To enable automatic and instant biodiversity impact assessment enquiry, the BiA tool has been developed to facilitate enquiry services for land planners and other interested parties via Azure platform. The BiA tool works by overlaying the enquiry site or region (or existing construction projects) with multiple geographic layers including species distribution and protected area range to investigate if the site or region is within certain distance (e.g., 3 km, 5 km) from and may cause impact on endangered species habitat and/or protected areas. The assessment reports illustrate ecological and environmental risks of construction projects for decision-makers and could hopefully promotes them to take biodiversity into consideration.
A brief timeline of the BiA tool:
Apr-Jun 2020: team formation, requirement communication, system development plan
Jul-Sept 2020: tool development
Oct 2020: trial test, application and dissemination
(in preparation) Apr-Sept 2022: system upgrade
Years of data collection accumulation and constant thinking of data application approaches.
Theoretical & technical basis accumulated from long-term research and conservation practice.
Promotion of the BiA tool to its potential users, like governments, investors, and enterprise.
Keeping track of tool operation and user feedback to devise further upgrade of the tool.
Data application is the foremost step in the whole data workflow, where the data turns into valuable information for stakeholders. Effective data application reports should bear the audience in mind (e.g., being concise and focused).
The complete of development and releasing is not the last step for a tool. Finding potential users and persuading them to use the tool is also very important. A tool has to be used to provide the most value.
Spatial and temporal campaign page displaying gingko investigation results
Shan Shui Conservation Center
Species records in Yunnan province
Shan Shui Conservation Center
[GIF] Home page and spatial campaign page (e.g., squirrel investigation results)
Shan Shui Conservation Center
[GIF] Spatial and temporal campaign page (e.g., gingko investigation results)
Shan Shui Conservation Center
[GIF] Data visualization on different administrative division levels (e.g., Zhejiang Province)
Shan Shui Conservation Center
During nature watch campaigns, citizen scientists are invited to observe and record wildlife timely, which not only strengthens the connection between citizens and nature but also serves as a promising species distribution data source. Species record data collected by citizen scientists via online questionnaire automatically flows into the visualization platform database (after data cleaning and manually periodically check) and turns into intuitive and attractive visualized charts and maps (two types: spatial, spatial and temporal) via Power BI. The platform, with both web and mobile version, provides real-time feedback to citizen scientists’ nature watch efforts, boosting their sense of accomplishment and motivating their future participation in nature watch activities. Moreover, since the platform integrates multiple nature watch campaigns with links to web articles about specific analysis of each campaign, it offers a broad range of biodiversity knowledge and enables “virtual nature watch” for citizens to get to know wildlife in other regions.
A brief timeline of the platform:
Jan-Feb 2021: form team, analyze analysis, make blueprint
Mar-Jun 2021: develop database and platform
Jul-Aug 2021: trial test
Sept 2021: go live and promotion
A well-designed data-collection questionnaire and automatic data cleaning mechanism to ensure data quality and a manually periodically check (normally once a season) to ensure data reality.
Visualization methods selection and aesthetic design with the engagement of citizen scientists.
PowerBI technology.
Citizen scientist WeChat community operation and maintenance.
As a public outreach product, it would never be too much for polishing contents and aesthetic design to make the platform user-friendly and attractive.
Engaging users in the planning stage and collecting their thoughts is very helpful for identifying user needs.
Questionnaires are needed to be well-designed and citizen scientists are needed to be well-trained before recording data. Otherwise, it’s easy to cause data loss.
AI detected camera trap image: red fox in the Sanjiangyuan region
Shan Shui Conservation Center
AI detected camera trap image: snow leopard in the Sanjiangyuan region
Shan Shui Conservation Center
Community-based camera trap monitoring assistant app
Shan Shui Conservation Center
Camera trap data management system: species identification page
Shan Shui Conservation Center
To accelerate camera trap data workflows, an online data management system along with app-based tools and AI image recognition is being developed supported by technical partners, which consists of:
Community-based camera trap monitoring assistant app: the app allows local monitors to automatically record the time and GPS location of camera trap setup/pickup, saving the cumbersome process of collecting data from local monitors and manual data entry. (blueprint: Jun 2019, development: Oct 2019-Feb 2020, trial and use: Mar-Oct 2020)
AI image recognition models: AI models help detect animals and identify species in camera trap photos, which greatly reduce the number of photos that need human identification and enhance data processing efficiency.
