Investigating Grazing Intensity and Range Condition of Grasslands in Northeastern Kansas Using Landsat Thematic Mapper Data

Peterson, D. L.; Price, Kevin P.; Martinko, Edward A.

doi:10.1080/10106040208542250

Cited by 6 publications

(2 citation statements)

References 29 publications

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“…5). Overgrazing in some parts of the study area, especially in the lowlands, has significantly changed the species composition by reducing species richness (especially the palatable species) and increasing surface bare soil cover (Peterson et al, 2002;Cesa and Paruelo, 2011). Specifically, under overgrazing stress, the domination of palatable species in the study area such as Artemisia sieberi was gradually replaced by unpalatable species such as Scariola orientalis, Lunea spinose, and Noaea mucronata.…”

Section: Discussionmentioning

confidence: 98%

Vegetation composition differentiation and species-environment relationships in the northern part of Isfahan Province, Iran

et al. 2017

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A considerable proportion of Iran's territory is covered with arid and semi-arid rangelands and mismanagement and overexploitation of those rangelands have resulted in serious ecological degradation. Thus, the need is pressing to examine the present species composition and the relationships with environmental factors for providing the needed scientific references to species conservation and ecological rehabilitation efforts. The aims of this study were to examine the species composition and to delineate the most important factors influencing the distributions of plant species and groups in the northern rangelands of Isfahan Province (Iran) using two-way indicator species analysis (TWINSPAN), detrended correspondence analysis (DCA), principal component analysis (PCA), and canonical correspondence analysis (CCA). Field investigations were conducted in the growing season of 2014 using stratified random method in 22 homogeneous sampling units. In total, 75 plant species belonging to 52 genera and 19 families were identified. The most important families were Asteraceae and Papilionaceae, the most important genera were Astragalus, Cousinia, and Acanthophyllum, and the most important species were Artemisia aucheri and Artemisia sieberi. Plant species were classified into 10 groups using TWINSPAN. DCA was used to estimate the magnitude of changes in species composition along the first two ordination axes to provide gradient length estimations for PCA and CCA ordinations. The first three PCA axes and the first three CCA axes demonstrated similar cumulative percentage of variance, indicating that the environmental factors (selected by PCA) used in CCA ordination were acceptable for explaining the species composition and the distributions. CCA ordination showed that the first axis was closely related to elevation, slope, surface bare soil cover, surface litter cover, gravel proportion, organic matter, total nitrogen, CaCO 3 content, and grazing intensity and that the second axis was closely related to sand proportion, silt proportion, clay proportion, and saturation percentage. Among these factors, elevation was the most effective factor to separate the plant groups and grazing was the major cause of rangeland degradation.

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Section: Discussionmentioning

confidence: 98%

Vegetation composition differentiation and species-environment relationships in the northern part of Isfahan Province, Iran

et al. 2017

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“…Further, quantitative maps of AGB are an important input to support forest and landscape management [2], [3], to understand deforestation impact on carbon release and global warming [4], to assess productivity of forested areas in relation to forest composition [5], and in view of specific forest management practices [1], [6]. Since AGB is an indicator for quantity and quality of forage, it is considered relevant information to study animal ecology, i.e., herbivore behaviors [7] and grazing intensities [8], [9]. Further, grassland biomass has a high potential to become flammable during an extended dry season [10], and therefore accurate AGB estimates are relevant input for fire risk assessment [11] and carbon cycle modeling.…”

Section: Introductionmentioning

confidence: 99%

Mapping Alpine Aboveground Biomass From Imaging Spectrometer Data: A Comparison of Two Approaches

Fatehi

Damm

Schweiger

et al. 2015

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Aboveground biomass (AGB) of terrestrial ecosystems is an important constraint of global change and productivity models and used to assess carbon stocks and thus the contribution of vegetated ecosystems to the global carbon cycle. Although an indispensable and important requirement for decision makers, coherent and accurate estimates of grassland and forest AGB especially in complex environments are still lacking. In this study, we aim to assess the capability of two strategies to map grassland and forest AGB in a complex alpine ecosystem, i.e., using a discrete as well as a continuous field (CF) mapping approach based on imaging spectroscopy (IS) data. In situ measurements of grassland and forest AGB were acquired in the Swiss National Park (SNP) to calibrate empirical models and to validate AGB retrievals. The selection of robust empirical models considered all potential two narrow-band combinations of the simple ratio (SR) and the normalized difference vegetation index (NDVI) generated from Airborne Prism Experiment (APEX) IS data and in situ measurements. We found a narrow-band SR including spectral bands from the short-wave infrared (SWIR) (1689 nm) and near infrared (NIR) (851 nm) as the best regression model to estimate grassland AGB. Forest AGB showed highest correlation with an SR generated from two spectral bands in the SWIR (1498, 2112 nm). The applied accuracy assessment revealed good results for estimated grassland AGB using the discrete mapping approach [R 2 of 0.65, mean RMSE (mRMSE) of 0.91 t · ha −1 , and mean relative RMSE (mrRMSE) of 26%]. The CF mapping approach produced a higher R 2 ( R 2 = 0.94 ), and decreased the mRMSE and the mrRMSE to 0.55 t · ha −1 and 15%, respectively. For forest, the discrete approach predicted AGB with an R 2 value of 0.64, an mRMSE of 67.8 t · ha −1 , and an mrRMSE of 25%. The CF mapping approach improved the accuracy of forest AGB estimation with R 2 = 0.85 , mean RMSE = 55.85 t · ha −1 , and mean relative RMSE = 21%. Our results indicate that, in general, both mapping approaches are capable of accurately mapping grassland and forest AGB in complex environments using IS data, whereas the CF-based approach yielded higher accuracies due to its capability to incorporate subpixel information (abundances) of different land cover types.

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Effects of drought on plant parameters of different rangeland types in Khansar region, Iran

et al. 2019

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Investigating Grazing Intensity and Range Condition of Grasslands in Northeastern Kansas Using Landsat Thematic Mapper Data

Cited by 6 publications

References 29 publications

Vegetation composition differentiation and species-environment relationships in the northern part of Isfahan Province, Iran

Vegetation composition differentiation and species-environment relationships in the northern part of Isfahan Province, Iran

Mapping Alpine Aboveground Biomass From Imaging Spectrometer Data: A Comparison of Two Approaches

Effects of drought on plant parameters of different rangeland types in Khansar region, Iran

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