,"identity":"d04dc59d-ccc9-4276-8e02-40deb0c53552","added_by":"auto","created_at":"2026-01-16 15:49:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":121594,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart illustrating the Land Use and Land Cover (LULC) classification process.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8418868/v1/98ca27afc64479c16a6d9325.png"},{"id":100546906,"identity":"f9d44220-8294-415a-8586-91edb5490914","added_by":"auto","created_at":"2026-01-19 08:13:08","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3115481,"visible":true,"origin":"","legend":"\u003cp\u003eLand-cover change from 1990 to 2022 in Dharmapur Sal Forest, Birol, Dinajpur.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8418868/v1/117b1eb051a6bf9303e44ade.png"},{"id":100546528,"identity":"bfcd8066-1b91-459d-80a1-03d13e8c3c8d","added_by":"auto","created_at":"2026-01-19 08:10:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2625960,"visible":true,"origin":"","legend":"\u003cp\u003eShowing Land-cover change from 1990 to 2022 in Nawabganj National Park, \u0026nbsp;\u0026nbsp;Dinajpur.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8418868/v1/705fb7d5cb00ad6ab0857f04.png"},{"id":100547186,"identity":"a88d04d3-3505-4711-a573-f698c19ea785","added_by":"auto","created_at":"2026-01-19 08:14:46","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":89538,"visible":true,"origin":"","legend":"\u003cp\u003eChange detection analysis of land use and land cover (LULC) in Dharmapur Sal Forest from 1990 to 2022.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8418868/v1/d17b4a8fa2e8e0696a582c3f.png"},{"id":100436903,"identity":"972c6edd-39c9-401f-8be8-216a1fe47897","added_by":"auto","created_at":"2026-01-16 15:49:45","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":86342,"visible":true,"origin":"","legend":"\u003cp\u003eChange detection of land use and land cover in Nawabganj National Park, Dinajpur\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-8418868/v1/e92eaffeb5811135cf8d1403.png"},{"id":100547525,"identity":"6ae9eead-c0ad-43d1-9f24-88c400989d50","added_by":"auto","created_at":"2026-01-19 08:15:57","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":67010,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal trend of ecosystem service values (ESVs) per unit area in Dharmapur Sal Forest and Nawabganj National Park from 1990 to 2022.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-8418868/v1/f94984adfdbbd0dd75c0bbca.png"},{"id":100554280,"identity":"15e8bb9f-5457-4687-9702-2372657a7cca","added_by":"auto","created_at":"2026-01-19 08:38:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13061127,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8418868/v1/41e25215-eff1-454f-ab59-81ae45980a1c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of Co-Management Strategies on Forest Ecosystems in Protected Areas of Bangladesh Using Remote Sensing and GIS Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eForests are critical natural resources that support biodiversity, mitigate climate change and provide essential ecosystem services (Salam, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Azfar et al., 2019). Due to anthropogenic activities like deforestation, logging, and urbanization, along with climate change continue to pose serious threats to forest ecosystems (Rodr\u0026iacute;guez \u0026amp; Redondo, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Daly \u0026amp; Bryant, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Khan et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Arshad et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Noor et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). For a very long time, forests have been losing ground (Ullah et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). A report of United Nations suggested that about 12\u0026nbsp;million hectares of forest are eliminated each year. The current rapid deforestation rate in the tropics is nearly 6\u0026nbsp;million ha of forests lost between 2010 and 2015, which has raised serious concerns (FAO, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). On a global and national level, preventing or, at the very least, reducing deforestation requires specialized land-use regulations that address forest loss (Sahide \u0026amp; Giessen, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Since the causes of deforestation vary at different temporal and spatial scales, land-use policies and forest conservation measures to prevent deforestation and lessen its effects are divisive (Geist et al., 2002; Pfaff et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Rudel et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). The most often used land-use strategy to safeguard forests and preserve biodiversity is the creation of protected areas (Watson et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003eb\u003c/span\u003e). This land-use policy is not new, but the number and coverage of protected areas increased significantly around the world over the past century from a small number of sites at the beginning of the 20th century to 258,608 designated protected areas covering 20.28\u0026nbsp;million square kilometers in 2020, or 15% of the earth's land surface (UNEP-WCMC, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Watson et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003eb\u003c/span\u003e). The concept of protected areas has been redefined, developed, and modernized. According to Butchart et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), Geldmann et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), Joppa and Pfaff (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), and Naughton-Treves et al. (\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2005a\u003c/span\u003e), protected areas have unquestionably retained biodiversity better than any other land-use policy.