Articles | Volume 7, issue 1
https://doi.org/10.5194/esd-7-151-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/esd-7-151-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Potential impact of climate and socioeconomic changes on future agricultural land use in West Africa
Kazi Farzan Ahmed
Department of Civil and Environmental Engineering and Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, CT, USA
Guiling Wang
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering and Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, CT, USA
Liangzhi You
International Food Policy Research Institute, Washington, DC, USA
Miao Yu
Department of Civil and Environmental Engineering and Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, CT, USA
Related authors
No articles found.
Yating Ru, Brian Blankespoor, Ulrike Wood-Sichra, Timothy S. Thomas, Liangzhi You, and Erwin Kalvelagen
Earth Syst. Sci. Data, 15, 1357–1387, https://doi.org/10.5194/essd-15-1357-2023, https://doi.org/10.5194/essd-15-1357-2023, 2023
Short summary
Short summary
Economic statistics are frequently produced at an administrative level that lacks detail to examine development patterns and the exposure to natural hazards. This paper disaggregates national and subnational administrative statistics of agricultural GDP into a global dataset at the local level using satellite-derived indicators. As an illustration, the paper estimates that the exposure of areas with extreme drought to agricultural GDP is USD 432 billion, where nearly 1.2 billion people live.
Hanqin Tian, Zihao Bian, Hao Shi, Xiaoyu Qin, Naiqing Pan, Chaoqun Lu, Shufen Pan, Francesco N. Tubiello, Jinfeng Chang, Giulia Conchedda, Junguo Liu, Nathaniel Mueller, Kazuya Nishina, Rongting Xu, Jia Yang, Liangzhi You, and Bowen Zhang
Earth Syst. Sci. Data, 14, 4551–4568, https://doi.org/10.5194/essd-14-4551-2022, https://doi.org/10.5194/essd-14-4551-2022, 2022
Short summary
Short summary
Nitrogen is one of the critical nutrients for growth. Evaluating the change in nitrogen inputs due to human activity is necessary for nutrient management and pollution control. In this study, we generated a historical dataset of nitrogen input to land at the global scale. This dataset consists of nitrogen fertilizer, manure, and atmospheric deposition inputs to cropland, pasture, and rangeland at high resolution from 1860 to 2019.
Qiangyi Yu, Liangzhi You, Ulrike Wood-Sichra, Yating Ru, Alison K. B. Joglekar, Steffen Fritz, Wei Xiong, Miao Lu, Wenbin Wu, and Peng Yang
Earth Syst. Sci. Data, 12, 3545–3572, https://doi.org/10.5194/essd-12-3545-2020, https://doi.org/10.5194/essd-12-3545-2020, 2020
Short summary
Short summary
SPAM makes plausible estimates of crop distribution within disaggregated units. It moves the data from coarser units such as countries and provinces to finer units such as grid cells and creates a global gridscape at the confluence between earth and agricultural-production systems. It improves spatial understanding of crop production systems and allows policymakers to better target agricultural- and rural-development policies for increasing food security with minimal environmental impacts.
Miao Lu, Wenbin Wu, Liangzhi You, Linda See, Steffen Fritz, Qiangyi Yu, Yanbing Wei, Di Chen, Peng Yang, and Bing Xue
Earth Syst. Sci. Data, 12, 1913–1928, https://doi.org/10.5194/essd-12-1913-2020, https://doi.org/10.5194/essd-12-1913-2020, 2020
Short summary
Short summary
Global cropland distribution is critical for agricultural monitoring and food security. We propose a new Self-adapting Statistics Allocation Model (SASAM) to develop the global map of cropland distribution. SASAM is based on the fusion of multiple existing cropland maps and multilevel statistics of cropland area, which is independent of training samples. The synergy map has higher accuracy than the input datasets and better consistency with the cropland statistics.
Randal D. Koster, Alan K. Betts, Paul A. Dirmeyer, Marc Bierkens, Katrina E. Bennett, Stephen J. Déry, Jason P. Evans, Rong Fu, Felipe Hernandez, L. Ruby Leung, Xu Liang, Muhammad Masood, Hubert Savenije, Guiling Wang, and Xing Yuan
Hydrol. Earth Syst. Sci., 21, 3777–3798, https://doi.org/10.5194/hess-21-3777-2017, https://doi.org/10.5194/hess-21-3777-2017, 2017
Short summary
Short summary
Large-scale hydrological variability can affect society in profound ways; floods and droughts, for example, often cause major damage and hardship. A recent gathering of hydrologists at a symposium to honor the career of Professor Eric Wood motivates the present survey of recent research on this variability. The surveyed literature and the illustrative examples provided in the paper show that research into hydrological variability continues to be strong, vibrant, and multifaceted.
Congsheng Fu, Guiling Wang, Michael L. Goulden, Russell L. Scott, Kenneth Bible, and Zoe G. Cardon
Hydrol. Earth Syst. Sci., 20, 2001–2018, https://doi.org/10.5194/hess-20-2001-2016, https://doi.org/10.5194/hess-20-2001-2016, 2016
Short summary
Short summary
Hydraulic redistribution (HR) of plant root has important hydrological impact (on evapotranspiration, Bowen ratio, and soil moisture) in ecosystems that have a pronounced dry season but are not overall so dry that sparse vegetation and very low soil moisture limit HR.
