We used evolutionary programming to model innate migratory pathways of wildebeest in the Serengeti Mara Ecosystem, Tanzania and Kenya. Wildebeest annually move from the southern short‐grass plains of the Serengeti to the northern woodlands of the Mara. We used satellite images to create 12 average monthly and 180 10‐day surfaces from 1998 to 2003 of percentage rainfall and new vegetation. The surfaces were combined in five additive and three multiplicative models, with the weightings on rainfall and new vegetation from 0% to 100%. Modeled wildebeest were first assigned random migration pathways. In simulated generations, animals best able to access rainfall and vegetation were retained, and they produced offspring with similar migratory pathways. Modeling proceeded until the best pathway was stable. In a learning phase, modeling continued with the ten‐day images in the objective function. The additive model, influenced 25% by rainfall and 75% by vegetation growth, yielded the best agreement, with a multi‐resolution comparison to observed densities yielding 76.8% of blocks in agreement (kappa = 0.32). Agreement was best for dry season and early wet season (kappa = 0.22–0.57), and poorest for the late wet season (0.04). The model suggests that new forage growth is a dominant correlate of wildebeest migration.

Rangelands are one of the Earth’s major ice-free land cover types. They provide food and support livelihoods for millions of people in addition to delivering important ecosystems services. However, rangelands are at threat from climate change, although the extent and magnitude of the potential impacts are poorly understood. Any declines in vegetation biomass and fluctuations in grazing availability would be of concern for food production and ecosystem integrity and functionality. In this study, we use a global rangeland model in combination with livestock and socio-economic datasets to identify where and to what extent rangeland systems may be at climatic risk. Overall, mean herbaceous biomass is projected to decrease across global rangelands between 2000 and 2050 under RCP 8.5 (−4.7%), while inter- (year-to-year) and intra- (month-to-month) annual variabilities are projected to increase (+21.3% and +8.2%, respectively). These averaged global estimates mask large spatial heterogeneities, with 74% of global rangeland area projected to experience a decline in mean biomass, 64% an increase in inter-annual variability and 54% an increase in intra-annual variability. Half of global rangeland areas are projected to experience simultaneously a decrease in mean biomass and an increase in inter-annual variability—vegetation trends both potentially harmful for livestock production. These regions include notably the Sahel, Australia, Mongolia, China, Uzbekistan and Turkmenistan and support 376 million people and 174 million ruminant Tropical Livestock Units. Additionally, the rangeland communities currently the most vulnerable (here, with the lowest livestock productivities and economic development levels and with the highest projected increases in human population densities) are projected to also experience the most damaging vegetation trends for livestock production. Although the capacity of rangeland systems to adapt is highly complex, analyses such as these generate some of the information required to inform options to facilitate pastoral system mitigation and adaptation strategies under climate change.

We developed a “continual engagement” model to better integrate knowledge from policy makers, communities, and researchers with the goal of promoting more effective action to balance poverty alleviation and wildlife conservation in 4 pastoral ecosystems of East Africa. The model involved the creation of a core boundary-spanning team, including community facilitators, a policy facilitator, and transdisciplinary researchers, responsible for linking with a wide range of actors from local to global scales. Collaborative researcher−facilitator community teams integrated local and scientific knowledge to help communities and policy makers improve herd quality and health, expand biodiversity payment schemes, develop land-use plans, and fully engage together in pastoral and wildlife policy development. This model focused on the creation of hybrid scientific−local knowledge highly relevant to community and policy maker needs. The facilitation team learned to be more effective by focusing on noncontroversial livelihood issues before addressing more difficult wildlife issues, using strategic and periodic engagement with most partners instead of continual engagement, and reducing costs by providing new scientific information only when deemed essential. We conclude by examining the role of facilitation in redressing asymmetries in power in researcher−community−policy maker teams, the role of individual values and character in establishing trust, and how to sustain knowledge-action links when project funding ends.

People construct fences to delineate land ownership and to control access to land. Fences accomplish several purposes, notable among these are containing livestock or wildlife raised for profit or subsistence, excluding use of vegetation within areas to be conserved and reducing conflicts between wildlife and humans. In addition, fences may offer unanticipated benefits such as vegetation within hedgerow fences providing cover to wildlife, or grazing by confined herbivores promoting native flora. However, because fences limit mobility of large herbivores, fenced areas become fragments within the landscape. Fences may entangle or electrocute herbivores, truncate migratory routes, excise important resources needed by large herbivores and allow resident herbivore populations to become too high and damage vegetation. More subtly, fencing parcels may reduce the carrying capacity of a landscape irrespective of habitat loss by eliminating access to heterogeneous forage patches. Normalised difference vegetation in...