Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation
• The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use chan...
Ausführliche Beschreibung
Autor*in: |
Doelman, Jonathan C. [verfasserIn] |
---|
Format: |
E-Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2018transfer abstract |
---|
Schlagwörter: |
---|
Umfang: |
17 |
---|
Übergeordnetes Werk: |
Enthalten in: Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys - Laplanche, G. ELSEVIER, 2014transfer abstract, human and policy dimensions, Amsterdam [u.a.] |
---|---|
Übergeordnetes Werk: |
volume:48 ; year:2018 ; pages:119-135 ; extent:17 |
Links: |
---|
DOI / URN: |
10.1016/j.gloenvcha.2017.11.014 |
---|
Katalog-ID: |
ELV042015936 |
---|
LEADER | 01000caa a22002652 4500 | ||
---|---|---|---|
001 | ELV042015936 | ||
003 | DE-627 | ||
005 | 20230626000250.0 | ||
007 | cr uuu---uuuuu | ||
008 | 180726s2018 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.1016/j.gloenvcha.2017.11.014 |2 doi | |
028 | 5 | 2 | |a GBV00000000000524.pica |
035 | |a (DE-627)ELV042015936 | ||
035 | |a (ELSEVIER)S0959-3780(16)30639-2 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | 4 | |a 670 |q VZ |
082 | 0 | 4 | |a 330 |q VZ |
100 | 1 | |a Doelman, Jonathan C. |e verfasserin |4 aut | |
245 | 1 | 0 | |a Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation |
264 | 1 | |c 2018transfer abstract | |
300 | |a 17 | ||
336 | |a nicht spezifiziert |b zzz |2 rdacontent | ||
337 | |a nicht spezifiziert |b z |2 rdamedia | ||
338 | |a nicht spezifiziert |b zu |2 rdacarrier | ||
520 | |a • The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. | ||
520 | |a • The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. | ||
650 | 7 | |a Integrated assessment |2 Elsevier | |
650 | 7 | |a REDD |2 Elsevier | |
650 | 7 | |a Shared Socio-economic Pathways (SSPs) |2 Elsevier | |
650 | 7 | |a Bioenergy |2 Elsevier | |
650 | 7 | |a Climate change mitigation |2 Elsevier | |
650 | 7 | |a Land-use change |2 Elsevier | |
700 | 1 | |a Stehfest, Elke |4 oth | |
700 | 1 | |a Tabeau, Andrzej |4 oth | |
700 | 1 | |a van Meijl, Hans |4 oth | |
700 | 1 | |a Lassaletta, Luis |4 oth | |
700 | 1 | |a Gernaat, David E.H.J. |4 oth | |
700 | 1 | |a Hermans, Kathleen |4 oth | |
700 | 1 | |a Harmsen, Mathijs |4 oth | |
700 | 1 | |a Daioglou, Vassilis |4 oth | |
700 | 1 | |a Biemans, Hester |4 oth | |
700 | 1 | |a van der Sluis, Sietske |4 oth | |
700 | 1 | |a van Vuuren, Detlef P. |4 oth | |
773 | 0 | 8 | |i Enthalten in |n Elsevier |a Laplanche, G. ELSEVIER |t Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys |d 2014transfer abstract |d human and policy dimensions |g Amsterdam [u.a.] |w (DE-627)ELV022995692 |
773 | 1 | 8 | |g volume:48 |g year:2018 |g pages:119-135 |g extent:17 |
856 | 4 | 0 | |u https://doi.org/10.1016/j.gloenvcha.2017.11.014 |3 Volltext |
912 | |a GBV_USEFLAG_U | ||
912 | |a GBV_ELV | ||
912 | |a SYSFLAG_U | ||
912 | |a GBV_ILN_11 | ||
912 | |a GBV_ILN_21 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_74 | ||
912 | |a GBV_ILN_105 | ||
912 | |a GBV_ILN_2001 | ||
912 | |a GBV_ILN_2008 | ||
912 | |a GBV_ILN_2018 | ||
912 | |a GBV_ILN_2021 | ||
951 | |a AR | ||
952 | |d 48 |j 2018 |h 119-135 |g 17 |
author_variant |
j c d jc jcd |
---|---|
matchkey_str |
doelmanjonathancstehfestelketabeauandrze:2018----:xlrnspadsdnmcuighiaeoergoaadrdeseaisfadscagad |
hierarchy_sort_str |
2018transfer abstract |
publishDate |
2018 |
allfields |
10.1016/j.gloenvcha.2017.11.014 doi GBV00000000000524.pica (DE-627)ELV042015936 (ELSEVIER)S0959-3780(16)30639-2 DE-627 ger DE-627 rakwb eng 670 VZ 330 VZ Doelman, Jonathan C. verfasserin aut Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation 2018transfer abstract 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. • The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. Integrated assessment Elsevier REDD Elsevier Shared Socio-economic Pathways (SSPs) Elsevier Bioenergy Elsevier Climate change mitigation Elsevier Land-use change Elsevier Stehfest, Elke oth Tabeau, Andrzej oth van Meijl, Hans oth Lassaletta, Luis oth Gernaat, David E.H.J. oth Hermans, Kathleen oth Harmsen, Mathijs oth Daioglou, Vassilis oth Biemans, Hester oth van der Sluis, Sietske oth van Vuuren, Detlef P. oth Enthalten in Elsevier Laplanche, G. ELSEVIER Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys 2014transfer abstract human and policy dimensions Amsterdam [u.a.] (DE-627)ELV022995692 volume:48 year:2018 pages:119-135 extent:17 https://doi.org/10.1016/j.gloenvcha.2017.11.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_74 GBV_ILN_105 GBV_ILN_2001 GBV_ILN_2008 GBV_ILN_2018 GBV_ILN_2021 AR 48 2018 119-135 17 |