Related subject area
Earth system interactions with the biosphere: landuse
The biogeophysical effects of idealized land cover and land management changes in Earth system models
The response of the regional longwave radiation balance and climate system in Europe to an idealized afforestation experiment
Comparison of uncertainties in land-use change fluxes from bookkeeping model parameterisation
Modelled land use and land cover change emissions – a spatio-temporal comparison of different approaches
Biases in the albedo sensitivity to deforestation in CMIP5 models and their impacts on the associated historical radiative forcing
Impact of environmental changes and land management practices on wheat production in India
Impacts of future agricultural change on ecosystem service indicators
Biogeophysical impacts of forestation in Europe: first results from the LUCAS (Land Use and Climate Across Scales) regional climate model intercomparison
A multi-model analysis of teleconnected crop yield variability in a range of cropping systems
Different response of surface temperature and air temperature to deforestation in climate models
Changes in crop yields and their variability at different levels of global warming
A global assessment of gross and net land change dynamics for current conditions and future scenarios
Quantification of the impacts of climate change and human agricultural activities on oasis water requirements in an arid region: a case study of the Heihe River basin, China
Projected changes in crop yield mean and variability over West Africa in a world 1.5 K warmer than the pre-industrial era
Managing fire risk during drought: the influence of certification and El Niño on fire-driven forest conversion for oil palm in Southeast Asia
Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments
Uncertainties in the land-use flux resulting from land-use change reconstructions and gross land transitions
Continuous and consistent land use/cover change estimates using socio-ecological data
Vulnerability to climate change and adaptation strategies of local communities in Malawi: experiences of women fish-processing groups in the Lake Chilwa Basin
Deforestation in Amazonia impacts riverine carbon dynamics
Assessing uncertainties in global cropland futures using a conditional probabilistic modelling framework
Ocean–atmosphere interactions modulate irrigation's climate impacts
Impacts of land-use history on the recovery of ecosystems after agricultural abandonment
Actors and networks in resource conflict resolution under climate change in rural Kenya
Groundwater nitrate concentration evolution under climate change and agricultural adaptation scenarios: Prince Edward Island, Canada
The role of spatial scale and background climate in the latitudinal temperature response to deforestation
Implications of land use change in tropical northern Africa under global warming
Quantifying differences in land use emission estimates implied by definition discrepancies
Inter-annual and seasonal trends of vegetation condition in the Upper Blue Nile (Abay) Basin: dual-scale time series analysis
Local sources of global climate forcing from different categories of land use activities
Effects of climate variability on savannah fire regimes in West Africa
Sustainable management of river oases along the Tarim River (SuMaRiO) in Northwest China under conditions of climate change
Terminology as a key uncertainty in net land use and land cover change carbon flux estimates
Towards decision-based global land use models for improved understanding of the Earth system
Implications of accounting for land use in simulations of ecosystem carbon cycling in Africa
The impact of nitrogen and phosphorous limitation on the estimated terrestrial carbon balance and warming of land use change over the last 156 yr
A theoretical framework for the net land-to-atmosphere CO2 flux and its implications in the definition of "emissions from land-use change"
Spatio-temporal analysis of the urban–rural gradient structure: an application in a Mediterranean mountainous landscape (Serra San Bruno, Italy)
Effects of land cover change on temperature and rainfall extremes in multi-model ensemble simulations
Urbanization suitability maps: a dynamic spatial decision support system for sustainable land use
The influence of vegetation on the ITCZ and South Asian monsoon in HadCM3
Steven J. De Hertog, Felix Havermann, Inne Vanderkelen, Suqi Guo, Fei Luo, Iris Manola, Dim Coumou, Edouard L. Davin, Gregory Duveiller, Quentin Lejeune, Julia Pongratz, Carl-Friedrich Schleussner, Sonia I. Seneviratne, and Wim Thiery
Earth Syst. Dynam., 14, 629–667, https://doi.org/10.5194/esd-14-629-2023, https://doi.org/10.5194/esd-14-629-2023, 2023
Short summary
Short summary
Land cover and land management changes are important strategies for future land-based mitigation. We investigate the climate effects of cropland expansion, afforestation, irrigation and wood harvesting using three Earth system models. Results show that these have important implications for surface temperature where the land cover and/or management change occur and in remote areas. Idealized afforestation causes global warming, which might offset the cooling effect from enhanced carbon uptake.
Marcus Breil, Felix Krawczyk, and Joaquim G. Pinto
Earth Syst. Dynam., 14, 243–253, https://doi.org/10.5194/esd-14-243-2023, https://doi.org/10.5194/esd-14-243-2023, 2023
Short summary
Short summary
We provide evidence that biogeophysical effects of afforestation can counteract the favorable biogeochemical climate effect of reduced CO2 concentrations. By changing the land surface characteristics, afforestation reduces vegetation surface temperatures, resulting in a reduced outgoing longwave radiation in summer, although CO2 concentrations are reduced. Since forests additionally absorb a lot of solar radiation due to their dark surfaces, afforestation has a total warming effect.
Ana Bastos, Kerstin Hartung, Tobias B. Nützel, Julia E. M. S. Nabel, Richard A. Houghton, and Julia Pongratz
Earth Syst. Dynam., 12, 745–762, https://doi.org/10.5194/esd-12-745-2021, https://doi.org/10.5194/esd-12-745-2021, 2021
Short summary
Short summary
Fluxes from land-use change and management (FLUC) are a large source of uncertainty in global and regional carbon budgets. Here, we evaluate the impact of different model parameterisations on FLUC. We show that carbon stock densities and allocation of carbon following transitions contribute more to uncertainty in FLUC than response-curve time constants. Uncertainty in FLUC could thus, in principle, be reduced by available Earth-observation data on carbon densities at a global scale.
