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Author (up) Dibari, C.; Argenti, G.; Catolfi, F.; Moriondo, M.; Staglianò, N.; Bindi, M.
Title Climate change impacts on natural pasturelands of Italian Apennines Type Conference Article
Year 2014 Publication Abbreviated Journal
Volume Issue Pages
Keywords
Abstract As well as the entire Mediterranean area, the Italian Apennines have been affected by increasing temperatures, rainfall extreme events and decreases in annual precipitation due to climate change. Moreover, permanent grasslands, species-diverse ecosystems characterizing the marginal areas of the Apennines landscape, are acknowledged as very sensitive and vulnerable to climate variation. Building on these premises, statistical classification models coupled with data integration by GIS techniques, were used to territorially assess future climate change impacts on pastoral communities on the Italian Apennines chain. Specifically, a machine learning approach (Random Forest – RF), firstly calibrated  for the present period and then applied to future conditions, as projected by HadCM3 General Circulation Model (GCM), was used to simulate potential expansion/reduction and/or altitudinal shifts of the Apennine pasturelands in two time slices, centred on 2050 and 2080, under A2 and B2 SRES scenarios. RF classification model proved to be robust and very efficient to predict lands suited to pastures with regards to present period (classification error: 12%). Furthermore, according to RF simulations, relevant reductions (46 and 34%) of areas potentially suitable for pastoral resource are expected under A2 at the middle and end of the century, respectively, as depicted by the GCM and SRES scenarios. Moreover, progressive upwards shifts are predicted by the model under both SRES scenarios. These reductions will likely interest the central area of the chain threatening the typical and unique herbaceous biodiversity characterizing the Apennine pasturelands.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title FACCE MACSUR Mid-term Scientific Conference
Series Volume 3(S) Sassari, Italy Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy
Notes Approved no
Call Number MA @ admin @ Serial 5062
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Author (up) Dietrich, J.P.; Popp, A.; Lotze-Campen, H.
Title Reducing the loss of information and gaining accuracy with clustering methods in a global land-use model Type Journal Article
Year 2013 Publication Ecological Modelling Abbreviated Journal Ecol. Model.
Volume 263 Issue Pages 233-243
Keywords aggregation; downscaling; clustering; information conservation; land use model; scale; scales; agriculture; simulation; dynamics; pattern
Abstract Global land-use models have to deal with processes on several spatial scales, ranging from the global scale down to the farm level. The increasing complexity of modern land-use models combined with the problem of limited computational resources represents a challenge to modelers. One solution of this problem is to perform spatial aggregation based on a regular grid or administrative units such as countries. Unfortunately this type of aggregation flattens many regional differences and produces a homogenized map of the world. In this paper we present an alternative aggregation approach using clustering methods. Clustering reduces the loss of information due to aggregation by choosing an appropriate aggregation pattern. We investigate different clustering methods, examining their quality in terms of information conservation. Our results indicate that clustering is always a good choice and preferable compared to grid-based aggregation. Although all the clustering methods we tested delivered a higher degree of information conservation than grid-based aggregation, the choice of clustering method is not arbitrary. Comparing outputs of a model fed with original data and a model fed with aggregated data, bottom-up clustering delivered the best results for the whole range of numbers of clusters tested. (C) 2013 Elsevier B.V. All rights reserved.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0304-3800 ISBN Medium Article
Area Expedition Conference
Notes TradeM Approved no
Call Number MA @ admin @ Serial 4488
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Author (up) Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Popp, A.; Muller, C.
Title Forecasting technological change in agriculture-An endogenous implementation in a global, and use model Type Journal Article
Year 2014 Publication Technological Forecasting and Social Change Abbreviated Journal Technological Forecasting and Social Change
Volume 81 Issue Pages 236-249
Keywords Technological change; Land use; Agricultural productivity; Land use; intensity; Research and development; land-use; research expenditures; productivity growth; impact; deforestation; forest; yield; Business & Economics; Public Administration
Abstract Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 029 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (”Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995-2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change. (C) 2013 Elsevier Inc. All rights reserved.
Address 2016-10-31
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0040-1625 ISBN Medium Article
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4789
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Author (up) Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Popp, A.; Müller, C.
Title Forecasting technological change in agriculture—An endogenous implementation in a global land use model Type Journal Article
Year 2014 Publication Technological Forecasting and Social Change Abbreviated Journal Technological Forecasting and Social Change
Volume 81 Issue Pages 236-249
Keywords Technological change; Land use; Agricultural productivity; Land use intensity; Research and development; land-use; research expenditures; productivity growth; impact; deforestation; forest; yield; Business & Economics; Public Administration
Abstract ► Endogenous technological change in an economic land use model ► Estimation of yield elasticity with respect to investments in technological change ► Projections of future agricultural productivity rates ► Validation with observed data and historic trends ► Trade-off between required technological change and forest protection objectives Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 0.29 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (“Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995–2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0040-1625 ISBN Medium Article
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4518
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Author (up) Dirnböck, T.; Bezák, P.; Dullinger, S.; Haberl, H.; Lotze-Campen, H.; Mirtl, M.; Peterseil, J.; Redpath, S.; Singh, S.J.; Travis, J.; Wijdeven, S.M.J.
Title Critical Scales for Long-Term Socio-ecological Biodiversity Research Type Book Chapter
Year 2013 Publication Abbreviated Journal
Volume Issue Pages 123-138
Keywords TradeM
Abstract
Address
Corporate Author Thesis
Publisher Springer Place of Publication Dordrecht Editor Singh, S.J.; Haberl, H.; Chertow, M.; Mirtl, M.; Schmid, M.
Language Summary Language Original Title
Series Editor Series Title Long Term Socio-Ecological Research Abbreviated Series Title
Series Volume Human-environment interactions (2) Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number MA @ admin @ Serial 2390
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