Knowledge gain or system benefit in environmental decision making?

The quality of environmental decisions are gauged according to the management objectives of a conservation project. Management objectives are generally about maximising some quantifiable measure of system benefit, for instance population growth rate. They can also be defined in terms of learning about the system in question, in such a case actions would be chosen that maximise knowledge gain, for instance in experimental management sites. Learning about a system can also take place when managing practically. The adaptive management framework (Walters 1986) formally acknowledges this fact by evaluating learning in terms of how it will improve management of the system and therefore future system benefit. This is taken into account when ranking actions using stochastic dynamic programming (SDP). However, the benefits of any management action lie on a spectrum from pure system benefit, when there is nothing to be learned about the system, to pure knowledge gain. The current adaptive management framework does not permit management objectives to evaluate actions over the full range of this spectrum. By evaluating knowledge gain in units distinct to future system benefit this whole spectrum of management objectives can be unlocked. This paper outlines six decision making policies that differ across the spectrum of pure system benefit through to pure learning. The extensions to adaptive management presented allow specification of the relative importance of learning compared to system benefit in management objectives. Such an extension means practitioners can be more specific in the construction of conservation project objectives and be able to create policies for experimental management sites in the same framework as practical management sites

Stem growth of woody species at the Nkuhlu exclosures, Kruger National Park: 2006–2010

An important aspect of managing African conservation areas involves understanding how large herbivores affect woody plant growth. Yet, data on growth rates of woody species in savannas are scarce, despite its critical importance for developing models to guide ecosystem management. What effect do browsing and season have on woody stem growth? Assuming no growth happens in the dry season, browsing should reduce stem growth in the wet season only. Secondly, do functional species groups differ in stem growth? For example, assuming fine-leaved, spiny species’ growth is not compromised by carbon-based chemical defences, they should grow faster than broad-leaved, chemically defended species. Dendrometers were fixed at 20 cm in height on the main stems of 244 random plants of six woody species in three plots (all large herbivores excluded, partial exclusion, and control) and observed from late 2006 to early 2010. Average monthly increment (AMI) per dendrometer and season (dry, wet) was calculated and the interaction between plot and season tested per species, controlling for initial stem girth. AMIs of Combretum apiculatum, Dichrostachys cinerea and Grewia flavescens were zero in the dry season, whilst those of Acacia exuvialis, Acacia grandicornuta and Euclea divinorum were either positive or negative in the dry season. Wet-season AMI of D. cinerea and dry-season AMI of G. flavescens tended to be reduced by browser exclusion. Net AMI (sum of the seasonal AMIs) was tested per species, but results suggested that only D. cinerea tended to be affected by browser exclusion. The results also suggested that stem radial growth of some fast-growing species is more prone to reduction by browser exclusion than the growth of other species, potentially reducing their competitiveness and increasing their risk of extirpation. Finally, the usefulness of grouping woody species into simple functional groups (e.g. fine-leaved vs. broad-leaved) for ecosystem management purposes in savannas requires further consideration. Conservation implications: Growth rates of woody plants are important parameters in savanna models, but data are scarce. Monitoring dendrometers in manipulative situations over several years can help fill that gap. Results of such studies can be used to identify species prone to high risk of extirpation