Biocultural Hysteresis Inhibits Adaptation to Environmental Change.

Indigenous peoples and local communities (IPLC) often use natural resources as both a reason and mechanism for environmental management, yet a number of environmental, social, and economic drivers disrupt this relationship. Here, we argue that these drivers can also trigger a set of feedback mechanisms that further diminish the efficacy of local management. We call this process biocultural hysteresis. These feedbacks, which include knowledge loss and a breakdown of social hierarchies, prevent IPLC from adapting their management to change. Biocultural hysteresis worsens as IPLC spend an increasing amount of time outside their social-ecological context. Therefore, we argue for adaptive policies and processes that favour protecting and enabling IPLC engagement with their environment.

Elevated mercury concentrations in the feathers of grey-faced petrels (Pterodroma gouldi) in New Zealand.

Our objective was to measure the concentrations of Hg, As, Cd, Co, Cr, Cu, Pb, Sb, V and Zn in the body feathers of grey-faced petrel (Pterodroma gouldi), fluttering shearwater (Puffinus gavia), little shearwater (Puffinus assimilis) and common diving petrel (Pelecanoides urinatrix) from breeding colonies in New Zealand between 2006 and 2013. The mean Hg concentration (36.48ppm; SD=9.59) in grey-faced petrel feathers was approximately 8.5 to 14 times that detected in the other three species sampled. We detected no trend or differences in Hg concentrations in grey-faced petrels over the 8years of this study, but Hg concentrations varied between breeding colonies although there was no strong relationship with latitude. The elevated Hg concentrations detected in grey-faced petrels could pose a risk to the breeding performance of grey-faced petrels and the customary harvest of chicks by Maori (New Zealand's indigenous peoples).

Pattern recognition in long­term Sooty Shearwater data: applying machine learning to create a harvest index.

Rakiura Maori (New Zealand's southernmost group of indigenous peoples) have harvested the chicks of burrow-nesting Sooty Shearwaters (Titi; Puffinus griseus) for generations. As part of the harvest process, some families have maintained annual harvest diaries, some dating back to the 1950s. We used generalized boosted regression models, a machine-learning algorithm, to calculate a harvest index that takes into account factors that could impact the numbers of birds taken on any given hunt. For predicted vs. observed values, r2 was between 0.59 and 0.90 for the nanao (first half of the season, when chicks are harvested from burrows during the day) and 0.67 and 0.88 for the rama (second half of the season, during which chicks are harvested from the surface at night). Exploration of the controlling factors of the models revealed that "day of season" plays an important role in predicting daily harvest during the second half of the season (the rama). The nightly tally in the rama peaked approximately halfway through (10­15 days in), which is probably related to the timing of birds emerging from burrows to fledge. The models also suggested that data from the rama (when chicks are 100­120 days old) may be the most suitable for long-term monitoring of populations of Sooty Shearwaters due to consistencies in calculated harvest indices between diaries. Nanao harvest indices, although less consistent, showed patterns similar to those of the rama. When comparing these data to the harvest indices calculated by general linear models by Clucas and colleagues, we found that the agreement between both indices was r2 = 0.31 and r2 = 0.59 for the nanao and rama, respectively. The use of machine learning to correct for extraneous factors (e.g., hunting effort, skill level, or weather) and to create standardized measures could be applied to other systems such as fisheries or terrestrial resource management.