Geography
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Item Degradation of Non-Photosynthetic Vegetation in a Semi-Arid Rangeland(MDPI, 2016-08-24) Jackson, Hasan; Prince, Stephen D.Land degradation in drylands is the process in which undesirable conditions emerge due to human and natural causes. Despite the particularly deleterious effects of degradation, and it’s potentially irreversible nature, regional assessments have provided conflicting extents, rates, and severities of degradation, both globally and regionally. Current monitoring of degradation relies upon the detection of green, photosynthetically active parts of vegetation (e.g., leaves). Less is known, however, about the effect of degradation on the non-photosynthetic components of vegetation (e.g., wood, stems, leaf litter) and the relationship between photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), and bare soil under degraded conditions (BS). The major objective of the study was to evaluate regional patterns of fractional cover (i.e., PV, NPV, BS) under degraded and non-degraded NPP conditions in a managed rangeland in north Queensland, Australia. Homogenous environmental conditions were identified and each of NPP, PV, NPV, and BS were scaled according to their potential, reference values. We found a strong spatial and temporal correlation between scaled NPP with both scaled PV and scaled BS. Drastic differences were also found for PV and BS between degraded and non-degraded conditions. NPV displayed similarity to both PV and BS, however no clear relationship was found for NPV in all areas, irrespective of degradation conditions.Item Unplanned Natural Experiments: The Case of Remote Sensing of Primary Production and Its Environmental Correlations in the Negev(MDPI, 2020-10-31) Prince, Stephen D.; Jackson, HasanStudies of the correlations of environmental factors with vegetation growth using remotely sensed measurements are necessarily made against a background of biophysical and anthropogenic factors, such as local fertility, microclimate, and the effects of human land use, in addition to the factors of interest. This is an inevitable outcome of a natural (unplanned) design where the effects of the factors of interest are confounded with other, often unknown factors, possibly rendering the results inaccurate or poorly-constrained. The problems associated with a natural design would be reduced if sites could be identified in which uncontrolled variables had no impact. However, rarely are such sites known a priori. Here, a component of the net primary production (NPP) local scaling (LNS) method was used to estimate the potential NPP in the absence of confounding factors. Subsequent analyses of the effects of the selected environmental variables were carried out using the potential NPP. The method was tested in relation to NPP along the transitional ecotone from desert to semiarid conditions in the northern Negev, Israel. The effects of four environmental factors were tested: precipitation, topography, land cover, and interannual variability. While precipitation is generally the only environmental variable that is considered in drylands, the other factors were found to be significant. The results provided unambiguous evidence of the value of the method.Item HUMAN-INDUCED VEGETATION DEGRADATION IN A SEMI-ARID RANGELAND(2017) Jackson, Hasan; Prince, Stephen D; Geography; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Current assessments of anthropogenic land degradation and its impact on vegetation at regional scales are prone to large uncertainties due to the lack of an objective, transferable, spatially and temporally explicit measure of land degradation. These uncertainties have resulted in contradictory estimates of degradation extent and severity and the role of human activities. The uncertainties limit the ability to assess the effects on the biophysical environment and effectiveness of past, current, and future policies of land use. The overall objective of the dissertation is to assess degradation in a semi-arid region at a regional scale where the process of anthropogenic land degradation is evident. Net primary productivity (NPP) is used as the primary indicator to measure degradation. It is hypothesized that land degradation resulting from human factors on the landscape irreversibly reduces NPP below the potential set by environmental conditions. It is also hypothesized that resulting reductions in NPP are distinguishable from natural, spatial and temporal, variability in NPP. The specific goals of the dissertation are to (1) identify the extent and severity of degradation using productivity as the primary surrogate, (2) compare the degradation of productivity to other known mechanisms of degradation, and (3) relate the expression of degradation to components of vegetation and varying environmental conditions. This dissertation employed the Local NPP Scaling (LNS) approach to identify patterns of anthropogenic degradation of NPP in the Burdekin Dry Tropics (BDT) region of Queensland (14 million hectares), Australia from 2000 to 2013. The method started with land classification based on the environmental factors presumed to control NPP to group pixels having similar potential NPP. Then, satellite remotely sensing data were used to compare actual NPP with its potential. The difference, in units of mass of carbon fixed in NPP per unit area per monitoring interval and per year, also its percentage of the potential, were the measures of degradation. Degradation was then compared to non-green components of vegetation (e.g. wood, stems, leaf litter, dead biomass) to determine their relationship in space and time. Finally, the symptoms of degradation were compared to land management patterns and the environmental variability (e.g. drought, non-drought conditions). Nearly 20% of the region was identified as degraded and another 7% had significant negative trends. The average annual reduction in NPP due to anthropogenic degradation was -17% of the non-degraded potential, although the severity of degradation varied substantially throughout the region. Non-green vegetation cover was strongly correlated with the inter-annual and intra-annual temporal trends of degradation. The dynamics of degradation in drought and non-drought years provided evidence of multiple stables states of degradation.