Wildlife Conservation Evaluation

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Some outcomes feed back into knowledge of the system and effect the input activities, and so the case study model is not complete. Further ecological studies and analysis of management processes would be needed to provide knowledge of more complex feedback loops. Mid-term evaluations can be used to check against project milestones, to benchmark against other programmes or to simply think about the project from a fresh perspective.

They can be used to identify areas of slack resource, or activities which could be scaled down in order to improve the overall effectiveness. The value of staff experience and the ways in which individuals learn while working their role is an important consideration for leaders because these factors have a direct impact on the effectiveness of their workforce.

It can be difficult for individuals to get all the experience they need while workloads are not at a peak, but these times allow them to become comfortable in their everyday tasks, even if this leads to idle time. The Theory of Change is a useful tool to assist leaders in understanding the importance of institutional knowledge, investment in experience and ecosystem knowledge. Conservation managers can develop a TOC to better explain interim outputs, set performance indicators and to relate these to impacts that are realised over the long term.

A TOC could be devised by leaders of other conservation projects through a similar process of internal document review and by carrying out semi structured interviews with their staff to ensure that the programme aims are communicated and understood. Prioritisation of work is important to leaders, and particularly those in the field of conservation, because resources can be limited and decisions about which action to take first will commonly lead to a worsening situation in the areas where no action is taken.


Once established, the TOC model can be used in regular planning activities to help set priorities, and so that mid-term evaluations become part of management process. The conservation actions of a project may have regular reviews, perhaps prompted by annual funding decisions, but the management processes of conservation programmes can also benefit from the type of in-depth evaluation which this study has described.

We thank the staff at Mauritian Wildlife Foundation, particularly the interviewees and Mauritius Fody project team. In addition, we thank the three anonymous reviewers for their helpful comments on earlier drafts of this manuscript. Conservation Biology, 29, Foudia rubra. International Journal of Ecology, , Open Journal of Leadership, 3, Conservation Biology, 24, Conservation Letters, 4, ISRN Biodiversity, , Ecology and Society, 16, Giving Direction and Clarity to Conservation Leadership.

Conservation Letters, 8, Biological Conservation, , Bird Conservation International, 20, Conservation Evidence, 6, Zoo Biology, 27, Wildlife Research, 40, Money for Nothing? PLoS Biology, 4, e Mauritius Fody Annual Report Unpublished Report to the Mauritian Wildlife Foundation. Animal Conservation, 15, Evaluation and Program Planning, 33, New York: McGraw Hill. Conservation Letters, 1, Oryx, 43, Supplementary Report No.

Conservation Biology, 23, New Directions for Evaluation, , Acting Fast Helps Avoid Extinction. Conservation Letters, 5, Monthly Mauritius Fody Report. Glossary of Statistical Terms. Frontiers in Ecology and the Environment, 6, Evaluation, 14, Andersen, G. Sterman Eds. What Is Conservation Biology? BioScience, 35, The Need for Evidence-Based Conservation. Trends in Ecology and Evolution, 19, Theory of Change: Technical Papers. New York. Handbook of Practical Program Evaluation. Evaluation, 19, A Guide to Organizational Assessment Process.

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Wildlife Conservation Evaluation

DOI: Mid-term evaluations can be informative tools to check how short term activities and resources are achieving long term conservation outcomes. This research study involved a programme evaluation of a successful species recovery project in Mauritius, using a systems-thinking approach to conservation management, and utilising a Theory of Change to assess the effectiveness of short term activities on long term impacts.

This systematic method of evaluation gave greater clarity on resource planning, performance indicators and supporting processes, with observations that could be incorporated into ongoing plans. Such an approach could be used by funding organisations or by local management teams to review project performance without the need for a comparator, extensive benchmark data, nor a prescriptive management standards framework.

Introduction Leadership is an important tool for advancing the field of wildlife conservation. The species was down-listed from Figure 1. Conflicts of Interest The authors declare no conflicts of interest. Cite this paper Stebbings, E. Open Journal of Leadership , 5 , References [ 1 ] Addison, P.

Wildlife conservation evaluation: attributes, criteria and values

Please enable JavaScript to view the comments powered by Disqus. OJL Subscription. E-Mail Alert. OJL Most popular papers. The current distribution of the mara within the landscape was not known, but we do expect that historically it was limited to areas with adequate habitat conditions. This species also probably historically used the entire landscape. We had more detailed knowledge of its distribution and abundance within the landscape than for the other species, as well as information on human activities affecting its abundance at specific sites [ 17 ].

Nevertheless, we sought to evaluate human activities associated with the distribution of this species throughout the landscape, in order to evaluate potential landscape-level impacts of addressing those activities. The human activities we considered to potentially have the greatest impacts on wildlife distribution and abundance were hunting and livestock husbandry. There are two principal types of hunting in the region, hunting by poachers, mostly urban residents, from vehicles along roads, and hunting by rural people from horseback.