Wolfgang A. Obermeier, Julia E. M. S. Nabel, Tammas Loughran, Kerstin Hartung, Ana Bastos, Felix Havermann, Peter Anthoni, Almut Arneth, Daniel S. Goll, Sebastian Lienert, Danica Lombardozzi, Sebastiaan Luyssaert, Patrick C. McGuire, Joe R. Melton, Benjamin Poulter, Stephen Sitch, Michael O. Sullivan, Hanqin Tian, Anthony P. Walker, Andrew J. Wiltshire, Soenke Zaehle, and Julia Pongratz
Earth Syst. Dynam., 12, 635–670, https://doi.org/10.5194/esd-12-635-2021, https://doi.org/10.5194/esd-12-635-2021, 2021
Short summary
Short summary
We provide the first spatio-temporally explicit comparison of different model-derived fluxes from land use and land cover changes (fLULCCs) by using the TRENDY v8 dynamic global vegetation models used in the 2019 global carbon budget. We find huge regional fLULCC differences resulting from environmental assumptions, simulated periods, and the timing of land use and land cover changes, and we argue for a method consistent across time and space and for carefully choosing the accounting period.
Quentin Lejeune, Edouard L. Davin, Grégory Duveiller, Bas Crezee, Ronny Meier, Alessandro Cescatti, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 1209–1232, https://doi.org/10.5194/esd-11-1209-2020, https://doi.org/10.5194/esd-11-1209-2020, 2020
Short summary
Short summary
Trees are darker than crops or grasses; hence, they absorb more solar radiation. Therefore, land cover changes modify the fraction of solar radiation reflected by the land surface (its albedo), with consequences for the climate. We apply a new statistical method to simulations conducted with 15 recent climate models and find that albedo variations due to land cover changes since 1860 have led to a decrease in the net amount of energy entering the atmosphere by −0.09 W m2 on average.
Shilpa Gahlot, Tzu-Shun Lin, Atul K. Jain, Somnath Baidya Roy, Vinay K. Sehgal, and Rajkumar Dhakar
Earth Syst. Dynam., 11, 641–652, https://doi.org/10.5194/esd-11-641-2020, https://doi.org/10.5194/esd-11-641-2020, 2020
Short summary
Short summary
Spring wheat, a staple for millions of people in India and the world, is vulnerable to changing environmental and management factors. Using a new spring wheat model, we find that over the 1980–2016 period elevated CO2 levels, irrigation, and nitrogen fertilizers led to an increase of 30 %, 12 %, and 15 % in countrywide production, respectively. In contrast, rising temperatures have reduced production by 18 %. These effects vary across the country, thereby affecting production at regional scales.
Sam S. Rabin, Peter Alexander, Roslyn Henry, Peter Anthoni, Thomas A. M. Pugh, Mark Rounsevell, and Almut Arneth
Earth Syst. Dynam., 11, 357–376, https://doi.org/10.5194/esd-11-357-2020, https://doi.org/10.5194/esd-11-357-2020, 2020
Short summary
Short summary
We modeled how agricultural performance and demand will shift as a result of climate change and population growth, and how the resulting adaptations will affect aspects of the Earth system upon which humanity depends. We found that the impacts of land use and management can have stronger impacts than climate change on some such
ecosystem services. The overall impacts are strongest in future scenarios with more severe climate change, high population growth, and/or resource-intensive lifestyles.
Edouard L. Davin, Diana Rechid, Marcus Breil, Rita M. Cardoso, Erika Coppola, Peter Hoffmann, Lisa L. Jach, Eleni Katragkou, Nathalie de Noblet-Ducoudré, Kai Radtke, Mario Raffa, Pedro M. M. Soares, Giannis Sofiadis, Susanna Strada, Gustav Strandberg, Merja H. Tölle, Kirsten Warrach-Sagi, and Volker Wulfmeyer
Earth Syst. Dynam., 11, 183–200, https://doi.org/10.5194/esd-11-183-2020, https://doi.org/10.5194/esd-11-183-2020, 2020
Matias Heino, Joseph H. A. Guillaume, Christoph Müller, Toshichika Iizumi, and Matti Kummu
Earth Syst. Dynam., 11, 113–128, https://doi.org/10.5194/esd-11-113-2020, https://doi.org/10.5194/esd-11-113-2020, 2020
Short summary
Short summary
In this study, we analyse the impacts of three major climate oscillations on global crop production. Our results show that maize, rice, soybean, and wheat yields are influenced by climate oscillations to a wide extent and in several important crop-producing regions. We observe larger impacts if crops are rainfed or fully fertilized, while irrigation tends to mitigate the impacts. These results can potentially help to increase the resilience of the global food system to climate-related shocks.
Johannes Winckler, Christian H. Reick, Sebastiaan Luyssaert, Alessandro Cescatti, Paul C. Stoy, Quentin Lejeune, Thomas Raddatz, Andreas Chlond, Marvin Heidkamp, and Julia Pongratz
Earth Syst. Dynam., 10, 473–484, https://doi.org/10.5194/esd-10-473-2019, https://doi.org/10.5194/esd-10-473-2019, 2019
Short summary
Short summary
For local living conditions, it matters whether deforestation influences the surface temperature, temperature at 2 m, or the temperature higher up in the atmosphere. Here, simulations with a climate model show that at a location of deforestation, surface temperature generally changes more strongly than atmospheric temperature. Comparison across climate models shows that both for summer and winter the surface temperature response exceeds the air temperature response locally by a factor of 2.
Sebastian Ostberg, Jacob Schewe, Katelin Childers, and Katja Frieler
Earth Syst. Dynam., 9, 479–496, https://doi.org/10.5194/esd-9-479-2018, https://doi.org/10.5194/esd-9-479-2018, 2018
Short summary
Short summary
It has been shown that regional temperature and precipitation changes in future climate change scenarios often scale quasi-linearly with global mean temperature change (∆GMT). We show that an important consequence of these physical climate changes, namely changes in agricultural crop yields, can also be described in terms of ∆GMT to a large extent. This makes it possible to efficiently estimate future crop yield changes for different climate change scenarios without need for complex models.
