Modelling cheetah relocation success in southern Africa using an Iterative Bayesian Network Development Cycle

Relocation is one of the strategies used by conservationists to deal with problem cheetahs in southern Africa. The success of a relocation event and the factors that influence it within the broader context of long-term viability of wild cheetah metapopulations was the focus of a Bayesian Network (BN) modelling workshop in South Africa. Using a new heuristics, Iterative Bayesian Network Development Cycle (IBNDC), described in this paper, several networks were formulated to distinguish between the unique relocation experiences and conditions in Botswana and South Africa. There were many common underlying factors, despite the disparate relocation strategies and sites in the two countries. The benefit of relocation BNs goes beyond the identification and quantification of the factors influencing the success of relocations and population viability. They equip conservationists with a powerful communication tool in their negotiations with land and livestock owners, which is key to the long-term survival of cheetahs in southern Africa. Importantly, the IBNDC provides the ecological modeller with a methodological process that combines several BN design frameworks to facilitate the development of a BN in a multi-expert and multi-field domain.     

Adjusting the economy to the new energy realities of the second half of the age of oil

Our research indicates that, due to the depletion of conventional, and hence cheap, crude oil supplies (i.e. peak oil), increasing the supply of oil in the future would require exploiting lower quality resources (i.e. expensive), and thus will most likely occur only at high prices. This situation creates a system of feedbacks where economic growth, which requires more oil, would require high oil prices that will undermine that economic growth. We conclude that the economic growth of the past 40 years is unlikely to continue unless there is some remarkable change in how we manage our economy.     

Nitrogen dynamics in an Australian semiarid grassland soil

We conducted a four-week laboratory incubation of soil from a Themeda triandra Forsskal grassland to clarify mechanisms of nitrogen (N) cycling processes in relation to carbon (C) and N availability in a hot, semiarid environment. Variation in soil C and N availability was achieved by collecting soil from either under tussocks or the bare soil between tussocks, and by amending soil with Themeda litter. We measured N cycling by monitoring: dissolved organic nitrogen (DON), ammonium (NH4+), and nitrate (NO3-) contents, gross rates of N mineralization and microbial re-mineralization, NH4+ and NO3- immobilization, and autotrophic and heterotrophic nitrification. We monitored C availability by measuring cumulative soil respiration and dissolved organic C (DOC). Litter-amended soil had cumulative respiration that was eightfold greater than non-amended soil (2000 compared with 250 microg C/g soil) and almost twice the DOC content (54 compared with 28 microg C/g soil). However, litter-amended soils had only half as much DON accumulation as non-amended soils (9 compared with 17 microg N/g soil) and lower gross N rates (1-4 compared with 13-26 microg N x [g soil](-1) x d(-1)) and NO3- accumulation (0.5 compared with 22 microg N/g soil). Unamended soil from under tussocks had almost twice the soil respiration as soil from between tussocks (300 compared with 175 microg C/g soil), and greater DOC content (33 compared with 24 microg C/g soil). However, unamended soil from under tussocks had lower gross N rates (3-20 compared with 17-31 microg N x [g soil](-1) d(-1)) and NO3- accumulation (18 compared with 25 microg N/g soil) relative to soil from between tussocks. We conclude that N cycling in this grassland is mediated by both C and N limitations that arise from the patchiness of tussocks and seasonal variability in Themeda litterfall. Heterotrophic nitrification rate explained >50% of total nitrification, but this percentage was not affected by proximity to tussocks or litter amendment. A conceptual model that considers DON as central to N cycling processes provided a useful initial framework to explain results of our study. However, to fully explain N cycling in this semiarid grassland soil, the production of NO3- from organic N sources must be included in this model.     

Can we meet targets for biofuels and renewable energy in transport given the constraints imposed by policy in agriculture and energy?

The deployment of biofuels is significantly affected by policy in energy and agriculture. In the energy arena, concerns regarding the sustainability of biofuel systems and their impact on food prices led to a set of sustainability criteria in EU Directive 2009/28/EC on Renewable Energy. In addition, the 10% biofuels target by 2020 was replaced with a 10% renewable energy in transport target. This allows the share of renewable electricity used by electric vehicles to contribute to the mix in achieving the 2020 target. Furthermore, only biofuel systems that effect a 60% reduction in greenhouse gas emissions by 2020 compared with the fuel they replace are allowed to contribute to meeting the target. In the agricultural arena, cross-compliance (which is part of EU Common Agricultural Policy) dictates the allowable ratio of grassland to total agricultural land, and has a significant impact on which biofuels may be supported. This paper outlines the impact of these policy areas and their implications for the production and use of biofuels in terms of the 2020 target for 10% renewable transport energy, focusing on Ireland. The policies effectively impose constraints on many conventional energy crop biofuels and reinforce the merits of using biomethane, a gaseous biofuel. The analysis shows that Ireland can potentially satisfy 15% of renewable energy in transport by 2020 (allowing for double credit for biofuels from residues and ligno-cellulosic materials, as per Directive 2009/28/EC) through the use of indigenous biofuels: grass biomethane, waste and residue derived biofuels, electric vehicles and rapeseed biodiesel.