Consultant - Statistical Analyst for Analyzing the consumption of Wild Meat in Central Africa

Reference number: 2143
Job status: In-progress
Job category: Consultancy
Duty station: Home-based
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CIFOR-ICRAF
The Center for International Forestry Research (CIFOR) and World Agroforestry (ICRAF) envision a more equitable world where trees in all landscapes, from drylands to the humid tropics, enhance the environment and well-being for all. CIFOR and ICRAF are non-profit science institutions that build and apply evidence to today’s most pressing challenges, including energy insecurity and the climate and biodiversity crises. Over a combined total of 65 years, we have built vast knowledge on forests and trees outside of forests in agricultural landscapes (agroforestry). Using a multidisciplinary approach, we seek to improve lives and to protect and restore ecosystems. Our work focuses on innovative research, partnering for impact, and engaging with stakeholders on policies and practices to benefit people and the planet. Founded in 1993 and 1978, CIFOR and ICRAF are members of CGIAR, a global research partnership for a food secure future dedicated to reducing poverty, enhancing food and nutrition security, and improving natural resources.

Overview

Wild meat has long been used as a source of food and income by many communities across the tropics. Recently, however, growing human populations and increasing commercial trade to urban markets have driven up demand for wild meat products and led to unsustainable levels of wildlife harvesting in many tropical regions. Despite the importance of wild meat as a food source for many rural communities, and the impacts of overhunting on many species and ecosystems, we still have major gaps in our understanding of wild meat consumption. Many studies over the last few decades have documented the consumption of wild meat by rural communities and town and city dwellers around Central Africa. While these studies have given us valuable insights into the drivers, uses and users of wild meat, taken on their own they provide only localized snapshots. However, combined they can provide a powerful evidence base for policymakers, practitioners, researchers and civil society. The WILDMEAT project (http://www.wildmeat.org), in collaboration with the EU-SWM project (https://www.swm-programme.info/), has been collating site-level consumption data from available studies in a standardized format, and has available data for over 100 sites across Central Africa. A unique time-series dataset is also available at a national level for Gabon because of long-term partnerships between the Institute for Tropical Ecology Research and the University of Stirling since 2001. These national and regional-level datasets will form the basis for this project, which will model the levels of wild meat consumption regionally across Central Africa and the correlates of this consumption, as well as investigate changes in consumption over time at a national scale in Gabon. The project is a collaboration between Sustainable Wildlife Management (SWM) (including CIFOR, CIRAD, WCS and FAO), WILDMEAT and the UKRI TRADE Hub. It aims to significantly increase our understanding of the consumption of wild meat across communities in Central Africa, both for rural and urban consumers, creating the first regional estimate of consumption rates and investigating the key correlates of these rates. In addition, the project will investigate how consumption patterns are changing over time, and how this may influence the sustainability of wild meat use, using Gabon as a national case study. These results will be used to inform national and international policies on wild meat; for example, directly reporting results to government partners in Gabon.

Duties and responsibilities

?1) ???Identify, collate and enter further consumption datasets into the WILDMEAT database:?

• Use a systematic survey approach (using online library searches, online survey tools and outreach to data providers via email, amongst others) to identify any further consumption datasets not already housed in the WILDMEAT database;
  
• Convert all identified datasets (including those already identified by WILDMEAT but not yet entered) into the standardized WILDMEAT data format, conducting rigorous data checking at all stages.
  

2) Model consumption rates across Central Africa and test hypotheses and scenarios developed with project partners. The consultant will use appropriate statistical models (this could use Bayesian or frequentist models; to be discussed with the consultant at the start of the project) to analyse wild meat consumption rates across Central Africa. This will include (but not be confined to) an analysis of how consumption rates vary:

• By species and/or taxa;
  
• By key demographics (i.e., variation in rates by wealth, education);
  
• Spatially (i.e., how rates vary across the Central Africa region, and how this might by correlated with settlement type, habitat, remoteness, market access etc.);
  
• Temporally (if possible, given the data available – whether consumption rates are changing over time once the influence of other correlates are accounted for).
  

3) Using the analyses conducted in (2), create estimates of current wild meat consumption rates across Central Africa, and model how these rates might be expected to change under different scenarios of economic growth and demographic change.

4) Conduct steps 2 and 3 for a national case study (Gabon), focusing on investigation of changes in consumption rates over time (2001–2021).

5) Write up results as at least two peer-reviewed papers appropriate for submission to high impact journals.

6) Write up national results (Gabon) as a policy brief for the Government of Gabon, and regional results as a policy brief for an international audience.

Education, knowledge and experience

• PhD in statistics or a related field such as ecology, conservation biology or sustainable development. If the candidate’s PhD is in statistics, experience in a related field such as ecology, conservation biology or sustainable development is preferable but not required. Show demonstrable experience of applying advanced statistical approaches (such as Bayesian hierarchical models) to complex datasets;
• Have a strong publication record, demonstrating their application of advanced statistical approaches;
• Have experience of working effectively within a research team, and demonstrate good interpersonal skills;
• Fluency in English, both written and oral. Fluency in French is preferable.

Terms and conditions

• This is a full-time consultancy position.
• Period of the consultancy is expected to start in January 2022.
• The duty station: Home-based To apply, please visit our career site at: https://www.cifor.org/careers To learn more about CIFOR-ICRAF, please visit our websites at: https://www.cifor.org and www.worldagroforestry.org CIFOR is an equal opportunity employer. Staff diversity contributes to excellence.

Application process

The application deadline is 23 Oct-2021
We will acknowledge all applications, but will contact only short-listed candidates.