A series of AI models has been trained and/or tested with technical partners, including PU & PKU ResNet18 model (2018), MegaDetector (test only, 2020), MindSpore YOLOv3 model (2021).
Online data management platform: camera trap information collected via the app along with photos are upload to a structured cloud database. The data management platform not only supports species identification via AI and human, but also enables global data search and statistics reports. (blueprint: Apr-Aug 2021, development: Sept 2021-Jun 2022, trial and use: Jul 2022)
A systematic review of the current camera trap data workflow and translating into technical system development needs
Open-source and good-performing camera trap image AI recognition models
Cloud resources for AI computing, data storage, etc.
Rounds of trial use and feedback to fix bugs and improve the usability of the system
Rome was not built in a day. Due to time and resource constraints, we have to divide the system into different modules and develop modules step by step. We believe that each module itself can enhance one or more steps in our workflow and have benefited from modules before they are incorporated into the full system. Yet it is important to have a big-picture perspective in the beginning and make long-term plans for the final system integration.
A system cannot be perfect from the start. When the app first came out and put into use in one community, it did not work as we expected and local monitors reported various types of bugs. We collected and analyzed the feedbacks to improve the UI-design and functionality of the app.
Program personnel visited villages in areas considered at-risk for Ebola virus outbreaks. This engagement helped to identify community interest in contributing to animal mortality reporting and assess the potential role of hunters in the network. While researchers and ecoguards initially provided some reports of carcasses, the majority of reports were ultimately received from hunters, allowing for more focused engagement of this demographic group. In addition to reporting, outreach was conducted to reach hunters and communities in several ways to support awareness of risk reduction strategies. For example, in the Étoumbi region, the Field Veterinary Program provided outreach education on Ebola and livestock husbandry to the Étoumbi Hunters’ Association, as well as hunters and other villagers of Mbomo and Kellé. Communities around national parks (Nouabalé-Ndoki and Odzala-Kokoua) were engaged, and visual posters and books were also provided to a village nurse for further dissemination.
Long-term efforts in the region fostered trusted relationships with the community that likely facilitated successful engagement and participation.
Sensitivity to the needs and priorities of local stakeholders, including food security and cultural traditions, promoted practical solutions that supported buy-in and uptake.
The reporting process established clear channels for information flow, minimizing the burden for community participants providing reports while ensuring information was communicated from local to national levels.
This program was initiated in 2005. There may be updated regulations regarding hunting and other subsistence or commercial use of wildlife in the region that could affect practices, and additional technologies (e.g. vaccination) are now available that could change the management strategies for humans and potentially wild animals in the event of Ebola virus or other disease detection. However, the program reinforces the utility of locally-relevant approaches and solutions, as well as the role of involving stakeholders that may be perceived as far outside of the conservation or public health sectors. In this case, hunters and community members living in Sangha district were among those at greatest risk of exposure to infection from handling carcasses, making their awareness and engagement in risk reduction practices critically important. Given the importance of food security and cultural traditions, top-down approaches were and likely still are unlikely to be effective, instead requiring stakeholder engagement and locally-accepted solutions.
Information Flow, Animal Mortality Monitoring program
WCS
Components of the system involved mortality reporting by hunters and community members, investigation of reports by veterinarians trained on specimen collection and handling protocols, specimen transport to national laboratories, and laboratory screening for disease diagnostics. Each of these involved specialized inputs, but the coordination between entities created the system. Information management and communication were conducted throughout the process. A Carcass Data Collection and Reporting Protocol was integral to the process, ensuring consistent reporting.