Richard Fuchs, Reinhard Prestele, and Peter H. Verburg
Earth Syst. Dynam., 9, 441–458, https://doi.org/10.5194/esd-9-441-2018, https://doi.org/10.5194/esd-9-441-2018, 2018
Short summary
Short summary
We analysed current global land change dynamics based on high-resolution (30–100 m) remote sensing products. We integrated these empirical data into a future simulation model to assess global land change dynamics in the future (2000 to 2040). The consideration of empirically derived land change dynamics in future models led globally to ca. 50 % more land changes than currently assumed in state-of-the-art models. This impacts the results of other global change studies (e.g. climate change).
Xingran Liu and Yanjun Shen
Earth Syst. Dynam., 9, 211–225, https://doi.org/10.5194/esd-9-211-2018, https://doi.org/10.5194/esd-9-211-2018, 2018
Short summary
Short summary
The impacts of climate change and human activities on oasis water requirements in Heihe River basin were quantified with the methods of partial derivative and slope in this study. The results showed that the oasis water requirement increased sharply from 10.8 × 108 to 19.0 × 108 m3 during 1986–2013. Human activities were the dominant driving forces. Changes in climate, land scale and structure contributed to the increase in water requirement at rates of 6.9, 58.1, and 25.3 %, respectively.
Ben Parkes, Dimitri Defrance, Benjamin Sultan, Philippe Ciais, and Xuhui Wang
Earth Syst. Dynam., 9, 119–134, https://doi.org/10.5194/esd-9-119-2018, https://doi.org/10.5194/esd-9-119-2018, 2018
Short summary
Short summary
We present an analysis of three crops in West Africa and their response to short-term climate change in a world where temperatures are 1.5 °C above the preindustrial levels. We show that the number of crop failures for all crops is due to increase in the future climate. We further show the difference in yield change across several West African countries and show that the yields are not expected to increase fast enough to prevent food shortages.
Praveen Noojipady, Douglas C. Morton, Wilfrid Schroeder, Kimberly M. Carlson, Chengquan Huang, Holly K. Gibbs, David Burns, Nathalie F. Walker, and Stephen D. Prince
Earth Syst. Dynam., 8, 749–771, https://doi.org/10.5194/esd-8-749-2017, https://doi.org/10.5194/esd-8-749-2017, 2017
Reinhard Prestele, Almut Arneth, Alberte Bondeau, Nathalie de Noblet-Ducoudré, Thomas A. M. Pugh, Stephen Sitch, Elke Stehfest, and Peter H. Verburg
Earth Syst. Dynam., 8, 369–386, https://doi.org/10.5194/esd-8-369-2017, https://doi.org/10.5194/esd-8-369-2017, 2017
Short summary
Short summary
Land-use change is still overly simplistically implemented in global ecosystem and climate models. We identify and discuss three major challenges at the interface of land-use and climate modeling and propose ways for how to improve land-use representation in climate models. We conclude that land-use data-provider and user communities need to engage in the joint development and evaluation of enhanced land-use datasets to improve the quantification of land use–climate interactions and feedback.
Anita D. Bayer, Mats Lindeskog, Thomas A. M. Pugh, Peter M. Anthoni, Richard Fuchs, and Almut Arneth
Earth Syst. Dynam., 8, 91–111, https://doi.org/10.5194/esd-8-91-2017, https://doi.org/10.5194/esd-8-91-2017, 2017
Short summary
Short summary
We evaluate the effects of land-use and land-cover changes on carbon pools and fluxes using a dynamic global vegetation model. Different historical reconstructions yielded an uncertainty of ca. ±30 % in the mean annual land use emission over the last decades. Accounting for the parallel expansion and abandonment of croplands on a sub-grid level (tropical shifting cultivation) substantially increased the effect of land use on carbon stocks and fluxes compared to only accounting for net effects.
Michael Marshall, Michael Norton-Griffiths, Harvey Herr, Richard Lamprey, Justin Sheffield, Tor Vagen, and Joseph Okotto-Okotto
Earth Syst. Dynam., 8, 55–73, https://doi.org/10.5194/esd-8-55-2017, https://doi.org/10.5194/esd-8-55-2017, 2017
Short summary
Short summary
The transition of land from one cover type to another can adversely affect the Earth system. A growing body of research aims to map these transitions in space and time to better understand the impacts. Here we develop a statistical model that is parameterized by socio-ecological geospatial data and extensive aerial/ground surveys to visualize and interpret these transitions on an annual basis for 30 years in Kenya. Future work will use this method to project land suitability across Africa.
Hanne Jørstad and Christian Webersik
Earth Syst. Dynam., 7, 977–989, https://doi.org/10.5194/esd-7-977-2016, https://doi.org/10.5194/esd-7-977-2016, 2016
Short summary
Short summary
This research is about climate change adaptation. It demonstrates how adaptation to climate change can avoid social tensions if done in a sustainable way. Evidence is drawn from Malawi in southern Africa.
Fanny Langerwisch, Ariane Walz, Anja Rammig, Britta Tietjen, Kirsten Thonicke, and Wolfgang Cramer
Earth Syst. Dynam., 7, 953–968, https://doi.org/10.5194/esd-7-953-2016, https://doi.org/10.5194/esd-7-953-2016, 2016
Short summary
Short summary
Amazonia is heavily impacted by climate change and deforestation. During annual flooding terrigenous material is imported to the river, converted and finally exported to the ocean or the atmosphere. Changes in the vegetation alter therefore riverine carbon dynamics. Our results show that due to deforestation organic carbon amount will strongly decrease both in the river and exported to the ocean, while inorganic carbon amounts will increase, in the river as well as exported to the atmosphere.