Interventions for the two types of hunting would be different. Livestock husbandry may affect native herbivores through various mechanisms, including direct competition for food and water, persecution by livestock producers, disease transmission from livestock to wildlife, and apparent competition between livestock and native prey via supplementation of native predators by livestock [ 13 ], [ 17 — 24 ]. Our design, based on occupancy modeling with covariates related to different human activities, permitted us to simultaneously evaluate distribution of these species and collect preliminary information on the most relevant human activities to target for adaptive management over the landscape.

This approach could be useful to plan conservation for large, mixed-use areas where information on distribution of target species and human activities, as well as relationships between animal distributions and human activities, is needed in a short time period. The 20,km 2 study area in northern Patagonia Fig 1 is a mosaic of three biomes: the Patagonian steppe, scrub, and high Andes. The topography consists of high plateaus, river valleys, and old volcanic cones up to m.

Due to this geography and topography, the region is one of the areas of highest biodiversity of arid Patagonia [ 9 ]. The predominant activity of local people is small-scale goat husbandry.

We divided the study area into a grid of 2 km by 2 km cells, and eliminated those that were inaccessible due to altitude and lack of trails or roads. We determined that with sites sampled 2 times, including a subset of 20 sites sampled more intensively 4 times , we could achieve an occupancy estimate of 0. We randomly selected cells to sample from the cells in the grid. We used a single-season design, and because of the high cost in time and money of reaching each site, we did repeated spatial sampling of each site on the same day, rather than repeating sampling over time [ 25 ].

Sampling was carried out from September to March , during the austral spring and summer. We sampled signs rather than using direct observation of animals on transects due to relative low density of all species, which would lead to low sample sizes. The pilot study and other previous work by our group on lesser rheas demonstrated that sign transects and transects based on direct sightings of rheas are highly correlated, and that use of direct sightings tends to underestimate rhea abundance, especially in areas of low density [ 26 ].

Sampling was based on observation of signs while walking along m transects. The cells to be sampled more intensively and the point of origin and orientation of each transect were chosen randomly. We recorded feces and other signs carcasses, tracks, feathers of lesser rheas, guanacos, and maras encountered along each transect. A transect was considered to be occupied by the species if at least one sign of that species was found in the transect. For each cell we estimated covariates related to habitat, hunting, and livestock husbandry Table 1.

Habitat covariates included NDVI, as a proxy for productivity, elevation, and slope.

Wildlife: Wildlife Habitat Evaluation Pgm (WHEP)

Working with 0. Slope was calculated as the average percent of slope per cell, obtained via the digital elevation model DEM using Spatial Analyst in ArcMap 9. We used density of roads within a cell including oil exploration trails , distance to the nearest public road, and distance to the nearest town as measures of access by poachers [ 17 ], and distance to the nearest rural residence as a measure of pressure of hunting by rural people Table 1.

For livestock husbandry, we used the proportion of each transect used by large and small livestock, as described above. For maras we also included introduced lagomorphs as potential competitors. We digitized roads and passable oil exploration trails as seen in Google Earth 6. We measured the distance from the central point of each cell to the nearest town, nearest road, and nearest rural residence in ArcGIS. Finally, we also considered factors that could affect the detection of signs in the transects and included these as covariates for the estimation of the probability of detection.

Most transects were carried out by the first author, so we also considered her greater experience with detection of signs to be a possible influence on detection probability and included the observer as an additional covariate in the estimation of detection probability. Remaining surveys were on private lands where we obtained permission from the owners to conduct surveys at each site. Occupancy models provide an estimation of occupancy psi that incorporates the probability of detection p.

Inclusion of covariates for occupancy provides a means for evaluating their impact on occupancy, and covariates for detection provide more robust estimations of occupancy. We first modeled detection probability with covariates, and for each species identified those that improved the models relative to models without the covariates. Variables with wide ranges of values that were not close to 1 NDVI, slope, elevation, road density, distance to nearest rural residence, distance to nearest town were normalized.

For each occupancy model we calculated the AIC, which provides a measure of fit and precision of the model, and ordered models from lowest to highest AIC. For each model we calculated the normalized Akaike weight as a measure of relative plausibility. This allowed us to make inferences about the relative importance of individual covariates when several models were supported nearly equally.

As models with covariates provide site-specific estimates of occupancy and detectability, we report the range of probabilities of occupancy and standard errors of occupancy for different sites under each model. To provide a measure of variability for these, we weighted each site-specific occupancy and standard error estimate by the model weight and summed over all of the equally plausible models.

We averaged these and calculated an overall weighted coefficient of variation CV by dividing the weighted standard errors by the weighted psi for each site and averaging over all sites. Finally, to get an overall estimate of potential impact of addressing different threats on the suite of species, we summed the importance weights for human-related covariates across all three species [ 6 ]. Lesser rheas were found throughout most of the study area, and maras were absent from the northernmost part of the study area and around the Rio Colorado. Therefore, we used feces of all age categories in the remainder of the analyses.

In the detection probability models for lesser rheas, the lowest AIC was obtained using the time of day as a covariate Table 3. Detectability of lesser rhea signs was very high, with estimates ranging from 0. Probability of detection was greatest at midday, lower in the morning, and lowest in the afternoon. Lesser rheas were found in higher, steeper areas, with lower productivity, though elevation and slope were of relatively low importance. With respect to livestock, lesser rheas were more likely to be found where there were fewer sheep, goats, cows, and horses, with sheep and goats having a much greater importance than large livestock.