spelling |
10.1016/j.gloenvcha.2017.11.014 doi GBV00000000000524.pica (DE-627)ELV042015936 (ELSEVIER)S0959-3780(16)30639-2 DE-627 ger DE-627 rakwb eng 670 VZ 330 VZ Doelman, Jonathan C. verfasserin aut Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation 2018transfer abstract 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. • The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. Integrated assessment Elsevier REDD Elsevier Shared Socio-economic Pathways (SSPs) Elsevier Bioenergy Elsevier Climate change mitigation Elsevier Land-use change Elsevier Stehfest, Elke oth Tabeau, Andrzej oth van Meijl, Hans oth Lassaletta, Luis oth Gernaat, David E.H.J. oth Hermans, Kathleen oth Harmsen, Mathijs oth Daioglou, Vassilis oth Biemans, Hester oth van der Sluis, Sietske oth van Vuuren, Detlef P. oth Enthalten in Elsevier Laplanche, G. ELSEVIER Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys 2014transfer abstract human and policy dimensions Amsterdam [u.a.] (DE-627)ELV022995692 volume:48 year:2018 pages:119-135 extent:17 https://doi.org/10.1016/j.gloenvcha.2017.11.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_74 GBV_ILN_105 GBV_ILN_2001 GBV_ILN_2008 GBV_ILN_2018 GBV_ILN_2021 AR 48 2018 119-135 17 |
allfields_unstemmed |
10.1016/j.gloenvcha.2017.11.014 doi GBV00000000000524.pica (DE-627)ELV042015936 (ELSEVIER)S0959-3780(16)30639-2 DE-627 ger DE-627 rakwb eng 670 VZ 330 VZ Doelman, Jonathan C. verfasserin aut Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation 2018transfer abstract 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. • The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. Integrated assessment Elsevier REDD Elsevier Shared Socio-economic Pathways (SSPs) Elsevier Bioenergy Elsevier Climate change mitigation Elsevier Land-use change Elsevier Stehfest, Elke oth Tabeau, Andrzej oth van Meijl, Hans oth Lassaletta, Luis oth Gernaat, David E.H.J. oth Hermans, Kathleen oth Harmsen, Mathijs oth Daioglou, Vassilis oth Biemans, Hester oth van der Sluis, Sietske oth van Vuuren, Detlef P. oth Enthalten in Elsevier Laplanche, G. ELSEVIER Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys 2014transfer abstract human and policy dimensions Amsterdam [u.a.] (DE-627)ELV022995692 volume:48 year:2018 pages:119-135 extent:17 https://doi.org/10.1016/j.gloenvcha.2017.11.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_74 GBV_ILN_105 GBV_ILN_2001 GBV_ILN_2008 GBV_ILN_2018 GBV_ILN_2021 AR 48 2018 119-135 17 |
allfieldsGer |
10.1016/j.gloenvcha.2017.11.014 doi GBV00000000000524.pica (DE-627)ELV042015936 (ELSEVIER)S0959-3780(16)30639-2 DE-627 ger DE-627 rakwb eng 670 VZ 330 VZ Doelman, Jonathan C. verfasserin aut Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation 2018transfer abstract 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. • The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. Integrated assessment Elsevier REDD Elsevier Shared Socio-economic Pathways (SSPs) Elsevier Bioenergy Elsevier Climate change mitigation Elsevier Land-use change Elsevier Stehfest, Elke oth Tabeau, Andrzej oth van Meijl, Hans oth Lassaletta, Luis oth Gernaat, David E.H.J. oth Hermans, Kathleen oth Harmsen, Mathijs oth Daioglou, Vassilis oth Biemans, Hester oth van der Sluis, Sietske oth van Vuuren, Detlef P. oth Enthalten in Elsevier Laplanche, G. ELSEVIER Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys 2014transfer abstract human and policy dimensions Amsterdam [u.a.] (DE-627)ELV022995692 volume:48 year:2018 pages:119-135 extent:17 https://doi.org/10.1016/j.gloenvcha.2017.11.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_74 GBV_ILN_105 GBV_ILN_2001 GBV_ILN_2008 GBV_ILN_2018 GBV_ILN_2021 AR 48 2018 119-135 17 |
allfieldsSound |