Kerstin Engström, Stefan Olin, Mark D. A. Rounsevell, Sara Brogaard, Detlef P. van Vuuren, Peter Alexander, Dave Murray-Rust, and Almut Arneth
Earth Syst. Dynam., 7, 893–915, https://doi.org/10.5194/esd-7-893-2016, https://doi.org/10.5194/esd-7-893-2016, 2016
Short summary
Short summary
The development of global cropland in the future depends on how many people there will be, how much meat and milk we will eat, how much food we will waste and how well farms will be managed. Uncertainties in these factors mean that global cropland could decrease from today's 1500 Mha to only 893 Mha in 2100, which would free land for biofuel production. However, if population rises towards 12 billion and global yields remain low, global cropland could also increase up to 2380 Mha in 2100.
Nir Y. Krakauer, Michael J. Puma, Benjamin I. Cook, Pierre Gentine, and Larissa Nazarenko
Earth Syst. Dynam., 7, 863–876, https://doi.org/10.5194/esd-7-863-2016, https://doi.org/10.5194/esd-7-863-2016, 2016
Short summary
Short summary
We simulated effects of irrigation on climate with the NASA GISS global climate model. Present-day irrigation levels affected air pressures and temperatures even in non-irrigated land and ocean areas. The simulated effect was bigger and more widespread when ocean temperatures in the climate model could change, rather than being fixed. We suggest that expanding irrigation may affect global climate more than previously believed.
Andreas Krause, Thomas A. M. Pugh, Anita D. Bayer, Mats Lindeskog, and Almut Arneth
Earth Syst. Dynam., 7, 745–766, https://doi.org/10.5194/esd-7-745-2016, https://doi.org/10.5194/esd-7-745-2016, 2016
Short summary
Short summary
We used a vegetation model to study the legacy effects of different land-use histories on ecosystem recovery in a range of environmental conditions. We found that recovery trajectories are crucially influenced by type and duration of former agricultural land use, especially for soil carbon. Spatially, we found the greatest sensitivity to land-use history in boreal forests and subtropical grasslands. These results are relevant for measurements, climate modeling and afforestation projects.
Grace W. Ngaruiya and Jürgen Scheffran
Earth Syst. Dynam., 7, 441–452, https://doi.org/10.5194/esd-7-441-2016, https://doi.org/10.5194/esd-7-441-2016, 2016
Short summary
Short summary
Climate change complicates rural conflict resolution dynamics and institutions. There is urgent need for conflict-sensitive adaptation in Africa. The study of social network data reveals three forms of fused conflict resolution arrangements in Loitoktok, Kenya. Where, extension officers, council of elders, local chiefs and private investors are potential conduits of knowledge. Efficiency of rural conflict resolution can be enhanced by diversification in conflict resolution actors and networks.
Daniel Paradis, Harold Vigneault, René Lefebvre, Martine M. Savard, Jean-Marc Ballard, and Budong Qian
Earth Syst. Dynam., 7, 183–202, https://doi.org/10.5194/esd-7-183-2016, https://doi.org/10.5194/esd-7-183-2016, 2016
Short summary
Short summary
According to groundwater flow and mass transport simulations, nitrate concentration for year 2050 would increase mainly due to the attainment of equilibrium conditions of the aquifer system related to actual nitrogen loadings, and to the increase in nitrogen loadings due to changes in agricultural practices. Impact of climate change on the groundwater recharge would contribute only slightly to that increase.
Yan Li, Nathalie De Noblet-Ducoudré, Edouard L. Davin, Safa Motesharrei, Ning Zeng, Shuangcheng Li, and Eugenia Kalnay
Earth Syst. Dynam., 7, 167–181, https://doi.org/10.5194/esd-7-167-2016, https://doi.org/10.5194/esd-7-167-2016, 2016
Short summary
Short summary
The impact of deforestation is to warm the tropics and cool the extratropics, and the magnitude of the impact depends on the spatial extent and the degree of forest loss. That also means location matters for the impact of deforestation on temperature because such an impact is largely determined by the climate condition of that region. For example, under dry and wet conditions, deforestation can have quite different climate impacts.
T. Brücher, M. Claussen, and T. Raddatz
Earth Syst. Dynam., 6, 769–780, https://doi.org/10.5194/esd-6-769-2015, https://doi.org/10.5194/esd-6-769-2015, 2015
Short summary
Short summary
A major link between climate and humans in northern Africa, and the Sahel in particular, is land use. We assess possible feedbacks between the type of land use and harvest intensity and climate by analysing a series of idealized GCM experiments using the MPI-ESM. Our study suggests marginal feedback between land use changes and climate changes triggered by strong greenhouse gas emissions.
B. D. Stocker and F. Joos
Earth Syst. Dynam., 6, 731–744, https://doi.org/10.5194/esd-6-731-2015, https://doi.org/10.5194/esd-6-731-2015, 2015
Short summary
Short summary
Estimates for land use change CO2 emissions (eLUC) rely on different approaches, implying conceptual differences of what eLUC represents. We use an Earth System Model and quantify differences between two commonly applied methods to be ~20% for historical eLUC but increasing under a future scenario. We decompose eLUC into component fluxes, quantify them, and discuss best practices for global carbon budget accountings and model-data intercomparisons relying on different methods to estimate eLUC.
E. Teferi, S. Uhlenbrook, and W. Bewket
Earth Syst. Dynam., 6, 617–636, https://doi.org/10.5194/esd-6-617-2015, https://doi.org/10.5194/esd-6-617-2015, 2015
Short summary
Short summary
This study concludes that integrated analysis of course and fine-scale, inter-annual and intra-annual trends enables a more robust identification of changes in vegetation condition. Seasonal trend analysis was found to be very useful in identifying changes in vegetation condition that could be masked if only inter-annual vegetation trend analysis were performed. The finer-scale intra-annual trend analysis revealed trends that were more linked to human activities.
