During the implementation of the intervention, the project team conducted the self-assessment that helps determine whether an intervention is in adherence with the IUCN Global Standard for Nature-based Solutionsᵀᴹ. The assessment provided information about the intervention’s strengths and weaknesses and helped derive concrete recommendations and corrective actions for future interventions. Two criteria were deemed insufficient. Criterion 3 (biodiversity net-gain) fell short, because the analysis of the biodiversity benefits achieved through this intervention were largely based on a desk review of existing literature and information rather than a specific assessment, monitoring framework or thorough and collective effort with key informants and stakeholders. Criterion 6 (balancing of trade-offs) was also deemed insufficiently addressed. While there was a reported willingness from the Revolutionary Government of Zanzibar to consider relevant trade-offs, the limits of these trade-offs and associated safeguards were not clarified. In addition, while provisions on the rights, usage of and access to marine and coastal resources for mariculture are in place, further information on how this is applied in practice is required.

Camera trapping allows non-invasive surveys of wildlife throughout the protected area, providing new insights into hotspots of rare and threatened species, while also providing information on which locations contained the most species targeted by hunters. Systematic camera traps were set in either fine-grid (smaller areas with 1-2 km spacing in between stations), or course-grid (full protected area coverage with ~2.5 km spacing between stations) designs, with stations that contain 2 or more cameras spaced about 20 m from one another. Cameras trapping systems were left in the field for ~3 months for each sample session to meet the closure assumption; fine grid designs for two locations were repeated 2 years apart, the course grid is intended to be reproduced in 2023 (5 years apart). Systematic cameras were set and microhabitat data were collected at each station site following protocols from Abrams et al (2018). 

References

Abrams, J. F., Axtner, J., Bhagwat, T., Mohamed, A., Nguyen, A., Niedballa, J., ... & Wilting, A. (2018). Studying terrestrial mammals in tropical rainforests. A user guide for camera-trapping and environmental DNA. Berlin, Germany: Leibniz-IZW.

Our anti-poaching teams have improved the workflow of detecting and pre-emptively stopping offenders who illegally enter the protected forest areas by deploying PoacherCams -- automated detection systems that operate via camera traps and artificial intelligence classification of humans, animals, and vehicles (Figure 3). PoacherCams are strategically placed at entry points into protected forests adjacent to local villages and access trails. When the cameras detect a human entering the park at PoacherCam installation sites, the site manager will receive a notification on their Smartphone of the threat and location. The manager will then deploy a mobile unit (forest rangers) to survey the area or document the entry and exit activity of the offender over time and make an arrest. Our system also has a dashboard for record-keeping purposes and note taking which forestry law-enforcement can refer to later when issuing penalties and following up with their issuance with commune-level law enforcement. Through extensive patrolling efforts, we have identified numerous central access points from local villages into the protected forests and set PoacherCams to monitor them and take action where needed.

The Spatial Monitoring and Reporting Tool (SMART) is a both a software and a framework that allows forest rangers and anti-poaching patrols to collect geospatial data on their smart phones (via the SMART mobile app), which acts as an advanced handheld GPS. When traps, illegal encampments, animals, or violators are located, the patrol will make a record using the app’s customized “data model” (a customization of the application that creates specific drop-down lists, and decision trees). The SVW data model is based on Vietnamese forestry law, so when any technical gaps are identified in the data model in terms of arrest procedures, non-standard violations, or priority species listed in legislative decrees, it can directly inform and improve policy.

Once data has been collected by patrols on their smart phones, the patrol data (paths walked, km travelled, time spent on patrol, and data recorded) will upload automatically to SMART desktop. This is where managers can evaluate poaching hotspots to apply pressure, and also allows them to monitor the effectiveness of the patrols themselves. With each new data input, data managers are able to adapt to the situation and adjust their team and patrolling regimens accordingly.

Anti-poaching (AP) teams are hired and funded under Save Vietnam's Wildlife, and approved by protected area managers where they sign a joint contract between the two. They undergo approximately one month of training in Vietnamese forestry law, species identification, self-defense, field training, first aid, and using SMART. 

AP patrols stay with forest rangers for 15-20 days of patrolling at various ranger stations each month, and an assigned Data Manager typically processes, cleans, analyzes and reports SMART data for all patrols to the park director and SVW coordinators. At the beginning of each month, a SMART report is generated by the data manager; based on the intelligence from this report, a patrol plan will be discussed with the ranger and anti-poaching members, and then submitted to the protected area director for approval; mobile units are on standby and led by forest rangers to rapidly respond to any emergencies, locations outside of planned patrol areas, or situations accessible by road.

Rangers were trained to use SMART mobile through vertical knowledge transfer in the field, and by the end of 2020, 100% of the forest rangers (73 people) were all effectively using SMART, increasing patrol data coverage across the entire protected area (Figure 1).

The agreements are aimed at preserving the integrity of the SFFG, through the release of transformed areas and the implementation of active and passive restoration processes, in order to achieve the recovery of degraded land cover and contribute to the maintenance of natural areas and the good living of the community.

To achieve the implementation of the ecological restoration agreements, it was necessary to carry out out outreach activities and socialization of the process with the 23 prioritized peasant families and also to collect information according to the guidelines of participatory ecological restoration, which allowed the construction of the technical annexes and the content of the agreements.

Its purpose is to involve local communities in the restoration process, depending on the socioeconomic environment prevailing in the area, with special attention to the aspirations of local communities in terms of the future they want for the space they inhabit. Therefore, in the implementation of the restoration strategy, local communities made up of children, youth and adults were involved in activities such as:

(i) Identification of the areas to be restored.

ii) Construction of community nurseries for the propagation of high Andean forest species. iii) Participation in the implementation of isolation in areas under pressure from agricultural activities, in order to encourage the use of the region's own natural resources that contribute to valuing the existing biodiversity and ensure the long-term continuity of the project, taking into account the important knowledge that the community has about their region, its history of use, the location of the species and in some cases their propagation.

The purpose of identifying the areas to be restored is to determine the number of hectares in which active restoration actions should be implemented (which consists of direct human intervention on the structure and characteristics of the degraded ecosystem, in order to replace, rehabilitate or restore it to ensure the existence of a structured and functional ecosystem) and passive restoration (focused on eliminating or minimizing the disturbances causing the degradation, leaving the degraded ecosystem to recover its structure and functionality by itself).This process was carried out through the methodology of observation and participatory research, which consists of making field trips with some members of the community, to take geo-reference points with the GPS, to subsequently build the polygons and calculate the area to be restored, which comprises 196.2 hectares. Parallel to this activity, a diagnosis of the conservation status and composition of the plant species present in the area is made to determine the degree of intervention to which the ecosystem has been subjected and thus make the decision on what type of restoration will be implemented.

Community buy-in and participation are key building blocks for project success and sustainability. These depend in large measure on community awareness of the project itself, as well as its intended benefits, beneficiaries, and long-term viability. Raising awareness around new protected areas, revised laws/regulations, community conservation agreements, etc. is also a key element of effective enforcement and interdiction, and assuring community adherence to conservation plans.

The overall project objective is "to facilitate a transformative shift towards sustainable land and forest management in the forested landscape of Savannakhet Province in order to secure the critical wildlife habitats, conserve biodiversity and maintain a continuous flow of multiple services including quality water provision and flood prevention." This transformative shift to sustainability is predicated on the provision of adequate alternatives to unsustainable resource use. Previous unsustainable usages of the project's forested landscapes (e.g. logging, poaching) will not cease unless replacement livelihood activities provide an economic benefit and improve income generation for participating villagers.