Consultant Scope of Work - District FLR data collection and verification

SCOPE OF WORK - District FLR data collection and verification Consultant Scope Malawi is targeting to restore 4.5m hectares of degraded forests by 2030. Convenient and sustainable monitoring tools are critical in monitoring progress towards such goals and targets. Similarly, enhancing capacity to utilize such tools is highly critical. Modern Cooking for Healthy Forests (MCHF), a project co-funded by USAID and UKaid, is seeking a consultant to lead the capacity building, data collection and reporting process of Forest Landscape Restoration (FLR) progress. The Consultant(s) will collaborate with the Deputy Chief of Party, as well as Objective 2 and 4 leads, to facilitate the integration of district FLR data into the Forestry Data Management System (FDMS) under the Forest and Landscape Restoration Monitoring Unit (FLMU) or National Monitoring Unit (NMU). The consultancy will build upon existing initiatives by engaging in a consultative process through MCHF with; the NMU; FLR District Council Focal Points; District Forest Officers; and District Monitoring and Evaluation (M&E) Officers. Recognizing the existing gaps in the data collection and capacity at the local level, particularly regarding Forest Landscape Restoration (FLR) activities, MCHF has developed standardized multiple data collection templates/tools for forest and landscape monitoring. Through the utilization of standardized templates and a consultative approach, the aim is to enhance the quality and usefulness of data, thereby supporting evidence-based decision making for sustainable forest management and landscape restoration. The consultancy will leverage these data collection tools to support the development of comprehensive, quality-assured data. This process will enhance the utility of the collected data by incorporating geospatial specificity and implementing quality assessment and control measures. The Consultants(s) will play a pivotal role in facilitating coordination, information sharing, and capacity building among key stakeholders. By working with MCHF objective 2 and 4 leads, they will contribute to strengthen the overall monitoring and evaluation framework for the project, enabling informed decision-making and ensuring the success of forest and landscape management initiatives. The Consultant(s) will therefore work on the following tasks: Build on the FLR data collection tool and engage district focal points in reporting FLR implementation Conduct a training session on data collection for forest landscape restoration as well as NMU data needs, to ensure participants understand data reporting requirements and timelines. Facilitate collection of spatially explicit FLR data in MCHF target districts - ensuring the inclusion of geospatial information (where available). Suggest improvements to the data collection process, tools, and templates for data management needs, once the current tools are validated by key stakeholders, and district officers. Period of Performance: Two months full time starting June 2023. Specific Deliverables: Conduct district-based orientation with selected district council staff on FLR data collection needs, requirements and timelines. Collect and collate all the initial reporting data from MCHF target districts. Conduct training/workshop in Lilongwe for selected district-level staff, together with the NMU, to assess and confirm evidence (geospatially) of the FLR implementation. Support the NMU and MCHF to brief district councils and relevant stakeholders in MCHF target districts on the results of FLR data collection and verification. Prepare a concise summary report (no more than 10 pages) highlighting the data collection process, tools, challenges and recommendations to support the NMU to scale up district level data collection to all the 28 districts. Consultant Qualifications and Background Qualification: Bachelor’s degree in Natural Resource Management, forestry, or related environmental field. At least 3 years of experience in data collection data processing and analysis; including relevant experience in forest landscape restoration. Practical experience in the development and handling of Data Management System Requirements: Essential that the Consultant(s) are either from Malawi or possess a deep understanding of the local context to effectively perform the task. Commitment to travel to MCHF project districts to facilitate discussions with district stakeholders. Mandatory consistent and reliable access to highspeed internet to ensure timely interpretation of the images where necessary. Prior experience in forest landscape management, monitoring systems, data collection and analysis. Consultant should possess necessary technical expertise to effectively carry out the tasks. Consultant(s) should have an understanding of forest monitoring methodologies, data collection techniques, and ability to work with spatially explicit data. The consultant (s) should be flexible and adaptable to changing project needs and requirements. The consultant should be able to adjust the approach based on feedback and emerging priorities. The consultant should be availability for weekly progress meetings. The consultant should adhere to clear timelines and demonstrate the ability to work independently. Skills and Competence: Familiarity with FLR process and data needs in Malawi. Experience with GIS tools and platforms for forest monitoring. Excellent computer skills in word-processing and spreadsheets. Skills in delivering effective training sessions and facilitating discussions with diverse stakeholders. Skills to clearly communicate project data needs and encourage participants to contribute their data. Experience with data collection and quality control procedures. Strong communication skills, both interpersonal and written in English and Chichewa Winrock is an equal opportunity employer. We are committed to providing equal employment opportunity for all people and value diversity and inclusiveness. Winrock recruits, employs, trains, promotes and compensates regardless of race, color, religion, sex, gender, gender identity, gender expression, sexual orientation, national origin, ancestry, citizenship, age, physical or mental disability, medical condition, family care status, or any other basis protected by law. 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