INTERACTIVE TOOLKIT FOR
CROP WILD RELATIVE CONSERVATION PLANNING version 1.0

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Development of a monitoring plan at the individual CWR level.

Regardless of where the monitoring of CWR populations takes place (within formally recognized genetic reserves or informal in situ conservation areas) the monitoring is likely to be implemented as follows:

  1. Identification of the monitoring objectives for target CWR.
  2. Identification and selection of variables to monitor.
  3. Design of the sampling strategy.
  4. Selection of the sampling units.
  5. Positioning of sampling units.
  6. Determination of the timing of monitoring.
  7. Determination of frequency of monitoring
  8. Implementation of a pilot study.
  9. Data analysis.
  10. Adjustment of the monitoring plan.

1. Identification of the monitoring objectives of target CWR

The initial step is to define the specific objectives of the monitoring programme, for example whether to assess trends in population size and structure and/or in population genetic diversity. Ideally, genetic diversity monitoring should be carried out but, as it is costly, it should only be used if specific questions need to be answered (see Iriondo et al. 2008 for recommendations on how, when and why to use genetic monitoring). Monitoring of genetic diversity may be needed (i) to recognize situations where an overall reduction of fitness has occurred, (ii) to decide what to do if a conserved population or population being considered for protection has severely declined in population size and (iii) to assess the extent of gene flow among populations that are, or have become, fragmented in a conservation area.

2. Identification and selection of variables to monitor

These variables may include demographic, ecological, anthropogenic and/or genetic parameters (see Table below for a description of these variables). Life form and breeding system of target taxa and the resources available for monitoring should be taken into account.

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TABLE 1 Monitoring parameters for CWR to detect changes in diversity (see Iriondo et al. 2008 for more detail on each parameter).
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TABLE 2 Demographic parameters that should be monitored according to the population size and threat status of the target taxon (source: Iriondo et al. 2008).
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TABLE 3 Parameters and equations for monitoring plant community structure (source: Cox 1990).

3. Design of the sampling strategy

This involves making decisions on the type, size, number and position of the sampling units and the timing and frequency of sampling (Elzinga et al. 2001). It should be based on both a literature review of target taxa or of taxa with similar life forms and biological traits and on consultation with experts.

4. Selection of the sampling units

Sampling can be carried out using various methods:

  • Plots (or quadrats): diversity is sampled within areas of standard size. The establishment of permanent quadrats is perhaps the most used monitoring method.
  • Transects (banded transects or intercept transects): diversity is sampled within a defined distance either side of a central line, often one metre either side, making a two-metre-wide transect. The intercept method samples diversity that actually touches the transect line.
  • Monitoring of individual plants (or plant parts) for particular attributes (e.g. plant height, number of seeds per fruit) (Iriondo et al. 2008).

5. Positioning of sampling units

This should be random and ideally distributed throughout the entire distribution of the population. Simple random sampling involves the selection of a combination of sampling units that each have the same probability of being selected. Equally, the selection of one sampling unit does not affect the selection of any other. Systematic sampling involves the collection of samples at regular (in time and space) intervals. Stratified random sampling involves dividing the population into two or more groups prior to sampling, where individuals within the same group share common features, and simple random samples then are taken within each group (Iriondo et al. 2008).

6. Determination of the timing of monitoring

Populations of CWR should be monitored regularly in order to detect any changes. Monitoring should be scheduled at the same phenological time each year to ensure data are directly comparable between monitoring events. It is often most effective during flowering or fruiting, because taxa can be easily identified. However, it may also be possible when leaves are unusually coloured or about to fall, or when the surrounding vegetation does not obscure the target species or a particular character of the target species.

7. Determination of frequency of monitoring

This depends on the life form, the expected rate of change, the rarity and trend of the target species, as well as the resources available for monitoring. It can be as frequent as every month during several growing seasons (e.g. rare or very threatened annuals), or much less frequently (e.g. perennials). In many cases working with both annuals and perennials, monitoring is performed annually.

8. Implementation of a pilot study

Once the monitoring scheme has been designed, a pilot study should be carried out before the implementation of a long-term monitoring strategy. This provides an opportunity to assess whether the experimental design and the field techniques are efficient or whether they need some adjustment.

9. Data analysis

The results of the pilot study should be analyzed in order to detect possible problems with the monitoring design and field methodologies. Statistical tests that provide meaningful conclusions need to be chosen at this stage.

10. Adjustment of the monitoring plan

Refinement of the monitoring plan will often be necessary. If variables such as the chosen sample size, or the position of sampling units etc. are found to be inadequate in detecting meaningful changes in the population they will need to be adjusted. Nevertheless, it is important to note that changes to the monitoring regime may impact data comparison, so any changes need to be considered carefully, possibly with the help of a statistician, before being implemented.


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