10.1016/j.gloenvcha.2017.11.014 doi GBV00000000000524.pica (DE-627)ELV042015936 (ELSEVIER)S0959-3780(16)30639-2 DE-627 ger DE-627 rakwb eng 670 VZ 330 VZ Doelman, Jonathan C. verfasserin aut Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation 2018transfer abstract 17 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. • The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. Integrated assessment Elsevier REDD Elsevier Shared Socio-economic Pathways (SSPs) Elsevier Bioenergy Elsevier Climate change mitigation Elsevier Land-use change Elsevier Stehfest, Elke oth Tabeau, Andrzej oth van Meijl, Hans oth Lassaletta, Luis oth Gernaat, David E.H.J. oth Hermans, Kathleen oth Harmsen, Mathijs oth Daioglou, Vassilis oth Biemans, Hester oth van der Sluis, Sietske oth van Vuuren, Detlef P. oth Enthalten in Elsevier Laplanche, G. ELSEVIER Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys 2014transfer abstract human and policy dimensions Amsterdam [u.a.] (DE-627)ELV022995692 volume:48 year:2018 pages:119-135 extent:17 https://doi.org/10.1016/j.gloenvcha.2017.11.014 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_74 GBV_ILN_105 GBV_ILN_2001 GBV_ILN_2008 GBV_ILN_2018 GBV_ILN_2021 AR 48 2018 119-135 17 |
language |
English |
source |
Enthalten in Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys Amsterdam [u.a.] volume:48 year:2018 pages:119-135 extent:17 |
sourceStr |
Enthalten in Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys Amsterdam [u.a.] volume:48 year:2018 pages:119-135 extent:17 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
Integrated assessment REDD Shared Socio-economic Pathways (SSPs) Bioenergy Climate change mitigation Land-use change |
dewey-raw |
670 |
isfreeaccess_bool |
false |
container_title |
Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys |
authorswithroles_txt_mv |
Doelman, Jonathan C. @@aut@@ Stehfest, Elke @@oth@@ Tabeau, Andrzej @@oth@@ van Meijl, Hans @@oth@@ Lassaletta, Luis @@oth@@ Gernaat, David E.H.J. @@oth@@ Hermans, Kathleen @@oth@@ Harmsen, Mathijs @@oth@@ Daioglou, Vassilis @@oth@@ Biemans, Hester @@oth@@ van der Sluis, Sietske @@oth@@ van Vuuren, Detlef P. @@oth@@ |
publishDateDaySort_date |
2018-01-01T00:00:00Z |
hierarchy_top_id |
ELV022995692 |
dewey-sort |
3670 |
id |
ELV042015936 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV042015936</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626000250.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180726s2018 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.gloenvcha.2017.11.014</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBV00000000000524.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV042015936</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0959-3780(16)30639-2</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">670</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">330</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Doelman, Jonathan C.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">17</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">• The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">• The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Integrated assessment</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">REDD</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Shared Socio-economic Pathways (SSPs)</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Bioenergy</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Climate change mitigation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Land-use change</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Stehfest, Elke</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tabeau, Andrzej</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">van Meijl, Hans</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lassaletta, Luis</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gernaat, David E.H.J.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hermans, Kathleen</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Harmsen, Mathijs</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Daioglou, Vassilis</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Biemans, Hester</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">van der Sluis, Sietske</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">van Vuuren, Detlef P.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Laplanche, G. ELSEVIER</subfield><subfield code="t">Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys</subfield><subfield code="d">2014transfer abstract</subfield><subfield code="d">human and policy dimensions</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV022995692</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:48</subfield><subfield code="g">year:2018</subfield><subfield code="g">pages:119-135</subfield><subfield code="g">extent:17</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.gloenvcha.2017.11.014</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_21</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2018</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">48</subfield><subfield code="j">2018</subfield><subfield code="h">119-135</subfield><subfield code="g">17</subfield></datafield></record></collection>
