Abstract:
Kenya's forest sector is undergoing major changes, which are attributed to the rapid depletion and degradation of natural resources, as well as viable actions on remedial measures. The demand for forest products and ecosystem services continue to increase against a declining supply from afforestation, reforestation and the dynamics of work. This emerging challenge necessitates improving the institutional capacity of organisations that are involved in, or support forest conservation activities. It is increasingly recognised that a combination of factors, which include inefficient operational capacity, contributes to the low levels in adopting forestry innovations. This implies that there are limited possibilities to achieving an enhanced adoption of forestry innovations over time. There is therefore, a need to identify the knowledge gaps and quantify the interactive influence of institutional capacity on adoption of forestry innovations over time. The main objective of the study was to analyse institutional capacity and adoption of forestry innovations across relevant institutions in Kenya. The study dealt with 51 main institutions involved in, or support conservation activities, of which 32 were public, 15 non-governmental, and 4 private. Stratified purposive sampling was used due to the heterogeneity of the institutions involved in conservation. Primary data were collected using a structured questionnaire to examine the following capacity indicators: human capital, conservation interactions, training interactions, research interactions, user interactions, internal interactions, non-salary incentives, salary incentives, technical support, published outputs, electronic media output, conservation management, conservation investments, and facilities at empirical level. Conceptually, the indicators were categorised as tangible and intangible variables at operational level. Their interactive variables constituted the theoretical level expressed as visible adoption of forestry innovations. The analytical model used, which was based on quartile statistics, established what accounted for the differences in capacity variation as expected variation region or the common cause and the unexpected variation region or the special cause, which should be investigated and acted upon. Embracing the approach confirmed the model as appropriate quantitative analytical framework for assessing and articulating elements of institutional capacity and adoption of forestry innovations across the relevant institutions in Kenya. Evidently, the study reiterates that to overcome institutional capacity gaps and respond to conservation paradigm shift, relevance, engagement, and commitment of all stakeholders is imperative.