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eHowever, since the second half of the 20th century, protected areas and human settlements have rapidly expanded, increasing their interaction (Watson et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003eb\u003c/span\u003e). Because a significant number of communities have grown near previously established Protected areas in remote locations, are now facing new challenges, and issues relating to the exclusion of local communities from Protected areas have grown to be a serious concern (Agrawal \u0026amp; Redford, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Brockington et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). In response, the idea of including local populations in protected area management started to gain traction in the late 1970s and early 1980s (Lemos \u0026amp; Agrawal, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). The intellectual foundation for a shift towards decentralized environmental policies and community-based resource management was laid during the 1980s and later by extensive research by academics on common property, political ecology, community capacity, and resource management by other small-scale social formations (Lemos \u0026amp; Agrawal, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Peluso, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Nearly 15.3% of the world's forests are legally maintained by local communities, and more than 500\u0026nbsp;million people rely on these forests (Agrawal, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; RRI, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Different names in different nations refer to these forest management methods; examples include social forestry, joint forest management (JFM), participatory forest management (PFM), co-management, community-based conservation, and community forestry (FAO, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The term \"co-management\" is used in this paper as a general term to refer to the approaches mentioned above that take the form of various projects and programs in various nations. According to Matose (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), co-management refers to government management of reserved and protected forests in which local communities actively participate in creating, planning, and implementing policy.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eGovernments and international organizations have advocated for the conceptual and geographical development of co-management for the governance of protected areas throughout the past few decades, particularly among developing nations in the tropical region. Protected areas have now been established to preserve the forest and its environment and offer residents a means of subsistence (Anaya et al., 2018). However, on top of their already dubious effectiveness, this additional role of the protected area has increased the likelihood that it will fail to achieve its added objectives (Geldmann et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003ea; Muench \u0026amp; Martnez-Ramos, 2016; Naughton-Treves et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2005b\u003c/span\u003e). Lack of resources, particularly in poor and undeveloped nations, is the key factor undermining the success of protected area co-management (Balmford et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Bruner et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Leverington et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Creating protected areas (PAs) often leads to socio-environmental conflicts, as it frequently involves the displacement of various groups from their ancestral lands. This phenomenon has resulted in \"conservation refugees\" (Geisler, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Dowie, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Therefore, there is a need to address the knowledge gap about the influence and efficiency of co-managed protected areas in conserving biodiversity because of the fast growth of protected areas, which has outpaced their monitoring and evaluation. This have to be achieved by understanding the impact of these protected areas on a global, national, and regional scale, which is required to conserve the forests by their respective communities.\u003c/p\u003e \u003cp\u003eOnly 11% of Bangladesh's territory is forest, and the remaining woods rapidly lose tree cover (Potapov et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Bangladesh is a developing nation (Uddin \u0026amp; Taplin, 2006). The Bangladesh Forest Department (BFD) is the government agency responsible for maintaining all the country's natural forests. Compared to its neighbors Nepal and India, Bangladesh first implemented co-management of protected areas in 2004 (BFD, 2020). Co-management strategies have recently grown in popularity among locals who depend on forests and have also demonstrated some sound, long-term effects on biodiversity preservation (Mukul et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Rashid et al., \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2013b\u003c/span\u003e). The effectiveness of the system to conserve forests, the lack of active participation from the local communities, the ambiguity regarding the roles and responsibilities of the stakeholders, and a gap in the implementation of policy frameworks are some of the serious concerns regarding these co-managed Protected areas, on the other hand (Mollick et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Rahman et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Rashid et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2013a\u003c/span\u003e). The creation of additional Protected areas and the growth of co-management systems to govern and manage these Protected areas are deeply ingrained in Bangladesh's forestry policies, which seek to cover 30% of state-owned forests by 2035 (BFD, 2016). Nevertheless, the frequent revisions to forest policies, rules, and acts over the protected areas in the past decade have clarified that the current policy and legal frameworks are insufficient to sustain such expansion plans (Rahman et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2016b\u003c/span\u003e). Through programs supported and aid from international donor organizations, the BFD is scaling up the current co-management model to new protected areas with minimal modifications (Rahman et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016a\u003c/span\u003e). Since there is no \"one-size-fits-all\" approach, replicating a co-management strategy that has appeared to be effective would not be the best option for all of Bangladesh's protected areas.\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe success of Protected areas must shift from number to quality while their rapid global expansion continues (Pringle, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Watson et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). It is critical to assess the influence and results of the current ones to enhance the protection area's effectiveness and quality in the future. There are a few studies that look at significant populations and worldwide scales to determine the effects and results of protected area conservation of biodiversity (Hajjar et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Oldekop et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Watson et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2014a\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2014b\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In-depth micro-level studies are equally as significant as global and national-scale research because they can thoroughly understand the effects of protected areas at the local and regional levels. The findings of this research may play a crucial role in closing the governance gap between the protected area's management plan and the practical reality gap. This study addresses the knowledge gap in evaluating the ecological and social outcomes of co-managed PAs at the micro-level. Specifically, we assess forest cover change, stakeholder perceptions, and ecosystem service trends in two co-managed forests referred to as the Nawabganj National Park and Dharmapur Sal Forest, Dinajpur District, located in the northern region of Bangladesh, where continued deforestation has been occurring for years (Islam et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e; Moslehuddin et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The results provide empirical evidence to inform forest policy, conservation planning, and sustainable land governance elsewhere in a similar geographic context.