Cumulative effects of widespread landscape change alter predator-prey dynamics.

Predator search efficiency can be enhanced by anthropogenic landscape change, leading to increased predator-prey encounters and subsequent prey population declines. Logging increases early successional vegetation, providing ungulate forage. This increased forage, however, is accompanied by linear feature networks that increase predator hunting efficiency by facilitating predator movement and increasing prey vulnerability. We used integrated step selection analyses to weigh support for multiple hypotheses representing the combined impact of logging features (cutblocks and linear features) on wolf (Canis lupus) movement and habitat selection in interior British Columbia. Further, we examine the relationship between logging and wolf kill-sites of moose (Alces alces) identified using spatiotemporal wolf location cluster analysis. Wolves selected for linear features, which increased their movement rates. New (0-8 years since harvest) cutblocks were selected by wolves. Moose kill-sites had a higher probability of occurring in areas with higher proportions of new and regenerating (9-24 years since harvest) cutblocks. The combined selection and movement responses by wolves to logging features, coupled with increased moose mortality sites associated with cutblocks, indicate that landscape change increases risk for moose. Cumulative effects of landscape change contribute to moose population declines, stressing the importance of cohesive management and restoration of anthropogenic features.

Identifying crop vulnerability to groundwater abstraction: modelling and expert knowledge in a GIS.

Water use is expected to increase and climate change scenarios indicate the need for more frequent water abstraction. Abstracting groundwater may have a detrimental effect on soil moisture availability for crop growth and yields. This work presents an elegant and robust method for identifying zones of crop vulnerability to abstraction. Archive groundwater level datasets were used to generate a composite groundwater surface that was subtracted from a digital terrain model. The result was the depth from surface to groundwater and identified areas underlain by shallow groundwater. Knowledge from an expert agronomist was used to define classes of risk in terms of their depth below ground level. Combining information on the permeability of geological drift types further refined the assessment of the risk of crop growth vulnerability. The nature of the mapped output is one that is easy to communicate to the intended farming audience because of the general familiarity of mapped information. Such Geographic Information System (GIS)-based products can play a significant role in the characterisation of catchments under the EU Water Framework Directive especially in the process of public liaison that is fundamental to the setting of priorities for management change. The creation of a baseline allows the impact of future increased water abstraction rates to be modelled and the vulnerability maps are in a format that can be readily understood by the various stakeholders. This methodology can readily be extended to encompass additional data layers and for a range of groundwater vulnerability issues including water resources, ecological impacts, nitrate and phosphorus.