Browsing by Subject "VEGETATION"

Now showing 1 - 3 of 3
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    A novel approach to assess livestock management effects on biodiversity of drylands
    (Ecological Indicators, 2015-01-01) Chillo, V; Ojeda, RA; Anand, M; Reynolds, JF
    In drylands livestock grazing is the main production activity, but overgrazing due to mismanagement is a major cause of biodiversity loss. Continuous grazing around water sources generates a radial gradient of grazing intensity called the piosphere. The ecological sustainability of this system is questionable and alternative management needs to be evaluated. We apply simple indicators of species response to grazing gradients, and we propose a novel methodological approach to compare community response to grazing gradients (double reciprocal analysis). We assessed degradation gradients of biodiversity under different management strategies in semiarid rangelands of the Monte desert (Argentina) by analyzing changes in vegetation, ants and small mammal richness and diversity, and variation due to seasonality. At the species level, we determined the trend in abundance of each species along the gradient, and the potential cross-taxa surrogacy. At the community level, the new methodological consists of assessing the magnitude of biodiversity degradation along different piospheres by comparing the slopes of linear functions obtained by the double reciprocal analysis. We found that most species showed a decreasing trend along the gradient under continuous grazing; while under rotational grazing fewer species showed a decreasing trend, and a neutral trend (no change in the abundance along the gradient of grazing intensity) was the most common. We found that vegetation cannot be used as a surrogacy taxon of animal response. Moreover, weak cross-taxa surrogacy was found only for animal assemblages during the wet season. The double reciprocal analysis allowed for comparison of multi-taxa response under different seasons and management types. By its application, we found that constrains in precipitation interacted with disturbance by increasing the negative effect of grazing on vegetation, but not on animal assemblages. Continuous grazing causes biodiversity loss in all situations. Rotational grazing prevents the occurrence of vegetation degradation and maintains higher levels of animal diversity, acting as an opportunity for biodiversity conservation under current scenarios of land use extensification. Our approach highlights the importance of considering multi-taxa and intrinsic variability in the analysis, and should be of value to managers concerned with biodiversity conservation.
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    Impacts of increased variability in precipitation and air temperature on net primary productivity of the Tibetan Plateau: A modeling analysis
    (Climatic Change, 2013-07-01) Ye, JS; Reynolds, JF; Sun, GJ; Li, FM
    We analyzed interannual variability (IAV) of precipitation and air temperature over a 40-year period (1969-2008) for 11 sites along a precipitation gradient on the Tibetan Plateau. The observed IAV for both precipitation and air temperature decreases with increasing mean annual precipitation. Using Biome-BGC, a process-based ecosystem model, we simulated net primary production (NPP) along this gradient and find that the IAV of NPP is positively correlated to the IAV of precipitation and temperature. Following projected climate change scenarios for the Tibetan Plateau, our simulations suggest that with increasing IAV of precipitation and temperature, the IAV of NPP will also increase and that climate thresholds exist that, if surpassed, lead to ecosystem die-off. The impacts of these changes on ecosystem processes and climate-vegetation feedbacks on the rapidly warming Tibetan Plateau are potentially quite significant. © 2013 Springer Science+Business Media Dordrecht.
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    Mammalian faunas, ecological indices, and machine-learning regression for the purpose of paleoenvironment reconstruction in the Miocene of South America
    (Palaeogeography, Palaeoclimatology, Palaeoecology, 2019-03-15) Spradley, JP; Glazer, BJ; Kay, RF
    © 2019 Elsevier B.V. Reconstructing paleoenvironments has long been considered a vital component for understanding community structure of extinct organisms, as well as patterns that guide evolutionary pathways of species and higher-level taxa. Given the relative geographic and phylogenetic isolation of the South American continent throughout much of the Cenozoic, the South American fossil record presents a unique perspective of mammalian community evolution in the context of changing climates and environments. Here we focus on one line of evidence for paleoenvironment reconstruction: ecological diversity, i.e. the number and types of ecological niches filled within a given fauna. We propose a novel approach by utilizing ecological indices as predictors in two regressive modeling techniques—Random Forest (RF) and Gaussian Process Regression (GPR)—which are applied to 85 extant Central and South American localities to produce paleoecological prediction models. Faunal richness is quantified via ratios of ecologies within the mammalian communities, i.e. ecological indices, which serve as predictor variables in our models. Six climate/habitat variables were then predicted using these ecological indices: mean annual temperature (MAT), mean annual precipitation (MAP), temperature seasonality, precipitation seasonality, canopy height, and net primary productivity (NPP). Predictive accuracy of RF and GPR is markedly higher when compared to previously published methods. MAT, MAP, and temperature seasonality have the lowest predictive error. We use these models to reconstruct paleoclimatic variables in two well-sampled Miocene faunas from South America: fossiliferous layers (FL) 1–7, Santa Cruz Formation (Early Miocene), Santa Cruz Province, Argentina; and the Monkey Beds unit, Villavieja Formation (Middle Miocene) Huila, Colombia. Results suggest general concordance with published estimations of precipitation and temperature, and add information with regards to the other climate/habitat variables included here. Ultimately, we believe that RF and GPR in conjunction with ecological indices have the potential to contribute to paleoenvironment reconstruction.