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Area Profile\u003c/h2\u003e \u003cp\u003eThis study was conducted at Dharmapur Sal forest, Birol in Dinajpur, which lies in the northwestern part of Bangladesh (88\u0026deg; 42'- 89\u0026deg; E, 25\u0026deg; 18'N-25\u0026deg; 29'N). The forest covers 1104.5 ha. The annual rainfall is 1726mm throughout the area, and Nawabganj National Park, Dinajpur, also lies in the northwestern part of Bangladesh (25\u0026deg;25'0.12\" N, 89\u0026deg;04'59.88\" E) (Islam et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019a\u003c/span\u003e; BFD, 2020). The forest covers 517.61 ha (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The land's topography is generally flat with a gentle southward slope. The \"Barind tract\" is formed on the old alluvium of the Pleistocene period. The general level of this tract is above flood level and intersected by numerous gentle depressions. The highest point in this tract does not exceed 20 feet above the surrounding land (Moslehuddin et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). All the areas were in designated compartments (permanent management units set by the forest department) under natural forest cover. The dominant floras are \u003cem\u003eShorea robusta\u003c/em\u003e and teak. There are \u003cem\u003ealso Gmelina arborea, Eucalyptus regnans, Syzygium cumini, Acacia auriculiformis\u003c/em\u003e, and a few types of Orchidaceae (Mukul et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Nath et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Wild animals include Bengal foxes, jungle cats, fishing cats, and snakes (Islam et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2019b\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDetection of Land Use and Land Cover Change\u003c/h3\u003e\n\u003cp\u003eThis study also uses spatial analysis to make the findings more comprehensive (Madnee et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Landsat images with 30m resolution from 1990, 2003, and 2022 were collected from the USGS Earth Explorer website (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These images were taken during the dry season (October, November, and December) to ensure minimum cloud cover and water level stability. Radiometric and atmospheric corrections are applied to eliminate potential inconsistencies in the data due to various atmospheric and geological differences. The geo-referencing accuracy of the 2022 image is improved with the help of ground control points and Google Earth images collected in the field in March 2023. Images are co-registered in ArcGIS Pro and are projected using 30m resolution and the UTM coordinate system (UTM-WGS 1984 Zone 46). Land use land cover (LULC) classification is done using the modified FAO (FAO, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) method and maximum likelihood algorithm, where classifications include barren land, encroached area/agriculture, forest, and waterbody (Nurrochmat et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The post-classification comparison (PCC) method was applied to analyze LULC change over time and the data was analyzed in Excel. Time series analysis was also done to find some important patterns of the land use/land cover changes (Madnee et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of Landsat Satellite image data used for the study\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSatellite Name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSensor ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRow / Path\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eData Acquisition Date\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eResolution\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLandsat 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138/42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 Oct 1990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSGS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLandsat 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138/42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 Oct 1990\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSGS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLandsat 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139/42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 Nov 2003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSGS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLandsat 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139/42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 Nov 2003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSGS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLandsat 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOLI_TIRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138/42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 Nov 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSGS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLandsat 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOLI_TIRS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138/42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e07 Dec 2022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUSGS\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eStakeholder Perceptions of Co-Management Outcomes\u003c/h3\u003e\n\u003cp\u003eThe study surveyed local stakeholders about their perspectives on conservation; who participated in protected areas (PAs) management (Engen et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The relationship between perceived risks to conservation values, prioritized management initiatives, and faith in PAs governance was examined, and it was determined whether these perceptions aligned with the stakeholders' chosen principal conservation strategy and their support for PAs (Engen et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eData were gathered through focus groups with members of several stakeholder groups, including local forest department officials, forest managers, and group