This research simulates the impacts of climate changes on seven main pastoral communities (pasture macro-types) located over the Italian Alps. More specifically, pre-existing spatial databases, namely pastoral cartography, habitat maps, and high resolution soil-topographic-climate datasets (WorldClim and HWSD) were integrated and harmonized within a GIS platform in order to identify seven pasture macro-types characterizing the Italian Alps. The pasture macro-types were those dominated by shrub species (SP), by Carex curvula (CC), by Carex firma (CF), by Nardus stricta (NS), by Festuca gr. rubra (FR), by Sesleria varia (SV), by xeric species (XS). Nine environmental parameters were then extracted from the soil-topographic-climate database and used as model predictors variables. Moreover, a computational framework (BIOMOD), collecting several statistical classification models, was used to select the model resulting with the best prediction accuracy. According to BIOMOD outputs, a machine learning approach (Random Forest, RF) was first calibrated for the present period and then applied to future conditions, as projected by HadCM3 General Circulation Model (GCM), in order to simulate possible spatial variation/shift in potential pastoral areas in three time slices (centred on 2020, 2050 and 2080) under A2 and B2 SRES scenarios. RF simulations showed a moderate reduction (<-16%) of areas potentially suitable to pastoral resource under the future CGM SRES scenarios. Conversely, future climate conditions will have impacts of great concern on pasture macro-types extent and distribution. Specifically, an overall decline, or in some cases complete loss, of lands suitable for the most rare (FR) or high-altitude macro-types (CC, CF, SV) is forecasted by RF simulations at the end of the century for both SRES scenarios. According to these results, the expected climate warming, coupled with an increasing abandonment of the traditional grazing practices over the Alps, will likely threat the unique and rare herbaceous biodiversity characterizing the Alpine mountain range
Climate change impacts on distribution and composition of the Alpine Natural Pasturelands / Dibari C.; Argenti G.; Moriondo M.; Staglianò N.; Targetti S; Bindi M.. - ELETTRONICO. - (2013), pp. 578-586. (Intervento presentato al convegno Climate change and its implications on ecosystem and society tenutosi a Lecce (LE) nel 23-24/09/2013).
Climate change impacts on distribution and composition of the Alpine Natural Pasturelands
DIBARI, CAMILLA;ARGENTI, GIOVANNI;MORIONDO, MARCO;STAGLIANO', NICOLINA;TARGETTI, STEFANO;BINDI, MARCO
2013
Abstract
This research simulates the impacts of climate changes on seven main pastoral communities (pasture macro-types) located over the Italian Alps. More specifically, pre-existing spatial databases, namely pastoral cartography, habitat maps, and high resolution soil-topographic-climate datasets (WorldClim and HWSD) were integrated and harmonized within a GIS platform in order to identify seven pasture macro-types characterizing the Italian Alps. The pasture macro-types were those dominated by shrub species (SP), by Carex curvula (CC), by Carex firma (CF), by Nardus stricta (NS), by Festuca gr. rubra (FR), by Sesleria varia (SV), by xeric species (XS). Nine environmental parameters were then extracted from the soil-topographic-climate database and used as model predictors variables. Moreover, a computational framework (BIOMOD), collecting several statistical classification models, was used to select the model resulting with the best prediction accuracy. According to BIOMOD outputs, a machine learning approach (Random Forest, RF) was first calibrated for the present period and then applied to future conditions, as projected by HadCM3 General Circulation Model (GCM), in order to simulate possible spatial variation/shift in potential pastoral areas in three time slices (centred on 2020, 2050 and 2080) under A2 and B2 SRES scenarios. RF simulations showed a moderate reduction (<-16%) of areas potentially suitable to pastoral resource under the future CGM SRES scenarios. Conversely, future climate conditions will have impacts of great concern on pasture macro-types extent and distribution. Specifically, an overall decline, or in some cases complete loss, of lands suitable for the most rare (FR) or high-altitude macro-types (CC, CF, SV) is forecasted by RF simulations at the end of the century for both SRES scenarios. According to these results, the expected climate warming, coupled with an increasing abandonment of the traditional grazing practices over the Alps, will likely threat the unique and rare herbaceous biodiversity characterizing the Alpine mountain rangeI documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.