Tropical Savannas CRC > Research > CRC Research 2001-2008 > Landscape Ecology > Predicting outcomes of management

Predicting outcomes of management

Project Leaders: John Ludwig and John Gross, CSIRO Sustainable Ecosystems

Full title: Predicting outcomes of savanna management: ecological interactions and socio-economic trade-offs across landscape scales

Project 1.1.1: Completed

Summary | Tools for different time and spatial scales | Contribution to TS–CRC research themes | Trade-offs under investigation | Outputs | Project team

Summary

A key challenge for the Tropical Savannas Management CRC (TS–CRC) is to predict the ecological and socio-economic consequences of different land-management decisions on savanna landscape health and the people of the savannas.

Land management can strongly influence and change savanna landscape processes and functions. For example, grazing and fire can reduce the size of vegetation patches occurring on a hillslope, which then increases run-off and soil erosion. These changes can, in turn, alter populations in these patches (e.g., loss of plants, termites and earthworms that create soil biopores) and biotic communities in the landscape (e.g., loss of bush-tucker plants, invasion of weeds and ferals).

This makes these landscapes less attractive and useful to people. While we can currently predict the ecological and socio-economic consequences of some specific savanna management actions, effective decision making will rely on a much greater understanding of the trade-offs between many different alternative actions over a range of landscape and management scales.

Predicting outcomes for trade-offs between different savanna management options requires computer simulation modelling tools. These tools allow us to explore the likely response of savanna systems to management options and environmental factors that are not feasible by experimentation.

These savanna system simulation models need to be robust, that is, they need to be built on solid knowledge so that we have confidence in their predictions.

Some simulation tools have already been developed during the first round of the CRC. Knowledge gained through the new landscape ecology projects will help improve these tools. In addition, there is a need to develop new models to integrate biophysical, ecological, and socio-economic dynamics at the catchment/regional scale. New tools are needed because the capabilities of existing simulation tools are too limited.

To build these tools, we will integrate new knowledge about the savannas acquired from new projects within the TS–CRC, as well as information from earlier CRC studies. This will enable us to build a predictive understanding into these tools.

This predictive understanding must include those basic ecological processes that sustain the functions of healthy savanna landscapes at fine scales, such as how vegetation patches function to retain resources on hillslopes. Simulation tools will be used to test and develop savanna management options and guidelines. These guidelines will be tested, developed and applied at enterprise, catchment and regional scales to address ecological, economic and social issues.

Tools for different time and spatial scales

Different simulation tools will be needed to explore trade-offs at different time and spatial scales. Below is a list of simulation models that will be applicable at the following scales:

  1. Patch/hillslope to paddock spatial scales—years to decade time scales
    Savanna-Au (a version of 4b specifically developed for Australian savanna landscapes), are spatially-explicit, process-based, simulation models designed to evaluate system responses for scenarios over relatively fine spatial scales (a few km2) and short time periods (e.g., 25 years). The GRASP model, a well tested, point-based, forage production model is also applicable at these scales, and has been linked with cattle herd and economic models (i.e., HerdGRASP).

  2. Paddock to sub-catchment spatial scales—decades to centuries time scales
    Arena is a plant traits simulation model designed to explore how specific vegetation attributes (annual vs. perennial; palatable vs. unpalatable) change over medium to long time periods in response to grazing impacts and environmental fluctuations. The objective of the Arena model is to better understand concepts and processes behind the dramatic changes that have been observed in plant species composition on lands grazed by livestock. The Arena model will be used, for example, to address medium to long-term grazing impact questions.Flames is a fire ecology simulation model designed to explore the impact of different fire regimes on savanna vegetation, particularly trees.
    The aim of Flames is to better understand the processes controlling why savanna tree populations are declining in some areas, but thickening in others, and how wildfires impact on fluxes of carbon and other greenhouse gases (see list of questions, above). Flames also aims to explore how people can better use fire to achieve different vegetation management goals such as the control of exotic woody weeds.
  3. Property to region/catchment spatial scales—decades to centuries time scales
    The Arena and Flames models have been linked to animal production and economics models (HerdGRASP and RiskHerd) to explore the impacts of grazing and fire on property economics and regional viability. Building on these tools, a new enterprise-scale model will be built to address a number of broad-scale, long-term savanna land use and planning questions.

Contribution to TS–CRC research themes

This project is strongly linked to TS–CRC projects in Themes 1 and 2 (Fig. 1). Basic knowledge on savanna ecology gained from Theme 1 projects will be used to improve our predictive tools (e.g., simulation models), while Theme 2 projects on savanna management will provide the critical scenarios that need to be explored with these tools. Predicted outcomes from these explorations will be useful for regional planning processes (Theme 3). Management recommendations resulting from these evaluations and planning processes will be communicated to our TSM-CRC clients and stakeholders (Theme 4).

Examples of trade-offs under investigation

The following questions are some examples of the types of trade-offs that will be explored by this project in direct collaboration with other TS–CRC projects.

