Semi‐arid grazing systems and climate change: a survey of present modelling potential and future needs

Abstract

Summary1. Sustainable land use under climate change requires detailed knowledge of the system dynamics. This applies particularly for the management of domestic livestock in semiarid and arid grazing systems, where the risk of degradation is high and likely climate change may have a strong impact. A suitable way to assess potential future trends of these complex systems is through the application of simulation models. 2. We reviewed 41 models published between 1995 and 2005 simulating semi-arid and arid livestock grazing systems. The models were categorized according to the model aim and type, their temporal and spatial scale, and several indicators of model complexity. Additionally, we developed a list of model requirements for adequately simulating the effects of climate change. Based on these requirements, we evaluated the potential of current models to simulate impacts of climate change and determine important shortcomings.3. Three general model types could be distinguished, namely state and transition, difference and differential equation, and rule-based models. Over time, we found that the number of models aiming to improve management strategies increased, while there were fewer models that aimed to understand system dynamics. This was accompanied by a trend to simplify model descriptions of hydrological relationships. 4. Important shortcomings of current models included the impact of increased CO 2 levels on plant productivity and the ability to resolve changes in intra-annual precipitation patterns. The consideration of both external drivers is crucial under climate change, hence sustainable long-term decision making is currently lacking important information. 5. Synthesis and applications . Sustainable livestock management in semi-arid and arid systems requires knowledge about effects of future climate change to adjust livestock density adequately. Producers' experiences from current weather conditions are not necessarily transferable to future conditions, thus models could help to support management. However, an analysis of current models has shown that few existing models are able to assess the impacts of the predicted climate change. Therefore, we call for the development of new dynamic grazing models that provide land managers with the necessary tools to face the threat of future climate changes.

Threshold behaviour in hydrological systems as (human) geo-ecosystems: manifestations, controls, implications

“…Vegetation, when abundant, is often arranged into patterns that consist of patches with strong plant cover that alternate with low-cover or bare soil patches (Tietjen and Jeltsch, 2007;Tietjen et al, 2009b). Typical patterns are either characterised as spotted or stippled, consisting of dense irregularly shaped vegetation clusters that are surrounded by bare soil .…”

“…However, a strong and persistent disturbance might seriously endanger the architecture of these systems (Tietjen and Jeltsch, 2007) and their ability to minimize the export of water, sediments and nutrients. Leaky vegetation structures, often caused by grazing pressures (Rietkerk and van de Koppel, 1997;Rietkerk et al, 2000Rietkerk et al, , 2002Kefi et al, 2007), are less efficient in trapping runoff and sediments (Walker et al, 1981(Walker et al, , 1999Ludwig et al, 2004Ludwig et al, , 2005.…”

“…Will an expected rainfall event trigger a landslide (van Asch et al, 1996(van Asch et al, , 1999Boogard et al, 2002;, or not? Will a higher disturbance due to enhanced grazing exceed the resilience of a savannah ecosystem (Rietkerk and van de Koppel, 1997;Kefi et al, 2007;Tietjen and Jeltsch, 2007), or not? To address such questions we must better understand whether the system of interest is in a critical state, which means whether the expected forcing/boundary conditions/ disturbance could be strong enough to push the system over the threshold ( Fig.…”

“…Threshold behaviour is also discussed in the context of the long-term development of soil structures and landforms (Newson and Newson, 2000;Phillips, 2004Phillips, , 2006, fluvial morphology (Willgoose et al, 1991a(Willgoose et al, , 1991bGrant, 1997;Piégay et al, 2000;Fryirs et al, 2007;Harnischmacher, 2007), rill and gully erosion (Bull and Kirkby, 1997;Kirkby et al, 2003;Poesen et al, 2003;Shao et al, 2005;Parkner et al, 2006Parkner et al, , 2007, badlands formation (CalvoCases and Harvey, 1996;Howard, 1997;Faulkner et al, 2000Faulkner et al, , 2003Boardman et al, 2003;Faulkner, 2008), and formation and growth of channel networks (Willgoose et al, 1991a(Willgoose et al, , 1991bRinaldo et al, 1996;Rodriguez-Iturbe et al, 1998;Rodriguez-Iturbe and Rinaldo, 2001). Threshold behaviour and feedbacks between vegetation patterns and redistribution of abiotic resources determine the resilience of geoecosystems in semi-arid regions (Grant, 1997;Piégay et al, 2000;Wilcox et al, 2003a;Wilcox and Newman, 2005;Fryirs et al, 2007;Saco et al, 2007;Tietjen and Jeltsch, 2007), grassland establishment (Baer et al, 2005;Baer and Blair, 2008), regeneration of forests in floodplain areas (Dufour and Piegay, 2008), plant diversity in wetlands …”

Application of Geographic Information Systems in Studying the Relationship between Stock Routes Changes with Water and Pasture Availability for Livestock under a Changing Climate Conditions: A Case of Ilemela and Magu Districts in Mwanza Region-Lake Victoria Basin, Tanzania

“…which forms nearly 30% of the world's land surface [3]. For the LVB (Lake Victoria Basin), more than 60% of its area is covered by rangeland which contributes 10-20% of the GDP (Gross Domestic Product) of East African economies [4].…”