leaders living within the national park. Altogether, four focus group discussions (FGD) were arranged. During these discussions, both the local experts and two of the authors participated in performing the scoring exercise. Before starting the participatory scoring exercise, a briefing was given to the local experts about each ecological integrity and ES component. Several field trips with the local experts were arranged to different LULC types of both forest areas to get an idea about the conditions of the different ES components before the interviews. Photographs of each LULC class were taken during the field trips and used during the participatory scoring exercise. Three FGDs were first conducted as a \u0026ldquo;warm-up\u0026rdquo; exercise of scoring before the final scoring. The last (i.e., fourth) FGD was then used for the final ES scoring. All methods were performed in accordance with the relevant guidelines and regulations and approved by the Research Ethics Committee of Hajee Mohammad Danesh Science and Technology University (HSTU), Bangladesh, in compliance with the Declaration of Helsinki (World Medical Association).\u003c/p\u003e\n\u003ch3\u003eCalculation process of Ecosystem Service Value\u003c/h3\u003e\n\u003cp\u003eIn this study, we referred to Costanza's ESV model to calculate the total ecosystem service valuation of the study area (Costanza et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1997\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) as well used in other studies (Zhao et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Arowolo A. O. et al., 2018; Yi et al., \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Akbera et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mamat, Halik, and Rouzi \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Uta et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Costanza et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Jalal et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) as follows \u0026ndash;\u003c/p\u003e \u003cp\u003e \u003cb\u003eESV\u003c/b\u003e \u003csub\u003e \u003cb\u003et\u003c/b\u003e \u003c/sub\u003e \u003cb\u003e=\u003c/b\u003e\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\sum\\:}_{\\text{i}=1}^{\\text{n}}{\\text{A}}_{\\text{i}}\\times\\:{\\text{E}\\text{S}\\text{V}}_{\\text{i}}\\)\u003c/span\u003e\u003c/span\u003e \u0026hellip;\u0026hellip;\u0026hellip; EQ. (i)\u003cb\u003eESV\u003c/b\u003e\u003csup\u003e\u003cb\u003e-1 ha\u003c/b\u003e\u003c/sup\u003e= \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\frac{{\\text{E}\\text{S}\\text{V}}_{\\text{t}}}{\\text{T}\\text{o}\\text{t}\\text{a}\\text{l}\\:\\text{a}\\text{r}\\text{e}\\text{a}\\:(\\text{i}\\text{n}\\:\\text{h}\\text{a}.)}\\)\u003c/span\u003e\u003c/span\u003e \u0026hellip;\u0026hellip;\u0026hellip;EQ. (ii)\u003c/p\u003e \u003cp\u003eWhereas;\u003c/p\u003e \u003cp\u003eESV\u003csub\u003et\u003c/sub\u003e​: Total ecosystem service value for the entire study area (e.g., Dharmapur or Nawabganj).\u003c/p\u003e \u003cp\u003eAi: Area (in hectares) of land use type iii (e.g., forest, waterbody, barren land, encroached area).\u003c/p\u003e \u003cp\u003eVi: Ecosystem service value coefficient per hectare for land use type, typically derived from previous studies such as Costanza et al. (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e1997\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eESV\u003csup\u003e\u0026minus;\u0026thinsp;1 ha\u003c/sup\u003e: Ecosystem service value per hectare for land use type.\u003c/p\u003e \u003cp\u003eESVi: Total ecosystem service value for land use type\u003c/p\u003e \u003cp\u003eEquation (i) adds the ESVs of all land use categories to determine the total value of ecosystem services provided by the entire landscape. Equation (ii) isolates the value of ecosystem services per unit area (hectare) for each land use type, useful for spatial comparison and scenario modeling. The change in the value of the ecosystem services was estimated by calculating the differences in the estimated values for each land-use type in 1990, 2003, and 2022.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eLand Use and Land Cover Change from 1990 to 2022\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe classified maps reveal significant temporal changes in land cover in both Dharmapur Sal Forest and Nawabganj National Park (Figs.\u0026nbsp;3 \u0026amp; 4). Between 1990 and 2003, both areas experienced a decline in forest cover and an increase in barren land. By 2022, forest cover showed substantial recovery; suggesting the effectiveness of co-management and restoration interventions. Water bodies remained relatively stable, while encroached areas slightly decreased. These findings are based on a consistent classification approach using Landsat data and maximum likelihood algorithms\u003c/p\u003e \u003cp\u003eTo ensure the reliability of the land use and land cover (LULC) classification results, an accuracy assessment was conducted using stratified random sampling and ground-truth data for the year 2022, complemented by historical imagery and ancillary data for 1990 and 2003. The results revealed high classification performance across all study years. The overall accuracy for 1990, 2003, and 2022 was 89.25%, 87.65%, and 91.45%, respectively. Correspondingly, the kappa coefficients (κ), which account for agreement beyond chance, were 0.864 for 1990, 0.843 for 2003, and 0.892 for 2022. These values indicate strong to almost perfect agreement between the classified maps and reference data. The highest accuracy in 2022 can be attributed to field-collected GPS points and high-resolution Google Earth validation. The consistent performance across all years confirms the robustness of the LULC classification and supports the validity of the temporal change analysis conducted in this study. The amount of transition in various land use land cover (LULC) categories from 1990 to 2022 in Dharmapur Sal Forest and Nawabganj National Park is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eThe amount of transition in various land use land cover (LULC) categories from 1990 to 2022 in Dharmapur Sal Forest and Nawabganj National Park.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eLand Use Land Cover (LULC) Categories\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e1990\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2003\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eComparative Change (1990\u0026ndash;2022)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eArea (ha)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eArea (ha)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eArea (ha)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eArea (ha)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eDharmapur Sal Forest, Birol, Dinajpur\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eForest Area\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e552.