|
author |
Doelman, Jonathan C. |
spellingShingle |
Doelman, Jonathan C. ddc 670 ddc 330 Elsevier Integrated assessment Elsevier REDD Elsevier Shared Socio-economic Pathways (SSPs) Elsevier Bioenergy Elsevier Climate change mitigation Elsevier Land-use change Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation |
authorStr |
Doelman, Jonathan C. |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)ELV022995692 |
format |
electronic Article |
dewey-ones |
670 - Manufacturing 330 - Economics |
delete_txt_mv |
keep |
author_role |
aut |
collection |
elsevier |
remote_str |
true |
illustrated |
Not Illustrated |
topic_title |
670 VZ 330 VZ Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation Integrated assessment Elsevier REDD Elsevier Shared Socio-economic Pathways (SSPs) Elsevier Bioenergy Elsevier Climate change mitigation Elsevier Land-use change Elsevier |
topic |
ddc 670 ddc 330 Elsevier Integrated assessment Elsevier REDD Elsevier Shared Socio-economic Pathways (SSPs) Elsevier Bioenergy Elsevier Climate change mitigation Elsevier Land-use change |
topic_unstemmed |
ddc 670 ddc 330 Elsevier Integrated assessment Elsevier REDD Elsevier Shared Socio-economic Pathways (SSPs) Elsevier Bioenergy Elsevier Climate change mitigation Elsevier Land-use change |
topic_browse |
ddc 670 ddc 330 Elsevier Integrated assessment Elsevier REDD Elsevier Shared Socio-economic Pathways (SSPs) Elsevier Bioenergy Elsevier Climate change mitigation Elsevier Land-use change |
format_facet |
Elektronische Aufsätze Aufsätze Elektronische Ressource |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
zu |
author2_variant |
e s es a t at m h v mh mhv l l ll d e g de deg k h kh m h mh v d vd h b hb d s s v dss dssv v d p v vdp vdpv |
hierarchy_parent_title |
Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys |
hierarchy_parent_id |
ELV022995692 |
dewey-tens |
670 - Manufacturing 330 - Economics |
hierarchy_top_title |
Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)ELV022995692 |
title |
Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation |
ctrlnum |
(DE-627)ELV042015936 (ELSEVIER)S0959-3780(16)30639-2 |
title_full |
Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation |
author_sort |
Doelman, Jonathan C. |
journal |
Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys |
journalStr |
Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys |
lang_code |
eng |
isOA_bool |
false |
dewey-hundreds |
600 - Technology 300 - Social sciences |
recordtype |
marc |
publishDateSort |
2018 |
contenttype_str_mv |
zzz |
container_start_page |
119 |
author_browse |
Doelman, Jonathan C. |
container_volume |
48 |
physical |
17 |
class |
670 VZ 330 VZ |
format_se |
Elektronische Aufsätze |
author-letter |
Doelman, Jonathan C. |
doi_str_mv |
10.1016/j.gloenvcha.2017.11.014 |
dewey-full |
670 330 |
title_sort |
exploring ssp land-use dynamics using the image model: regional and gridded scenarios of land-use change and land-based climate change mitigation |
title_auth |
Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation |
abstract |
• The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. |
abstractGer |
• The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. |
abstract_unstemmed |
• The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security. |
collection_details |
GBV_USEFLAG_U GBV_ELV SYSFLAG_U GBV_ILN_11 GBV_ILN_21 GBV_ILN_22 GBV_ILN_74 GBV_ILN_105 GBV_ILN_2001 GBV_ILN_2008 GBV_ILN_2018 GBV_ILN_2021 |
title_short |
Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation |
url |
https://doi.org/10.1016/j.gloenvcha.2017.11.014 |
remote_bool |
true |
author2 |
Stehfest, Elke Tabeau, Andrzej van Meijl, Hans Lassaletta, Luis Gernaat, David E.H.J. Hermans, Kathleen Harmsen, Mathijs Daioglou, Vassilis Biemans, Hester van der Sluis, Sietske van Vuuren, Detlef P. |
author2Str |
Stehfest, Elke Tabeau, Andrzej van Meijl, Hans Lassaletta, Luis Gernaat, David E.H.J. Hermans, Kathleen Harmsen, Mathijs Daioglou, Vassilis Biemans, Hester van der Sluis, Sietske van Vuuren, Detlef P. |
ppnlink |
ELV022995692 |
mediatype_str_mv |
z |
isOA_txt |
false |
