Adapting to climate change: A risk assessment and decision making framework for managing groundwater dependent ecosystems with declining water levels. Supporting document 2: Assessing risks to groundwater dependent wetland ecosystems in a drying climate:
|Title||Adapting to climate change: A risk assessment and decision making framework for managing groundwater dependent ecosystems with declining water levels. Supporting document 2: Assessing risks to groundwater dependent wetland ecosystems in a drying climate:|
|Year of Publication||2013|
|Authors||Sommer, B, McGuinness, S, Froend, R, Horwitz, P|
|Institution||National Climate Change Adaptation Research Facility|
Groundwater dependent wetland ecosystems on the Gnangara Groundwater System (GGS) have been under threat from a drying climate, and compounding stressors such as groundwater abstraction and other landuses, for over three decades. The management of these ecosystems depends on the ability to predict responses and assess risks posed by projected climate and landuse scenarios. Prediction for adaptation and adaptive management requires an approach that enables resource managers to adapt their conservation strategies to minimise the impacts from other – controllable - stressors to these ecosystems. The aim of this research was to develop a methodology for predicting risks to groundwater dependent wetland ecosystems in a drying climate. The methodology applies specifically to data-rich situations where the objectives are to (1) facilitate adaptation to climate change and climate change-related factors, and (2) to define risk in terms of ecosystem function. We have demonstrated the approach on a case study from the GGS where aquatic macroinvertebrates and littoral/supra-littoral vegetation were used as surrogates for wetland ecosystem function. Because the focus of this research was prediction and risk assessment, the analytical steps of the methodology are presented within the context of a risk assessment framework. Key features of the methodology, which is summarised in Table I, are:
1. Applies to data rich situations (e.g. long-term monitoring data are available);
2. Incorporates expert knowledge to estimate the inherent complexities that could not be derived from the quantitative data;
3. Uses a combination of multivariate statistical methods (therefore requires some statistical expertise) in a sequence of steps that fit into the context of a risk assessment framework;
4. Is designed to facilitate adaptation to climate change by setting targeted objectives;
5. Uses the concept of species functional groups, whereby:
- the methodology becomes geographically transferable
- functional responses can be directly related to adaptation
- functional characteristics can be directly linked with the hazard
- biotic response is simplified and contextualised to reflect the functional relationship with the hazard that is driving the change, which facilitates the prediction of future impacts.
6. Can be used to spatially represent risk by mapping different climate and landuse scenarios and associated risk.