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e469.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e550.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEncroached Area\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e412.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e420.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e381.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-31.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBarren Land\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWater Body\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-16.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e996.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e996.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e996.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eNawabganj National Park, Dinajpur\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eForest Area\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e454.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e393.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e432.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-21.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEncroached Area\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBarren Land\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWater Body\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e532.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e531.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e532.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003eThe Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e presents land cover data for two forest areas, Dharmapur Sal Forest, Birol, and Nawabganj National Park, for 1990, 2003, and 2022. Changes in forest cover, encroached areas, barren land, and water bodies are noted. In Dharmapur Sal Forest, Birol, the forest cover decreased from 552.048 hectares in 1990 to 469.95 hectares in 2003. However, by 2022, forest cover will rebound, reaching 550.41 ha. This could indicate a possible restoration of forested areas after a period of decline. The encroached agricultural area experienced fluctuations but ultimately decreased from 412.58 hectares in 1990 to 381.47 hectares in 2022, possibly suggesting a change in agricultural practices or land use policies. Barren land in Dharmapur Sal Forest, Birol, increased notably from 7.55 hectares in 1990 to 101.08 hectares in 2003, decreasing to 56.69 hectares in 2022. This could be due to factors like deforestation or changes in land management. Water bodies remained relatively stable, with some minor fluctuations over the years. In Nawabganj National Park, forest cover decreased from 454.18 hectares in 1990 to 393.72 hectares in 2003 but increased slightly to 432.36 hectares by 2022. Encroached agricultural areas fluctuated, slightly increasing from 54.63 hectares in 1990 to 69.82 hectares in 2022. Barren land experienced a substantial increase from 17.35 hectares in 1990 to 85.83 hectares in 2003 before declining to 23.31 hectares in 2022. Water bodies saw small fluctuations over the years.\u003c/p\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eChange detection of land use and land cover\u003c/h2\u003e\n \u003cp\u003eThe analysis delves comprehensively into the intricate shifts in land cover percentages over successive periods within Dharmapur Sal Forest, Birol, and Nawabganj National Park. Both forest areas exhibit dynamic fluctuations, initially decreasing from 1990 to 2003 and rebounding by 2022. The forest cover in Dharmapur Sal Forest, Birol, dropped from 55.42% in 1990 to 47.17% in 2003, marking a reduction of 8.25%. A subsequent resurgence was observed, with forest cover ascending from 47.17% in 2003 to 55.25% in 2022, resulting in an augmentation of 8.08%. The encroached agricultural area, conversely, witnessed an incremental rise from 41.42% in 1990 to 42.24% in 2003, indicating a marginal increase of 0.82%, followed by a downturn to 38.29% in 2022, signifying a decrement of 3.95%. Barren land in Dharmapur Sal Forest, Birol, experienced a notable surge from 0.76% in 1990 to 10.15% in 2003, denoting an elevation of 9.39%. This trend shifted as barren land diminished from 10.15% in 2003 to 5.69% in 2022, revealing a reduction of 4.46%. Correspondingly, water coverage in Dharmapur Sal Forest, Birol, declined from 2.41% in 1990 to 0.48% in 2003, illustrating a contraction of 1.93%, and subsequently increased to 0.77% in 2022, marking a growth of 0.29%.\u003c/p\u003e\n \u003cp\u003eConversely, in the context of Nawabganj National Park, the forest cover dwindled from 85.34% in 1990 to 73.97% in 2003, signifying a decline of 11.37%, before reclaiming ground to reach 81.23% in 2022, reflecting an ascent of 7.26%. The encroached agricultural area in Nawabganj National Park declined from 10.26% in 1990 to 9.22% in 2003, marking a decrease of 1.04%, and then escalated to 13.12% in 2022, indicating an increase of 3.90%. Barren land exhibited a pronounced escalation from 3.26% in 1990 to 16.13% in 2003, portraying an increase of 12.87%, followed by a decrease to 4.38% in 2022, reflecting a reduction of 11.75%. Notably, water coverage in Nawabganj National Park maintained relative constancy at 1.27% throughout all three years. These meticulous calculations offer profound insights into the intricate fluctuations that underscore land cover dynamics over the observed years in Dharmapur Sal Forest, Birol, and Nawabganj National Park. The analysis unveils the dynamic ebb and flow in the composition of these forests, characterized by periods of both augmentation and reduction across varied land cover categories.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eSocioeconomic features of the Stakeholder\u003c/h3\u003e\n\u003cp\u003eThe Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e presents the characteristics of the study\u0026apos;s participants, non-participants, and stakeholders. The data was divided into various categories, and the percentages of respondents falling into each category are provided. The study involved 54 respondents, 21 participants, 27 non-participants, and six forest staff members. The participants engaged in a specific activity or program being studied, while non-participants did not participate. Forest staff refers to the employees or personnel associated with the forest area under investigation. The data highlights notable differences between the groups. While participants and non-participants exhibit variations in gender distribution, with 59% male participants and 74% male non-participants, forest staff exclusively comprises males. Education-wise, a higher percentage of non-participants (46%) have education below SSC level compared to participants (37%), whereas forest staff members are well-educated, with 67% having completed SSC to HSC. The income distribution reveals that most participants and non-participants have incomes below 100,000 Tk. Meanwhile, forest staff see a significant 67% with incomes exceeding 200,000 Tk. Proximity to the protected area (PA) shows that participants live mainly on the PAs boundary (37%), while forest staff reside outside the PAs. Finally, years of experience indicate that participants and non-participants possess similar experience durations, with forest staff members displaying varying experience levels.