hochschulschrift_bool |
false |
author2_role |
oth oth oth oth oth oth oth oth oth oth oth |
doi_str |
10.1016/j.gloenvcha.2017.11.014 |
up_date |
2024-07-06T21:40:26.892Z |
_version_ |
1803867418151354369 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV042015936</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230626000250.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180726s2018 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.gloenvcha.2017.11.014</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBV00000000000524.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV042015936</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0959-3780(16)30639-2</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">670</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">330</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Doelman, Jonathan C.</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2018transfer abstract</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">17</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">• The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">• The SSP scenarios show a wide spread in agricultural land-use change in 2010-2050: from a decrease of 305 Mha in SSP1 to an increase of 826 Mha in SSP3. • Key drivers are population, agricultural efficiency, consumption, land availability, food losses, and dietary preferences. • Most land-use change is projected in Sub-Saharan Africa up to 424 Mha in the period 2010–2100. • Negative emissions from bioenergy (with CCS) and reforestation are crucial to limit temperature increases to 1.5oC in 2100. • REDD (avoided deforestation) in Sub-Saharan Africa could have substantial trade-offs negatively affecting food security.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Integrated assessment</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">REDD</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Shared Socio-economic Pathways (SSPs)</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Bioenergy</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Climate change mitigation</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Land-use change</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Stehfest, Elke</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Tabeau, Andrzej</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">van Meijl, Hans</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Lassaletta, Luis</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Gernaat, David E.H.J.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Hermans, Kathleen</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Harmsen, Mathijs</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Daioglou, Vassilis</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Biemans, Hester</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">van der Sluis, Sietske</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">van Vuuren, Detlef P.</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier</subfield><subfield code="a">Laplanche, G. ELSEVIER</subfield><subfield code="t">Sudden stress-induced transformation events during nanoindentation of NiTi shape memory alloys</subfield><subfield code="d">2014transfer abstract</subfield><subfield code="d">human and policy dimensions</subfield><subfield code="g">Amsterdam [u.a.]</subfield><subfield code="w">(DE-627)ELV022995692</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:48</subfield><subfield code="g">year:2018</subfield><subfield code="g">pages:119-135</subfield><subfield code="g">extent:17</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1016/j.gloenvcha.2017.11.014</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ELV</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_U</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_11</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_21</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_74</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_105</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2001</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2008</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2018</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">48</subfield><subfield code="j">2018</subfield><subfield code="h">119-135</subfield><subfield code="g">17</subfield></datafield></record></collection>
|
score |
7.3985558 |