dc.contributor.author | Negus, Peter | |
dc.contributor.author | Blessing, Joanna | |
dc.contributor.author | Clifford, Sara | |
dc.contributor.author | Marshall, Jonathan | |
dc.date.accessioned | 2020-09-08T02:48:54Z | |
dc.date.available | 2020-09-08T02:48:54Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 1448-6563 | |
dc.identifier.doi | 10.1080/14486563.2020.1750494 | |
dc.identifier.uri | http://hdl.handle.net/10072/397179 | |
dc.description.abstract | Ecosystem monitoring often fails to provide the right information to evaluate and guide environmental stewardship due to a lack of diagnostic capacity, long-term operational resources, explicit monitoring objectives and rigorous sampling designs. Our objective is to describe a monitoring framework that addresses these failures by including causative conceptual models and the concepts of adaptive monitoring and management. Resources are rarely available to monitor all ecosystem components, so identifying priorities is vital for the success of a monitoring program. An ecological risk assessment combining available information and expert opinion on threats and their consequences to the ecosystem can be used to prioritise monitoring and identify explicit objectives. A Pressure-Stressor-Response conceptual model forms the causative understanding of the ecosystem and the model components underpin the factors in the risk assessment. In this way, field sampling can validate the priority of ecosystem threats; provide information for refinement of conceptual understandings and guide efficient management activity. Repeated risk assessments using updated data and information can identify successful management and the increase and establishment of threats. Updated risk assessments can change threat priorities and therefore monitoring and assessment hypotheses and objectives can change. This ability to change underlies the concepts of adaptive monitoring and management. | |
dc.description.peerreviewed | Yes | |
dc.language | English | |
dc.language.iso | eng | |
dc.publisher | Taylor & Francis Group | |
dc.relation.ispartofpagefrom | 224 | |
dc.relation.ispartofpageto | 240 | |
dc.relation.ispartofissue | 2 | |
dc.relation.ispartofjournal | Australasian Journal of Environmental Management | |
dc.relation.ispartofvolume | 27 | |
dc.subject.fieldofresearch | Environmental sciences | |
dc.subject.fieldofresearch | Human society | |
dc.subject.fieldofresearchcode | 41 | |
dc.subject.fieldofresearchcode | 44 | |
dc.subject.keywords | Science & Technology | |
dc.subject.keywords | Life Sciences & Biomedicine | |
dc.subject.keywords | River health | |
dc.subject.keywords | Ecology | |
dc.title | Adaptive monitoring using causative conceptual models: assessment of ecological integrity of aquatic ecosystems | |
dc.type | Journal article | |
dc.type.description | C1 - Articles | |
dcterms.bibliographicCitation | Negus, P; Blessing, J; Clifford, S; Marshall, J, Adaptive monitoring using causative conceptual models: assessment of ecological integrity of aquatic ecosystems, Australasian Journal of Environmental Management, 2020, 27 (2), pp. 224-240 | |
dc.date.updated | 2020-09-08T02:47:49Z | |
gro.hasfulltext | No Full Text | |
gro.griffith.author | Marshall, Jonathan C. | |