\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSocioeconomic Features of the stakeholder in Dharmapur Sal Forest, Birol and Nawabganj National Park, Dinajpur\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSelected Characteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eDescriptions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eRespondents (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParticipants\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-participants\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eForest staff\u003c/p\u003e\n \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt; SSC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSSC- HSC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt; HSC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eIncome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;100000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1000000\u0026ndash;2000000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;200000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInside PAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOn PAs boundary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOutside PAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eExperience\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u0026ndash;30 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;30 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eStakeholders\u0026rsquo; perception of outcomes of PAs Co-management\u003c/h3\u003e\n\u003cp\u003eTable \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e illustrates the diverse impacts of co-management on selected forest attributes, as assessed by Participants, Non-participants, and Forest Staff. A pattern emerges where co-management positively influences forest cover enhancement, evident in high percentages among all groups; 82% for Participants, 76% for Non-participants, and a remarkable 100% for Forest Staff. Contrarily, forest cover decreases register much lower percentages (Participants: 18%, Non-participants: 24%, Forest Staff: 0%). A similar trend is observed for the native tree population increase, with participants at 73%, non-participants at 66%, and forest staff at 69%. Conversely, the decrease in the native tree population appears at 27%, 44%, and 31%, respectively (Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eStakeholders\u0026rsquo; perception on outcomes of PAs Co-management in Dharmapur Sal Forest, Birol and Nawabganj National Park, Dinajpur.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eSelected Attributes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eImpacts of Co-management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eDiscussant (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParticipants (N\u0026thinsp;=\u0026thinsp;21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-Participants (N\u0026thinsp;=\u0026thinsp;27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eForest Staff (N\u0026thinsp;=\u0026thinsp;6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eForest Cover\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eNative Tree population\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eExotic tree population\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eNatural regeneration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAwareness on Biodiversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eWildlife Diversity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eHunting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eEcotourism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTimber Collection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eFuel wood Collection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eNTFPs collection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDecreasing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eEcosystem Service trend in Dharmapur Sal Forest, Birol, and Nawabganj National Park\u003c/h2\u003e\n \u003cp\u003eThe Fig. \u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e presents ecosystem service information for two locations, \u0026quot;Dharmapur\u0026quot; and \u0026quot;Nawabganj,\u0026quot; for 1990, 2003, and 2022. In 1990, Dharmapur produced an ecosystem service value of 93.05, whereas Nawabganj contributed a somewhat higher value of 122.11. By 2003, Dharmapur\u0026apos;s and Nawabganj\u0026apos;s ecosystem service values had decreased, with Dharmapur\u0026apos;s falling to 83.68 and Nawabganj\u0026apos;s falling to 113.94.\u003c/p\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe temporal shifts in land cover observed across Dharmapur Sal Forest, Birol, and Nawabganj National Park reflect the interplay between human-induced pressures and ecological processes. Anthropogenic activities particularly deforestation, agricultural expansion, and urbanization were the primary drivers of forest loss, while natural regeneration and conservation initiatives contributed to recovery in later decades (Asner et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Patel et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Noor et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Distinguishing human-induced land-use change from natural successional dynamics remains crucial to understanding forest transitions (Joshi et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Over the 1990\u0026ndash;2022 period, land cover fluctuated in response to policy interventions, community participation, and restoration projects, underscoring the adaptive nature of forest ecosystems within socio-ecological systems (ASEAN, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; FAO, 2010; Geist \u0026amp; Lambin, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). From the governance perspective, these dynamics illustrate that co-management frameworks can act as catalysts for forest recovery, provided they are embedded in participatory and adaptive mechanisms (Berkes, 2009; Ostrom, 1990; Plummer et al., 2012). The integration of local knowledge through participatory forest committees appears to have fostered stewardship and accountability, which are core principles of \u003cem\u003eadaptive co-management\u003c/em\u003e (Olsson et al., 2004). In this study, GIS-based evidence of forest cover increase in the 2000s and 2010s coincides with the institutionalization of co-management projects such as Nishorgo and CREL, suggesting that decentralized governance arrangements can positively influence land cover outcomes. This aligns with global findings showing that co-management enhances biodiversity conservation when local users are granted decision-making power and benefit-sharing mechanisms (Cinner et al., 2012; Sunderlin et al., 2005; Persha et al., 2011).