Can fire and grazing regimes be manipulated to control savanna woody thickening and the invasion of exotic woody weeds?

These management trade-off predictions will use Savanna.Au and Flames simulation tools built on existing knowledge and new knowledge from current TS–CRC projects (e.g., 1.1.3, 1.1.4, and  1.2.3), Weeds CRC projects and other relevant studies.

Can patch burning effectively regulate the distribution of cattle grazing within large paddocks, such as those on properties in the VRD and the Burdekin?

This question will be addressed using Savanna.Au and existing knowledge and new findings from developing TS–CRC projects (e.g., Best Practice Project) and collaborations with the pastoral industry

How do different combinations of fire and grazing regimes and tree clearing manipulations alter runoff and sediment yields from hillslopes, watersheds and catchments?

Predicting these outcomes will require existing knowledge and that from new TS–CRC projects (e.g., 1.1.3 and 1.1.4) and collaborations with the Catchment Hydrology CRC.

Do certain fire regimes lead to long-term losses in soil carbon and nitrogen?

This question will be answered using tools such as the Flames model will depend on existing knowledge and that gained from new TS–CRC projects (e.g. 1.1.3, 1.1.4 and 2.1.4) and collaboration with the Carbon Accounting CRC.

How are current fire regimes and risks altered by the invasion of exotic pasture grasses?

These predictions will use existing knowledge and that from a new TS–CRC project being developed in collaboration with the Weeds CRC).

How are invertebrate, vertebrate and plant populations affected by different combinations of grazing and fire in savanna landscapes?

Predicting these trade-offs will require new tools built on existing knowledge  and that from TS–CRC projects (e.g., 1.2.3 & 2.1.2).]

Are regional land-use changes and climatic fluctuations likely to shift the way enterprises such as pastoralism and tourism develop and maintain their viability?

Addressing this complex question will require new tools and knowledge (e.g., TS-CRC projects 3.1.2, 3.2.1, & 3.2.3).

How is rural community ‘health’ or ‘well-being’ influenced by trends and trade-offs in ecological sustainability, economic profitability and social desirability?

Predicting these outcomes will also require new concepts, tools and knowledge under development in other CRC projects.

What are the most efficient and effective approaches for applying the predicted outcomes from this collaborative and integrative project?

This will require new TS-CRC tools and techniques in regional planning and human capability development.

Outputs

In general, outputs and deliverables will contribute to the CRC’s Key Result Areas (KRA) and include:

  • Predictions of the impact of, and trade-offs between, savanna-management strategies (e.g., between fire and grazing) on woody thickening and exotic weed invasions; (KRA 1 – healthy landscapes: predictive models of landscape function and the impact of interventions)
  • Predictions of the likely impacts of, and trade-offs between, different savanna managements on conserving specific flora and fauna while maintaining socio-economic viability at property to regional scales; (KRA 1 – healthy landscapes: predictive models of landscape function and the impact of interventions)
  • Guidelines for maintaining basic landscape processes and functions (i.e. conserving resources and habitats) at the enterprise scale while achieving specific land use goals; (KRA 1 – healthy landscapes: indicators and attributes of health)
  • Guidelines for managing catchments and regions that include a mix of land uses (e.g., Aboriginal, defense, farming, mining, pastoral and tourism) to improve natural resources (e.g., stream water quality) and economic and social conditions for people (e.g., viable communities); (KRA 3 – viable and socially desirable regions)
  • Contributions to general TS–CRC communication, learning packages, the education of postgraduates (e.g., a modeller with PhD qualifications).

Project team

Core Staff:

John Gross, CSIRO SE
John Ludwig, CSIRO SE
Adam Liedloff CSIRO SE
PhD Student, JCU
Malcolm Hodgen CSIRO LW
Peter Allan QDPI
Robert Eager CSIRO SE

Collaborating Staff

Peter O’Reagain, QDPI
Neil MacLeod, CSIRO SE
Garry Cook, CSIRO SE
Mark Stafford Smith, CSIRO SE
Neil MacDonald, NT DBIF
John Woinarski, PWCNT

Contacts

Dr Garry Cook
Principal Scientist
CSIRO Sustainable Ecosystems
Tel: 08 8944 8427

Fax: 08 8944 8444

PMB 44
WINNELLIE, NT 0822


Dr John Gross
Ecologist
Tel: (970) 267-2111

Fax: (970) 225 3585

1201 Oakridge Drive, Suite 200
FT COLLINS, COLORADO, 80525-5589 USA


Dr John Ludwig
Theme Leader, TS-CRC
Tel: 07 4091 8837

Fax: 07 4091 8888

PO Box 780
ATHERTON, QLD 4883


Contact:

Dr John Ludwig
Theme Leader, TS-CRC
Tel: 07 4091 8837

Fax: 07 4091 8888

PO Box 780
ATHERTON, QLD 4883