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Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation.

Kilpatrick AD, Lewis MM, Ostendorf B - PLoS ONE (2015)

Bottom Line: We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields) in the study region according to effectiveness of grazing management.While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities.These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged.

View Article: PubMed Central - PubMed

Affiliation: School of Biological Sciences, The University of Adelaide, Adelaide, Australia.

ABSTRACT
A need exists in arid rangelands for effective monitoring of the impacts of grazing management on vegetation cover. Monitoring methods which utilize remotely-sensed imagery may have comprehensive spatial and temporal sampling, but do not necessarily control for spatial variation of natural variables, such as landsystem, vegetation type, soil type and rainfall. We use the inverse of the red band from Landsat TM satellite imagery to determine levels of vegetation cover in a 22,672 km(2) area of arid rangeland in central South Australia. We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields) in the study region according to effectiveness of grazing management. The cross-fence comparison methodology generates and solves simultaneous equations of the relationship between each paddock and all other paddocks, derived from pairs of cross-fence sample points. We compare this ranking from two image dates separated by six years, during which management changes are known to have taken place. Changes in paddock rank resulting from the cross-fence comparison method show strong correspondence to those predicted by grazing management in this region, with a significant difference between the two common management types; a change from full stocking rate to light 20% stocking regime (Major Stocking Reduction) and maintenance of full 100% stocking regime (Full Stocking Maintained) (P = 0.00000132). While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities. These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged. For the first time, this method allows us to rank non-adjacent paddocks in a rangeland region relative to each other, while controlling for natural spatio-temporal variables such as rainfall, soil type, and vegetation community distributions, due to the nature of the cross-fence experimental design, and the spatially comprehensive data available in satellite imagery. This method provides a potential tool to aid land managers in decision making processes, particularly with regard to stocking rates.

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Schematic of expected and possible changes amongst the regimes.
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pone.0142742.g006: Schematic of expected and possible changes amongst the regimes.

Mentions: Fig 6 presents the conceptual framework for interpretation of paddock ranks and rank changes between the two dates. Possible rank changes between the first and second image date (y-axis) are compared with ranking on the first image date (x-axis). A limited number of changes in paddock rank are possible. Paddocks with the best condition on the first date (Fig 6; category A) can either not change, or decrease in rank. Paddocks with intermediate ranks can either decrease or increase in rank (Fig 6; category B), while the paddocks with the lowest ranks (poorest condition) on the first date can only stay the same or improve by the second date (Fig 6; category C). With four different management regimes in place between the two dates, we predict that those with the better management will either stay the same or increase in rank relative to those with poor management.


Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation.

Kilpatrick AD, Lewis MM, Ostendorf B - PLoS ONE (2015)

Schematic of expected and possible changes amongst the regimes.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4643980&req=5

pone.0142742.g006: Schematic of expected and possible changes amongst the regimes.
Mentions: Fig 6 presents the conceptual framework for interpretation of paddock ranks and rank changes between the two dates. Possible rank changes between the first and second image date (y-axis) are compared with ranking on the first image date (x-axis). A limited number of changes in paddock rank are possible. Paddocks with the best condition on the first date (Fig 6; category A) can either not change, or decrease in rank. Paddocks with intermediate ranks can either decrease or increase in rank (Fig 6; category B), while the paddocks with the lowest ranks (poorest condition) on the first date can only stay the same or improve by the second date (Fig 6; category C). With four different management regimes in place between the two dates, we predict that those with the better management will either stay the same or increase in rank relative to those with poor management.

Bottom Line: We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields) in the study region according to effectiveness of grazing management.While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities.These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged.

View Article: PubMed Central - PubMed

Affiliation: School of Biological Sciences, The University of Adelaide, Adelaide, Australia.

ABSTRACT
A need exists in arid rangelands for effective monitoring of the impacts of grazing management on vegetation cover. Monitoring methods which utilize remotely-sensed imagery may have comprehensive spatial and temporal sampling, but do not necessarily control for spatial variation of natural variables, such as landsystem, vegetation type, soil type and rainfall. We use the inverse of the red band from Landsat TM satellite imagery to determine levels of vegetation cover in a 22,672 km(2) area of arid rangeland in central South Australia. We interpret this wealth of data using a cross-fence comparison methodology, allowing us to rank paddocks (fields) in the study region according to effectiveness of grazing management. The cross-fence comparison methodology generates and solves simultaneous equations of the relationship between each paddock and all other paddocks, derived from pairs of cross-fence sample points. We compare this ranking from two image dates separated by six years, during which management changes are known to have taken place. Changes in paddock rank resulting from the cross-fence comparison method show strong correspondence to those predicted by grazing management in this region, with a significant difference between the two common management types; a change from full stocking rate to light 20% stocking regime (Major Stocking Reduction) and maintenance of full 100% stocking regime (Full Stocking Maintained) (P = 0.00000132). While no paddocks had a known increase in stocking rate during the study period, many had a reduction or complete removal in stock numbers, and many also experienced removals of pest species, such as rabbits, and other ecosystem restoration activities. These paddocks generally showed an improvement in rank compared to paddocks where the stocking regime remained relatively unchanged. For the first time, this method allows us to rank non-adjacent paddocks in a rangeland region relative to each other, while controlling for natural spatio-temporal variables such as rainfall, soil type, and vegetation community distributions, due to the nature of the cross-fence experimental design, and the spatially comprehensive data available in satellite imagery. This method provides a potential tool to aid land managers in decision making processes, particularly with regard to stocking rates.

Show MeSH
Related in: MedlinePlus