D. S. Ward and N. M. Mahowald
Earth Syst. Dynam., 6, 175–194, https://doi.org/10.5194/esd-6-175-2015, https://doi.org/10.5194/esd-6-175-2015, 2015
Short summary
Short summary
The radiative forcing of land use and land cover change activities has recently been computed for a set of forcing agents including long-lived greenhouse gases, short-lived agents (ozone and aerosols), and land surface albedo change. Here we address where the global forcing comes from and what land use activities, such as deforestation or agriculture, contribute the most forcing. We find that changes in forest and crop area can be used to predict the land use radiative forcing in some regions.
E. T. N'Datchoh, A. Konaré, A. Diedhiou, A. Diawara, E. Quansah, and P. Assamoi
Earth Syst. Dynam., 6, 161–174, https://doi.org/10.5194/esd-6-161-2015, https://doi.org/10.5194/esd-6-161-2015, 2015
C. Rumbaur, N. Thevs, M. Disse, M. Ahlheim, A. Brieden, B. Cyffka, D. Duethmann, T. Feike, O. Frör, P. Gärtner, Ü. Halik, J. Hill, M. Hinnenthal, P. Keilholz, B. Kleinschmit, V. Krysanova, M. Kuba, S. Mader, C. Menz, H. Othmanli, S. Pelz, M. Schroeder, T. F. Siew, V. Stender, K. Stahr, F. M. Thomas, M. Welp, M. Wortmann, X. Zhao, X. Chen, T. Jiang, J. Luo, H. Yimit, R. Yu, X. Zhang, and C. Zhao
Earth Syst. Dynam., 6, 83–107, https://doi.org/10.5194/esd-6-83-2015, https://doi.org/10.5194/esd-6-83-2015, 2015
J. Pongratz, C. H. Reick, R. A. Houghton, and J. I. House
Earth Syst. Dynam., 5, 177–195, https://doi.org/10.5194/esd-5-177-2014, https://doi.org/10.5194/esd-5-177-2014, 2014
M. D. A. Rounsevell, A. Arneth, P. Alexander, D. G. Brown, N. de Noblet-Ducoudré, E. Ellis, J. Finnigan, K. Galvin, N. Grigg, I. Harman, J. Lennox, N. Magliocca, D. Parker, B. C. O'Neill, P. H. Verburg, and O. Young
Earth Syst. Dynam., 5, 117–137, https://doi.org/10.5194/esd-5-117-2014, https://doi.org/10.5194/esd-5-117-2014, 2014
M. Lindeskog, A. Arneth, A. Bondeau, K. Waha, J. Seaquist, S. Olin, and B. Smith
Earth Syst. Dynam., 4, 385–407, https://doi.org/10.5194/esd-4-385-2013, https://doi.org/10.5194/esd-4-385-2013, 2013
Q. Zhang, A. J. Pitman, Y. P. Wang, Y. J. Dai, and P. J. Lawrence
Earth Syst. Dynam., 4, 333–345, https://doi.org/10.5194/esd-4-333-2013, https://doi.org/10.5194/esd-4-333-2013, 2013
T. Gasser and P. Ciais
Earth Syst. Dynam., 4, 171–186, https://doi.org/10.5194/esd-4-171-2013, https://doi.org/10.5194/esd-4-171-2013, 2013
G. Modica, M. Vizzari, M. Pollino, C. R. Fichera, P. Zoccali, and S. Di Fazio
Earth Syst. Dynam., 3, 263–279, https://doi.org/10.5194/esd-3-263-2012, https://doi.org/10.5194/esd-3-263-2012, 2012
A. J. Pitman, N. de Noblet-Ducoudré, F. B. Avila, L. V. Alexander, J.-P. Boisier, V. Brovkin, C. Delire, F. Cruz, M. G. Donat, V. Gayler, B. van den Hurk, C. Reick, and A. Voldoire
Earth Syst. Dynam., 3, 213–231, https://doi.org/10.5194/esd-3-213-2012, https://doi.org/10.5194/esd-3-213-2012, 2012
M. Cerreta and P. De Toro
Earth Syst. Dynam., 3, 157–171, https://doi.org/10.5194/esd-3-157-2012, https://doi.org/10.5194/esd-3-157-2012, 2012
M. P. McCarthy, J. Sanjay, B. B. B. Booth, K. Krishna Kumar, and R. A. Betts
Earth Syst. Dynam., 3, 87–96, https://doi.org/10.5194/esd-3-87-2012, https://doi.org/10.5194/esd-3-87-2012, 2012
Cited articles
Ackerman, F., DeCanio, S. J., Howarth, R. B., and Sheeran, K.: Limitations
of integrated assessment models of climate change, Climatic Change, 95,
297–315, https://doi.org/10.1007/s10584-009-9570-x, 2009.
Agarwal, C., Green, G. M., Grove, J. M., Evans, T. P., and Schweik, C. M.: A
Review and Assessment of Land-Use Change Models: Dynamics of Space, Time,
and Human Choice, GTR NE-297, USDA, Forest Service, Northeastern Research
Station, Newton Square, PA, p. 61, 2002.
Ahmed, K. F., Wang, G., Silander, J., Wilson, A. M., Allen, J. M., Horton,
R., and Anyah, R.: Statistical downscaling and bias correction of climate
model outputs for climate change impact assessment in the US northeast,
Global Planet. Change, 100, 320–332, 2013.
Ahmed, K. F., Wang, G., Yu, M., Koo, J., and You, L.: Potential impact of
climate change on cereal crop yield in West Africa, Climatic Change, 133, 321–334, 2015.