A local team, supported by a global program, ensured continuity of the broader Animal Mortality Monitoring Network and technical expertise to develop and implement disease investigation protocols
Full integration and support of Congolese government officials from multiple ministries helped prioritize the animal-human link for public health and conservation outcomes
Availability of functional national and international laboratories and the ability to move specimens rapidly, including from remote areas, supported diagnostics in endangered species
In this setting, hunters and some community members were the key eyes on the ground for wild animal mortality detection, having some of the only human presence in forest areas where carcasses may degrade rapidly, providing a limited window for detection and investigation. While the overall Animal Mortality Monitoring Network included a broader scope of reporting, only reports meeting certain criteria (such as being a great ape species, the extent of carcass degradation, and other factors) prompted disease investigation, keeping the scale of the program feasible and cost-effective. Unfortunately, despite its demonstrated value, sentinel detection in wild animals is not routinely a formal part of public and animal health surveillance in many parts of the world, missing a critical source of potential information that could promote early warning for disease threats in humans and other species. Training was also an important component of the project, including on biosafety protocols for safe disease investigation and diagnostic screening.
Coordination Platform for Sustainable Pasture Management
A Pasture Coordination Platform was organized in Armenia as a horizontal management network among relevant stakeholders on national and sub-national level. Each party is represented by a spokesperson, who coordinates the functions of the party within the Platform and ensures information flow. A secretariat ensures the operation of the Platform. The rationale for creation of the Platform was the need to promote effective cooperation, exchange of information, as well as coordination of activities among the projects implemented in Armenia, focusing on sustainable management of natural fodder areas.
Since 2018 the Platform has evolved and now more than 10 organizations, institutions, projects and public administration bodies are involved in the Platform’s activities, aiming to ensure viability of programs and investments in the area of animal farming, increase economic opportunities of communities and support income growth of rural residents in Armenia. Key objectives of the Coordination Platform are:
Coordination, exchange of information exchange and experience, identification of potential cooperation areas
Implementation of joint projects, activities
Advocating and supporting development of relevant state policy and legislation promoting sustainable use and management of natural fodder areas
The platform has a clear aim: "to improve the situation/ livelihood of the rural population which depends on natural fodder areas while sustainably using and conserving these natural ecosystems”.
The need for coordination, cooperation and exchange was felt by parties both from government as well as non-government organizations.
A memorandum was officially signed to establish the platform.
All members have clearly distinguished functions.
Active participation of the community stakeholders in decision making and coordination of the local projects was crucial. Placing the local working groups in charge of the local implementation not only generated a high level of ownership of the project and ensured the engagement of the community.
The coordination with other development organizations on the local scale was a key factor. The harmonization of these different local interventions resulted in a comprehensive, positive change for the communities. Each intervention was complimented by the others and would not have achieved the same results as an isolated activity.
Based on the memorandum of understanding, the common interest and need of all stakeholders in the platform to cooperate increased their commitment and ensured the continuity of the process.
Multi stakeholder advisory bodies face high risks from unforeseen changes in governmental institutions or even within their own parties. The meticulous documentation of agreements and activities has proven to be an important measure for dealing with this risk.
Maintaining pastures as a natural resource is easily to been done by the application of GIS and remote sensing tools to develop accurate classification maps, e.g. pastures, hay meadows, grassland. The combination of digital data and spatial technology enables detailed and useful monitoring of aboveground green vegetation biomass and grassland composition. Besides, resources and attributes can be monitored for knowledge management and long-term decision planning.
Mapping of pasture/ grassland ecosystem services and understanding of its contribution to human well-being
Facilitate regular monitoring at the management level
Short-term study of the positive and negative effects on pasture or grassland areas
Existence of relevant legal bases and close involvement of relevant bodies in the planning process
All factors that may affect pastures should be identified as spatial data
Mapping and monitoring changes in grassland vegetation cover is essential to understand grasslands dynamics
Reliable monitoring of changes in vegetation cover in grasslands is crucial for accurate and sustainable land management
Gathering more field/ ground truthing data was one of the important notes
It is vital to test and demonstrate different geospatial analyses to showcase what measures have the most impact on which erosion/degredadion situations and foster understanding for the solutions.
