Conducting monitoring and surveillance in wildlife (both healthy populations and those showing signs of disease) and routine serological testing for exposure to pathogens frequently shared with livestock as well as more in depth diagnostics e.g. PCR/ NGS on sick/ dead animals support comprehensive understanding of the circulation of pathogens in these populations, geographic and temporal distributions and time-lines of exposure and non-exposure of different populations. Integration of this data with livestock surveillance data contributes to understanding of the epidemiology of diseases and the dynamics of disease outbreaks, including the potential source, to implement effective science-based control strategies.

Building partnerships across the emergency management, animal health and environment/ wildlife sectors is an important first step for planning and implementation of wildlife surveillance to ensure results are used to guide science-based policy and disease control mechanisms. Convening multi-sectoral meetings to open discourse and share information on the challenges and opportunities to monitoring and management of disease at the wildlife-livestock interface, and to develop smooth communications and trust between and across sectors as well as multi-sectoral surveillance and response networks is critical.

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.

The mid term review examined the success of management plan in the middle of its implementation period. It reviewed the implementation progress of the action plan and the effectiveness of the outcomes. A detailed analysis of capacity for implementation and protected area management was carried out, as this would always be a major challenge. The analyses included extensive engagement with authorities and land managers, to gain open feedback. They provided feedback on the challenges and their resources, knowledge and experience, including where they fell short to achieve implementation. They also had the opportunity to suggest how we could better capacitate them for the remainder of the implementation period. 

Since 2014, PODD has been actively detecting abnormal health events and preventing outbreaks in Thailand with incredible support from both local governments and local communities. While PODD relies on software, the success of the project largely depends on the real-time data coming from our disease detectives in the field. These livestock owners are incentivized to provide health officials with direct disease data, since their own livelihood depends on the health of their animals.

Although there was a managing agency, the governance structure needed broader formal input, especially for a decision making mechanism. 

So a management committee, including the management authority, a water authority, local government, community representatives and regional government was initiated. 

The management committee has a chair, who has the responsibility to convene regular contact and meetings, and also special meetings to address issues or make decisions on management as the requirement emerges. 

For the first ten years after protected area designation, the management authority was in place but operating without a management plan. They did not have the internal capacity or knowledge to develop a plan that addressed the requirements for management of a protected landscape. 

The management plan was developed to provide the objectives, activities and indicators for measuring the outcomes. The plan included a ten year program of activities, with opportunity for a review and amendments after five years. 

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.