Using a state-and-transition approach to manage endangered Eucalyptus albens (White Box) woodlands.
Eucalyptus albens (White Box) woodlands are among the most poorly conserved and threatened communities in Australia. Remnants are under further threat from stock grazing, deteriorating soil conditions, weed invasion, and salinity. There is an urgent need to restore degraded White Box and other woodland ecosystems to improve landscape function. However, there is still a poor understanding of the ecology of degraded woodland ecosystems in fragmented agricultural landscapes, and consequently a lack of precise scientific guidelines to manage these ecosystems in a conservation context. State and Transition Models (STMs) have received a great deal of attention, mainly in rangeland applications, as a suitable framework for understanding the ecology of complex ecosystems and to guide management. We have developed a STM for endangered White Box woodlands and discuss the merits of using this approach for land managers of other endangered ecosystems. An STM approach provides a greater understanding of the range of states, transitions, and thresholds possible in an ecosystem, and provides a summary of processes driving the system. Importantly, our proposed STM could be used to clarify the level of "intactness" of degraded White Box woodland sites, and provide the impetus to manage different states in complementary ways, rather than attempting to restore ecosystems to one pristine stable state. We suggest that this approach has considerable potential to integrate researcher and land manager knowledge, focus future experimental studies, and ultimately serve as a decision support tool in setting realistic and achievable conservation and restoration goals.
Spooner
Peter G
PG
School of Environmental and Information Sciences, Charles Sturt University, PO Box 789, Albury, NSW, 2640, Australia. pspooner@csu.edu.au
Allcock
Kimberly G
KG
D003247:Conservation of Natural Resources / Q000379:methods*; D017753:Ecosystem; D005052:Eucalyptus / Q000254:growth & development*; D008962:Models, Theoretical