Burney, J. A., Davis, S. J., and Lobell, D. B.: Greenhouse gas mitigation by
agricultural intensification, P. Natl. Acad. Sci., 107, 12052–12057, https://doi.org/10.1073/pnas.0914216107, 2010.
Ellis, E. C.: Anthropogenic transformation of the terrestrial biosphere, Philos.
T. Roy. Soc. Lond. A, 369, 1010–1035, 2011.
FAOSTAT Database on Agriculture, Food and Agriculture Organization of the United
Nations, Rome, Italy, available at: http://faostat3.fao.org/download/Q/QC/E,
last access: May 2015.
Foley, J. A., DeFries, R., Asner, G. P., Barford, C., Bonan, G., Carpenter,
S. R., Chapin, F. S., Coe, M. T., Daily, G. C., Gibbs, H. K., Helkowski, J. H.,
Holloway, T., Howard, E. A., Kucharik, C. J., Monfreda, C., Patz, J. A.,
Prentice, I. C., Ramankutty, N., and Snyder, P. K.: Global consequences of land
use, Science, 309, 570–574, 2005.
Giorgi, F., Coppola, E., Solmon, F., Mariotti, L., Sylla, M. B., Bi, X.,
Elguindi, N., Diro, G. T., Nair, V., Giuliani, G., Cozzini, S., Guttler, I.,
O'Brien, T. A., Tawfik, A. B., Shalaby, A., Zakey, A. S., Steiner, A. L.,
Stordal, F., Sloan, L. C., and Brankovic, C.: RegCM4: model description and
preliminary tests over multiple CORDEX domains, Clim. Res., 52, 7–29, 2012.
Hagos, S., Leung, L. R., Xue, Y., Boone, A., de Sales, F., Neupane, N., Huang,
M., and Yoon, J. H.: Assessment of uncertainties in the response of the African
monsoon precipitation to land use change simulated by a regional model, Clim.
Dynam., 43, 2765–2775, 2014.
Havlik, P., Schneider, U. A., Schmid, E., Böttcher, H.,
Fritz, S., Skalsky, R., Aoki, K., Cara, S. D., Kindermann, G.,
Kraxner, F., Leduc, S., McCallum, I., Mosnier, A., Sauer, T., and Obersteiner,
M.,: Global land-use implicationsof first and second generation biofuel
targets, Energy Pol., 39, 5690–5702, 2011.
Hurtt, G. C., Chini, L. P., Frolking, S., Betts, R. A., Feddema, J.,
Fischer, G., and Wang, Y. P.: Harmonization of land-use scenarios for the period
1500–2100: 600 years of global gridded annual land-use transitions, wood
harvest, and resulting secondary lands. Climatic Change, 109, 117–161,
https://doi.org/10.1007/s10584-011-0153-2, 2011.
Jones, J., Hoogenboom, G., Porter, C., Boote, K., Batchelor, W., Hunt, L.,
and Ritchie, J.: The DSSAT cropping system model, Eur. J. Agron., 18, 235–265,
https://doi.org/10.1016/S1161-0301(02)00107-7, 2003.
Kalnay, E. and Cai, M.: Impact of urbanization and land–use change on climate,
Nature, 423, 528–531, 2003.
Knox, J., Hess, T., Daccache, A., and Wheeler, T.: Climate change impacts on
crop productivity in Africa and South Asia, Environ. Res. Lett., 7, 034032,
https://doi.org/10.1088/1748-9326/7/3/034032, 2012.
Lambin, E. F., Geist, H. J., and Lepers, E.: Dynamics of land-use and
land-cover change in tropical regions, Annu. Rev. Environ. Resour., 28,
205–241, https://doi.org/10.1146/annurev.energy.28.050302.105459, 2003.
Lawrence, P. J. and Chase, T. N.: Representing a new MODIS consistent land
surface in the Community Land Model (CLM 3.0), J. Geophys. Res., 112, G01023,
https://doi.org/10.1029/2006JG000168, 2007.
Lotze-Campen, H., Müller, C., Bondeau, A., Rost, S., Popp, A., and
Lucht, W.: Global food demand, productivity growth, and the scarcity of land
and water resources: a spatially explicit mathematical programming approach,
Agr. Econ., 39, 325–338, 2008.
Mahmood, R., Quintanar, A. I., Conner, G., Leeper, R., Dobler, S., Pielke,
R. A., and Syktus, J.: Impacts of Land Use/Land Cover Change on Climate and
Future Research Priorities, B. Am. Meteorol. Soc., 91, 37–46, https://doi.org/10.1175/2009BAMS2769.1, 2010.
Mei, R. and Wang, G.: Rain follows logging in the Amazon? Results from
CAM3–CLM3, Clim. Dynam., 34, 983–996, https://doi.org/10.1007/s00382-009-0592-x, 2009.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Flanner, M. G., Kluzek, E.,
Lawrence, P. J., Levis, S., Swenson, S. C., Thornton, P. E., Dai, A., Decker, M.,
DIckinson, R., Feddema, J., Heald, C. L., Hoffman, F., Lamarque, J. F., Mahowald,
N., Niu, G.-Y., Qian, T., Randerson, J., Running, S., Sakaguchi, K., Slater, A.,
Stockli, R., Wang, A., Yang, Z.-L., Zeng, X., and Zeng, X: Technical description of
version 4.0 of the Community Land Model, NCAR Tech. Note NCAR/TN-478+STR, NCAR, 2010.
Parker, D. C., Manson, S. M., Janssen, M. A., Hoffmann, M. J., Deadman, P., Manson,
S. M., and Hall, S.: Multi-agent systems for the simulation of land-use and
land-cover change: a review, Ann. Assoc. Am. Geogr., 93, 314–337, 2003.