\u003c/p\u003e \u003cp\u003eThe focus group results reveal exact social-ecological interactions within these frameworks. High participation rates in ecotourism (participants: 92%; non-participants: 87%; staff: 100%) and low engagement in hunting (participants: 16%; non-participants: 32%) suggest a shift in livelihood orientation from extractive to conservation-compatible activities. Yet, mixed outcomes for timber and fuelwood collection (24% and 3% among participants, respectively) indicate persistent livelihood dependence on forest resources. These findings demonstrate that co-management does not eliminate resource extraction pressures but rather reconfigures them within negotiated boundaries (Chakraborty \u0026amp; Joshi, 2018; Ghimire et al., 2015; Poteete \u0026amp; Ostrom, 2004). Effective governance therefore depends on continuous dialogue, enforcement, and benefit redistribution. Importantly, the findings contribute to broader theoretical debates by emphasizing the dual role of co-management as both a governance mechanism and a social learning process. The observed recovery of native species and natural regeneration reported by a majority of stakeholders illustrates how shared management can foster collective ecological literacy. This supports the proposition that co-management systems function best when they cultivate adaptive capacities and learning networks among stakeholders (Dietz et al., 2003; Pretty, 2003). However, the heterogeneity of responses among participant groups also indicates uneven perceptions of benefits and responsibilities, echoing global critiques that co-management success often depends on equity and institutional resilience (Agrawal \u0026amp; Gibson, 1999; Guti\u0026eacute;rrez et al., 2011).\u003c/p\u003e \u003cp\u003eThe recovery trends observed in this study resonate with international experiences. In Nepal, community forestry user groups have managed over two million hectares, reversing deforestation while improving livelihoods (Oldekop et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Similarly, Indonesia\u0026rsquo;s \u003cem\u003eHutan Kemasyarakatan\u003c/em\u003e program demonstrates how tenure security and capacity building can sustain forest recovery (Sahide et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The parallel with Bangladesh\u0026rsquo;s model is instructive: while legal frameworks exist to promote co-management, site-specific governance challenges such as overlapping jurisdiction and weak incentive structures must be addressed for lasting success. These lessons suggest that Bangladesh\u0026rsquo;s co-management framework is entering a \u0026ldquo;second generation\u0026rdquo; phase, where institutional maturity, ecological monitoring, and equitable benefit sharing are central to resilience. Ultimately, this study extends existing literature by empirically linking spatial forest recovery patterns with social governance processes, providing a rare longitudinal perspective (1990\u0026ndash;2022) on co-management effectiveness. By integrating GIS analysis with stakeholder perceptions, it demonstrates how hybrid methodologies can validate ecological outcomes while revealing governance dynamics. The results reinforce that sustainable forest management is not merely an ecological or technical challenge but a negotiated social process shaped by learning, trust, and policy coherence. Strengthening these feedback loops will be critical to scaling co-management across Bangladesh\u0026rsquo;s protected areas and contributing to global targets for forest restoration and biodiversity conservation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, the study comprehensively analyzes land-cover changes, co-management impacts, socio-economic characteristics, and ecosystem service trends in the Dharmapur Sal Forest, Birol and Nawabganj National Park, Dinajpur. The findings underscore the dynamic nature of these ecosystems and the importance of sustainable management practices. Both forest areas exhibit dynamic fluctuations, initially decreasing from 1990 to 2003 and recovering by 2022. The research provides valuable insights into forest management's complex interplay between ecological, social, and economic factors. The need for context-specific strategies, stakeholder engagement, and ongoing monitoring is emphasized to ensure the preservation of forest ecosystems and the delivery of essential ecosystem services.\u003c/p\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePolicy Recommendations\u003c/h2\u003e \u003cp\u003e Based on the results of forest cover change, ecosystem service improvements, and stakeholder perceptions, the following policy reforms and management guidelines are recommended for improving forest co-management in Bangladesh:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eEstablish a national framework for periodic forest and ecosystem service monitoring using remote sensing, GIS tools, and participatory methods.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAmend the Forest Act to define the rights, roles, and responsibilities of local communities and co-management committees in protected area governance.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDevelop location-specific co-management plans that reflect the ecological, social, and economic characteristics of each protected area.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eProvide training, capacity development, and financial incentives to local stakeholders for sustained participation.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eUse ESV data in national land-use planning, investment allocation, and conservation priority setting.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePromote income diversification strategies such as agroforestry, non-timber forest product (NTFP) harvesting, and ecotourism to reduce pressure on forests.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eEncourage collaboration between the Forest Department, Ministry of Environment, local governments, and NGOs for unified conservation planning and policy execution.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eImplement continuous education and outreach programs to raise awareness about the ecological and economic importance of co-managed forests among local communities and the general public.