How to use this toolkit
Recommendations on the appropriate use of indicators
Define your outcomes and assumptions: An ecological indicator should always be chosen to measure progress towards an intended outcome, or to test an important assumption in a Theory of Change. For instance, if your outcome is to protect pangolin species from overexploitation, you might want to measure wild meat use through surveys of pangolin offtakes (to measure harvest rates) and assess pangolin population numbers over time (to monitor population changes).
Identify the contextual factors affecting your system: It is crucial to rule out effects from other factors (e.g., natural population fluctuations, environmental factors such as change in food availability for game species and extreme climatic events [e.g., Bodmer et al. 2018], diversification of livelihoods and human migration [e.g., Gill et al. 2012], or anthropogenic factors such as habitat degradation) before making firm conclusions about the trends in wild meat based on indicators. You may therefore need to also collect data on these factors, as well as data on hunting and to populate your ecological indicators.
Select appropriate indicators: Different indicators will be appropriate for different questions are contexts. You will want to select indicators that track progress towards your outcomes, but you may also want to take into account the level of accuracy you require from the indicator, your available budget, technical capacity and time available.
Where possible, use more than one indicator, from different types of survey: Researchers should not rely on a single indicator to make inferences about the ecological impacts of wild meat use, but rather use several compelling and consistent indicators to make reasoned decisions regarding the impacts of wild meat use (see Richard-Hansen et al. 2019). Analysed in aggregate, a larger number of indicators pointing to the same outcome decreases the likelihood of an incorrect inference. We recommend that wild meat researchers should combine indicators from different surveys as frequently as possible – i.e., conducting offtake surveys concomitantly with surveys of the population size and distribution of hunted species in the same area. Alternatively, comprehensive testing must be conducted to ensure that these indicators are indeed reliable to be used as proxies of populations in that context (see Rao et al. 2005; Kümpel et al. 2008; Marrocoli et al. 2019).
Clearly define the extent of surveyed area: Indicators should be measured and be related to conditions and changes within a specific spatial area (e.g., protected area, management unit, supply basin, etc.).
Where possible, use control areas: It is always advisable to include control areas with which to compare the indicator trends with those measured in areas unaffected by hunting.
Collect baseline data before your intervention starts: If you work on an intervention project, indicators should be measured before starting the project to provide a baseline from which to monitor change and check whether the outcomes are being achieved as the monitoring cycle goes ahead.
Analyse trends over time: We recommend the assessment of trends of indicators over time in the same space (i.e., study area). Several studies can still be conducted using ‘space-for-time substitution’, such as comparisons between hunted and unhunted areas, or hunting offtake among communities with different human populations and ages, which likely reflect different points in time. However, these studies are ‘snapshots’ and should be interpreted with caution, since they do not provide a full picture and understanding of the impacts of wild meat use in those areas. It is important to take into consideration that social settings and ecological areas are usually not the same, and an impact of hunting in an area used by hunters does not necessarily reflect in a significant impact in the population of the target species in its whole area of distribution.