Finally, for the covariates related to hunting, lesser rheas were more likely to be found closer to roads and farther from rural residences, in areas with fewer roads Tables 5 and 6. Probability of occupancy of different sites psi under the models ranged from 0. For maras, neither time of day nor observer as detection probability covariates lowered the AIC Table 3. Thirteen models were equally plausible Table 7. In terms of habitat, maras were found in flatter areas of higher productivity.

Maras were positively associated with livestock and exotic lagomorphs. With respect to covariates related to hunting, maras were more likely to be present in areas with fewer roads, and closer to roads and residences Tables 8 and 9. Road density was the covariate with the greatest importance weight for maras, with a weight two times greater than that of the covariate with the next highest weight Table 8. Probability of occupancy per site under different models ranged from 0.

For guanacos, the detection probability model with lowest AIC contained the observer as a covariate Table 3. The principal observer had a higher detection probability than the secondary observers.

Applying Systems Thinking and Logic Models to Evaluate Effectiveness in Wildlife Conservation

Probability of detection of signs was high, ranging from 0. Five models were equally plausible. In terms of covariates related to habitat, guanacos were more likely to be found in higher, steeper areas. Among the covariates related to hunting, guanacos were more likely to be found where there were fewer roads Tables 11 and Probability of occupancy of different sites as estimated under the different models ranged from near zero to 0. When importance weights for covariates were summed across species, the covariate with the greatest weight was goat and sheep density Table This overall importance weight was negative even though the relationship with maras was positive, due to the heavy negative weights for guanacos and rheas.

Road density had the next greatest importance, as it had a negative weight for all three species. Although distance to the nearest road was not associated with guanaco presence, this was the covariate with the next greatest weight, due to its negative association with rheas and maras. The overall importance weights of cow-horse and distance to the nearest rural residence were also negative.

Importance weights obtained for covariates related to different threats allow us to establish hypotheses to guide conservation actions for adaptive intervention within this landscape, a method that could be used for similar conservation planning in other areas. The analysis is not meant to enable strong conclusions about explanatory power of the covariates [ 6 ], nor are the specific results meant to be extrapolated to other landscapes.

The most important factor associated with distribution of the suite of species in the landscape was goat and sheep density. This suggests that interventions that reduce the impact of livestock would have the greatest impacts on the conservation of these species. However, the research does not identify the mechanism through which goats and sheep are negatively associated with lesser rheas and guanacos, and positively with maras, so our initial conservation actions must be based on hypotheses about these mechanisms, supplemented by prior research and other information from the landscape.

Possible mechanisms for the strong negative relationship between goat and sheep density and lesser rheas and guanacos include direct and indirect competition, habitat degradation resulting from heavier grazing in areas with more goats and sheep, and persecution by or greater presence of goat and sheep herders in areas used more heavily by their livestock. In studies in other parts of Patagonia, lesser rheas did not appear to be negatively affected by high numbers of sheep nor greatly affected by overgrazing, did not have a high dietary overlap with sheep, and intense hunting and egg harvest appeared to have a stronger effect than overgrazing on their density and reproductive success [ 21 ], [ 33 ].

Thus we hypothesize that for rheas, the mechanism for the negative relationship with sheep and goats in our area could be persecution by or greater presence of herders in areas with more sheep and goats. Alternatively, goats are much more common than sheep in this area, and we cannot rule out a negative impact of greater competition with goats compared to sheep. For guanacos, the mechanism for the negative relationship with livestock is most likely direct competition.

The fact that guanacos were found in the drier areas makes habitat degradation an unlikely mechanism. Other studies have found a strong negative relationship between guanacos and sheep [ 23 ],[ 35 ], and goat [ 20 ] density, and have provided evidence that the mechanism is direct competition for forage [ 14 ], [ 24 ], [ 36 ].

However, persecution by herders and ranchers and their dogs is common pers. The mara is much more of a habitat specialist than the other two species, and its positive association with livestock may be because of a preference for more open habitat, due to a strategy for escaping predation based on early detection and fast flight to the safety of a den. Maras have higher reproductive success in more open areas [ 37 ], [ 38 ], and more open areas are temporarily covered with annual grasses in spring, resulting in increased food resources at this critical time of year [ 39 ].

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Forty-two CEAP watershed studies have been initiated to provide in-depth analysis and quantification of the measurable effects of conservation practices at the watershed scale and enhance our understanding of the effects of conservation in the biophysical setting of a watershed. Future efforts will include translating this science into practice to better manage agricultural landscapes.

Current literature on conservation programs that documents what is known and not known about the environmental benefits of conservation practices and programs for cropland, fish and wildlife, wetlands, and grazing lands. The National Agricultural Library maintains dynamic bibliographies cataloging studies from to the present. A full listing of all CEAP-related documents published to date. Review CEAP documents by region and assessment via interactive map. Natural Resources Conservation Service.