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest / Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval and Accordance with Guidelines\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Research Ethics Committee, Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur, Bangladesh. All methods were performed in accordance with the relevant guidelines and regulations and approved by the Research Ethics Committee of Hajee Mohammad Danesh Science and Technology University (HSTU), Bangladesh, in compliance with the Declaration of Helsinki (World Medical Association).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVerbal informed consent was obtained from all individual participants prior to the focus group discussions and interviews.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution statements:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization, Md. Manik Ali, Sudipto Saha Dipto; methodology, Sudipto Saha Dipto and Md. Manik Ali and Muhammad Madnee; software, Md. Manik Ali and Nazmin Akter; validation, Mahmuod Abubakar Bashir, Md. Farid Hasan, and Mst Mow; formal analysis, Md. Manik Ali, Sujan Kumar Shil and Md. Asif Adnan Prince; investigation, Mst. Mow; resources, Md. Shafiqul Bari; data curation, Mst. Mow; writing\u0026mdash;original draft preparation, Sudipto Saha Dipto ; writing\u0026mdash;review and editing, Md. Manik Ali\u0026nbsp;Muhammad Madnee, Mahmuod Abubakar Bashir\u003csup\u003e\u0026nbsp;\u003c/sup\u003eand Sujan Kumar Shil ; visualization, Md. Asif Adnan Prince and Sujan Kumar Shil; supervision, Md. Manik Ali and Md Shafiqul Bari; \u0026nbsp;project administration, Md. Manik Ali and Md Shafiqul Bari. All authors have read and agreed to the published version of the manuscript\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAgrawal A. Forests, governance, and sustainability: Common property theory and its contributions. Int J Commons. 2007;1:111. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.18352/ijc.10\u003c/span\u003e\u003cspan address=\"10.18352/ijc.10\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgrawal A, Redford K. Conservation and displacement: An overview. 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Land Use Policy. 2004;21(2):139\u0026ndash;48. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.landusepol.2003.10.003\u003c/span\u003e\u003cspan address=\"10.1016/j.landusepol.2003.10.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-environment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Environment](https://www.springer.com/44274/)","snPcode":"44274","submissionUrl":"https://submission.nature.com/new-submission/44274/3","title":"Discover Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Protected Area Co-management, Land-use Change, Ecosystem Services, Forest Conservation","lastPublishedDoi":"10.21203/rs.3.rs-8418868/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8418868/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Protected Area (PA) concept has contributed significantly to forest conservation worldwide and has also contributed to the expansion of forest cover. Co-management of PAs has emerged as a strategy to make forest restoration and biodiversity conservation more effective by encouraging the active participation of local people. This study analyzed the co-management effects of PA in two protected areas of Dharmapur Shal Forest and Nawabganj National Park in Dinajpur District, Bangladesh. Land use and land cover change were monitored between 1990 and 2022 using Landsat images. The study considered four main categories; forests, encroached areas, barren lands, and water bodies. The findings indicated that forest cover diminished in both forests between 1990 and 2003 but experienced a significant recovery by 2022. The expanse of Dharmapur Shal forest diminished from 552.05 hectares in 1990 to 469.95 hectares in 2003, then rising to 550.41 hectares in 2022. While the forest cover in Nawabganj National Park declined from 454.18 hectares to 393.72 hectares, it recovered to 432.36 hectares in 2022, demonstrating the hopeful effectiveness of co-management strategies. The Barren land initially increased and decreased in both areas, while the waterbody remained almost stable. Ecosystem service values (ESVs) related to carbon sequestration, biodiversity, and water regulation also improved. Stakeholder perception analysis, including forest officials and local communities, revealed strong support for co-management, citing enhanced forest cover, increased native species, and reduced illegal extraction. However, challenges remain in achieving historical biodiversity levels. This study highlights the potential of co-management in forest restoration and sustainable land governance in developing countries and provides evidence-based insights to inform future policy and planning.\u003c/p\u003e","manuscriptTitle":"Impact of Co-Management Strategies on Forest Ecosystems in Protected Areas of Bangladesh Using Remote Sensing and GIS Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 15:49:40","doi":"10.21203/rs.3.rs-8418868/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-23T10:54:48+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-19T10:06:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-17T07:40:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-14T13:07:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"298485379131416947661861353968472183526","date":"2026-02-09T11:43:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"127350042540705462181431215125379030195","date":"2026-02-08T09:12:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"337326830391214132133073182273501518259","date":"2026-02-06T17:36:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"254697278414005170765959062139477304549","date":"2026-02-06T12:54:24+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"36934502637087889335610638707185630154","date":"2026-02-06T10:17:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"235221566824133030292079167060886396065","date":"2026-02-06T09:25:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-13T11:29:01+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-12T05:04:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-07T18:15:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-07T15:31:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Environment","date":"2026-01-07T15:25:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-environment","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Environment](https://www.springer.com/44274/)","snPcode":"44274","submissionUrl":"https://submission.nature.com/new-submission/44274/3","title":"Discover Environment","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ed9e233b-24c1-4fb3-b2e9-b564c24bfd0b","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-25T05:25:42+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 15:49:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8418868","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8418868","identity":"rs-8418868","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}