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Synthesising the effects of land use on natural and managed landscapes

Overview of attention for article published in Science of the Total Environment, April 2015
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Title
Synthesising the effects of land use on natural and managed landscapes
Published in
Science of the Total Environment, April 2015
DOI 10.1016/j.scitotenv.2015.04.070
Pubmed ID
Authors

Richard Thackway, Alison Specht

Abstract

To properly manage our natural and managed landscapes, and to restore or repair degraded areas, it is important to know the changes that have taken place over time, particularly with respect to land use and its cumulative effect on ecological function. In common with many places in the world, where the industrial revolution resulted in profound changes to land use and management, Australia's landscapes have been transformed in the last 200years. Initially the VAST (Vegetation Assets, States and Transitions) system was developed to describe and map changes in vegetation over time through a series of condition states or classes; here we describe an enhancement to the VAST method which will enable identification of the factors contributing to those changes in state as a result of changes in management practice. The 'VAST-2' system provides a structure in which to compile, interpret and sequence a range of data about past management practices, their effect on site and vegetation condition. Alongside a systematic chronology of land use and management, a hierarchy of indices is used to build a picture of the condition of the vegetation through time: 22 indicators within ten criteria representing three components of vegetation condition-regenerative capacity, vegetation structure and species composition-are scored using information from a variety of sources. These indicators are assessed relative to a pre-European reference state, either actual or synthetic. Each component is weighted proportionally to its contribution to the whole, determined through expert opinion. These weighted condition components are used to produce an aggregated transformation score for the vegetation. The application of this system to a range of sites selected across Australia's tropical, sub-tropical and temperate bioregions is presented, illustrating the utility of the system. Notably, the method accommodates a range of different types of information to be aggregated.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Argentina 1 2%
Unknown 40 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 29%
Student > Ph. D. Student 5 12%
Student > Doctoral Student 4 10%
Professor 4 10%
Student > Bachelor 3 7%
Other 6 14%
Unknown 8 19%
Readers by discipline Count As %
Environmental Science 13 31%
Agricultural and Biological Sciences 5 12%
Social Sciences 3 7%
Engineering 2 5%
Business, Management and Accounting 1 2%
Other 5 12%
Unknown 13 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 May 2015.
All research outputs
#17,285,668
of 25,373,627 outputs
Outputs from Science of the Total Environment
#19,166
of 29,625 outputs
Outputs of similar age
#169,659
of 279,953 outputs
Outputs of similar age from Science of the Total Environment
#109
of 174 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 29,625 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 279,953 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 174 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.