Pielke, R.A., Pitman, A., Niyogi, D., Mahmood, R., McAlpine, C., Hossain,
F., Klein Goldewijk K., Nair, U., Betts, R., Fall, S., Reichstein, M.,
Kabat, P., and de Noblet-Ducoudre, N.: Land use/land cover changes and climate:
modeling analysis and observational evidence, WIREs Clim. Change, 2, 828–850, 2011.
Pongratz, J., Reick, C. H., Raddatz, T., and Claussen, M.: Biogeophysical
versus biogeochemical climate response to historical anthropogenic land
cover change, Geophys. Res. Lett., 37, L08702, https://doi.org/10.1029/2010GL043010, 2010.
Ramankutty, N. and Foley, J. A.: Estimating historical changes in global land
cover: Croplands from 1700 to 1992, Global Biogeochem. Cy., 13, 997–1027, 1999.
Rosegrant, M. W.: International Model for Policy Analysis of Agricultural
Commodities and Trade (IMPACT) Model Description, International Food Policy
Research Institute, IFPRI, July 2012.
Rounsevell, M. D. A., Arneth, A., Alexander, P., Brown, D. G., de Noblet-Ducoudré,
N., Ellis, E., Finnigan, J., Galvin, K., Grigg, N., Harman, I., Lennox, J.,
Magliocca, N., Parker, D., O'Neill, B. C., Verburg, P. H., and Young, O.:
Towards decision-based global land use models for improved understanding of the
Earth system, Earth Syst. Dynam., 5, 117–137, https://doi.org/10.5194/esd-5-117-2014, 2014.
Schlenker, W. and Lobell, D. B.: Robust negative impacts of climate change
on African agriculture, Environ. Res. Lett., 5, 014010, https://doi.org/10.1088/1748-9326/5/1/014010, 2010.
Schmitz, C., van Meijl, H., Kyle, P., Nelson, G. C., Fujimori, S., Gurgel,
A., Alin, H.: Land-use change trajectories up to 2050: insights from a
global agro-economic model comparison, Agr. Econ., 45, 69–84, https://doi.org/10.1111/agec.12090, 2014.
Sheffield, J., Goteti, G., and Wood, E. F.: Development of a 50-yr, high
resolution global dataset of meteorological forcings for land surface
modeling, J. Climate, 13, 3088–3111, 2006.
Taylor, C. M., Lambin, E. F., Stephenne, N., Harding, R. J., and Essery, R. L.:
The influence of land use change on climate in the Sahel, J. Climate, 15, 3615–3629, 2002.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An Overview of CMIP5 and
the experiment design, B. Am. Meteorol. Soc., 93, 485-498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012.
Tubiello, F. N., Salvatore, M., Rossi, S., Ferrara, A., Fitton, N., and
Smith, P.: The FAOSTAT database of greenhouse gas emissions from
agriculture, Environ. Res. Lett., 8, 015009, https://doi.org/10.1088/1748-9326/8/1/015009, 2013.
Valbuena, D., Verburg, P. H., Bregt, A. K., and Ligtenberg, A.: An
agent-based approach to model land-use change at a regional scale, Landscape
Ecol., 25, 185–199, https://doi.org/10.1007/s10980-009-9380-6, 2010.
Verburg, P. H.: Simulating feedbacks in land use and land cover change
models, Landscape Ecol., 21, 1171–1183, https://doi.org/10.1007/s10980-006-0029-4, 2006.
Verburg, P. H., Kok, K., Pontius Jr., R. G., and Veldkamp, A.: Modeling
land-use and land-cover change, in: Land-use and Land-cover Change,
Springer, Berlin, Heidelberg, 117–135, 2006.
Wang, G., Yu, M., Pal, J. S., Mei, R., Bonan, G. B., Levis, S., and Thornton,
P. E.: On the development of a coupled regional climate-vegetation model
RCM-CLM-CN-DV and its validation in Tropical Africa, Clim. Dynam., 46, 515–539, 2016.
West, T. O., Le Page, Y., Huang, M., Wolf, J., and Thomson, A. M.: Downscaling
global land cover projections from an integrated assessment model for use in
regional analyses: results and evaluation for the US from 2005 to 2095,
Environ. Res. Lett., 9, 064004, https://doi.org/10.1088/1748-9326/9/6/064004, 2014.
World Bank: Investment in Agricultural Water for Poverty Reduction and
Economic Growth in Sub-Saharan Africa, A collaborative programme of ADB,
Synthesis Report, FAO, IFAD, IWMI and World Bank, 2008.
Xue, Y. and Shukla, J.: The influence of land surface properties on Sahel
climate. Part 1: desertification, J. Climate, 6, 2232–2245, 1993.
You, L. S. and Wood, S.: An entropy approach to spatial disaggregation of
agricultural production, Agricult. Syst., 90, 329–347, https://doi.org/10.1016/j.agsy.2006.01.008, 2006.
You, L. S., Wood, S., Wood-Sichra, U., Wu, W.: Generating global crop
distribution maps: From census to grid, Agricult. Syst., 127, 53–60, 2014.
Yu, M., Wang, G., Parr, D., and Ahmed, K. F.: Future changes of the terrestrial
ecosystem based on a dynamic vegetation model driven with RCP8.5 climate
projections from 19 GCMs, Climatic change, 127, 257–271, 2014.
Short summary
A prototype model LandPro was developed to study climate change impact on land use in West Africa. LandPro considers climate and socioeconomic factors in projecting anthropogenic future land use change (LULCC). The model projections reflect that relative impact of climate change on LULCC in West Africa is region dependent. Results from scenario analysis suggest that science-informed decision-making by the farmers in agricultural land use can potentially reduce crop area expansion in the region.
A prototype model LandPro was developed to study climate change impact on land use in West...
Special issue
Altmetrics
Final-revised paper
Preprint