The effects of community-based group capacity on resource management planning success: Moving implementation outcomes from good to great

Background/Question/Methods

As community-based natural resource management (CBNRM) approaches increase in popularity, questions regarding the capacity of such groups to successfully manage natural resources are increasingly relevant.  However, few studies have quantitatively analyzed how the amount or type of capacity in a CBNRM organization directly affects the outputs or the environmental outcomes produced. Contributing to this paucity of research is the wide diversity of indicators for CBNRM group capacity and the heated debate over how to best define and measure success in CBNRM initiatives. Although concrete outputs vary widely, many efforts focus on creating natural resource management plans (RMPs). Our objectives were to explore the link between capacity and RMP implementation success within CBNRM groups across Illinois. We constructed a short, on-line survey to measure CBNRM participants’ (n=190) evaluations of ten key capacity indicators (i.e., leadership, communication, funding, etc.) and perceptions of RMP implementation success (i.e., low, moderate and high). To examine the relationship between RMP implementation success and the capacity indicators, we conducted multivariate analysis of variance (MANOVA) and discriminant function analysis (DFA), using RMP implementation success categories as the discriminant groups.

Results/Conclusions

We found that capacity, as measured by our indicators, was significantly different across each category of RMP implementation success (Pillai's Trace = 0.567, F(20, 232) = 4.592, P < 0. 001), with higher levels of capacity found in the most successful CBNRM groups. We also found that that the level of capacity within a CBNRM group was predictive of RMP implementation success (Wilk’s lambda = 0.495, P < 0.001 and Wilk’s lambda = 0.851, P < 0.023) with a 62.3% hit ratio. Further, our findings suggest that bonding social capital is crucial in predicting low versus moderate implementation success, while vision and motivation best distinguish moderately successful and highly successful RMP implementation. These patterns, evident in past management attempts, provide valuable direction for future CBNRM planning efforts.