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Land
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Land Use Change Feedbacks with Climate
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Land Use Change Feedbacks with Climate

A special issue of Land (ISSN 2073-445X).

Deadline for manuscript submissions: closed (31 March 2014) | Viewed by 53464

Special Issue Editor

Prof. Dr. Heiko Balzter

E-Mail Website
Guest Editor
NERC National Centre for Earth Observation, Leicester Institute for Space and Earth Observation, School of Geography, Geology and Environment, University of Leicester, University Road, Leicester LE1 7RH, UK
Interests: landscape and climate research; land surface modelling; terrestrial remote sensing; synthetic aperture radar (SAR); light detection and ranging (LIDAR); forest monitoring, carbon cycle and climate change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Land cover and land use influence the biogeochemical fluxes and the surface energy balance at the land/atmosphere boundary. Land use change can thus trigger biological, chemical, or physical feedbacks to the climate system via the atmosphere. In turn, climate change has begun to influence land use decisions as people are beginning to adapt to unavoidable global climate change in a warmer world with more weather extremes. Examples of such feedback processes are the urban heat island effect, the albedo feedback and the carbon cycle feedbacks. However, land use change is not only driven by climate change adaptation policies. It is influenced by a complex web of factors, including economic globalization, natural resource availability, commodity prices, regional infrastructure, social population demography and individual preferences, and government policies. Land is a limited resource and is becoming precious as the world’s population is growing. Multiple and often conflicting demands on land use mean that decisions have to be taken. The United Nations initiative to reduce greenhouse gas emissions from deforestation and forest degradation (REDD+), for example, places a different demand on tropical forest land than the rising demand for biofuels and food products.
This Special Issue provides an interdisciplinary perspective on land use change at local, regional, national and global scales and how it feeds back to the climate system. It applies a range of modeling, remote sensing, socio-economic and other methods to the problem of human/environment interactions, driving land use change and its implications for future scenarios of climate change.

Prof. Dr. Heiko Balzter
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • land use change
  • land cover change
  • climate change
  • land/atmosphere interactions
  • land surface modeling
  • biogeochemical cycles
  • remote sensing

Published Papers (5 papers)

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Research

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2148 KiB  
Article
The Re-Greening of the Sahel: Natural Cyclicity or Human-Induced Change?
by Issa Ouedraogo, Jürgen Runge, Joachim Eisenberg, Jennie Barron and Séraphine Sawadogo-Kaboré
Land 2014, 3(3), 1075-1090; https://doi.org/10.3390/land3031075 - 03 Sep 2014
Cited by 34 | Viewed by 9687
Abstract
The Sahel has been the focus of scientific interest in environmental-human dynamics and interactions. The objective of the present study is to contribute to the recent debate on the re-greening of Sahel. The paper examines the dynamics of barren land in the Sahel [...] Read more.
The Sahel has been the focus of scientific interest in environmental-human dynamics and interactions. The objective of the present study is to contribute to the recent debate on the re-greening of Sahel. The paper examines the dynamics of barren land in the Sahel of Burkina Faso through analysis of remotely-sensed and rainfall data from 1975–2011. Discussions with farmers and land management staff have helped to understand the anthropogenic efforts toward soil restoration to enable the subsistence farming agriculture. Results showed that area of barren land has been fluctuating during the study period with approximately 10-year cyclicity. Similarly, rainfall, both at national and local levels has followed the same trends. The trends of the area of barren land and rainfall variability suggest that when rainfall increases, the area of barren land decreases and barren land increases when rainfall decreases. This implies that rainfall is one of the main factors driving the change in area of barren land. In addition, humans have contributed positively and negatively to the change by restoring barren lands for agriculture using locally known techniques and by accelerating land degradation through intensive and inappropriate land use practices. Full article
(This article belongs to the Special Issue Land Use Change Feedbacks with Climate)
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1179 KiB  
Article
Investigation of the Dominant Factors Influencing the ERA15 Temperature Increments at the Subtropical and Temperate Belts with a Focus over the Eastern Mediterranean Region
by Tali Hirsch-Eshkol, Anat Baharad and Pinhas Alpert
Land 2014, 3(3), 1015-1036; https://doi.org/10.3390/land3031015 - 22 Aug 2014
Cited by 2 | Viewed by 8272
Abstract
A stepwise multi regression-based statistics was employed for prioritizing the influence of several factors, anthropogenic and/or natural, on the ERA15 temperature increments. The 5 factors that are defined as predictors are: topography, aerosol index (TOMS-AI), tropospheric vertical velocity along with two anthropogenic factors, [...] Read more.
A stepwise multi regression-based statistics was employed for prioritizing the influence of several factors, anthropogenic and/or natural, on the ERA15 temperature increments. The 5 factors that are defined as predictors are: topography, aerosol index (TOMS-AI), tropospheric vertical velocity along with two anthropogenic factors, population density and land use changes (Land Use Change Index (LUCI) and Normalized Difference Vegetation Index (NDVI) trends). The seismic hazard assessment factor was also chosen as the “dummy variable” for validity. Special focus was given to the land use change factor, which was based on two different data sets; Human Impacts on Terrestrial Ecosystems (HITE) data of historical land use/land cover data and of NDVI trends during 1982 and 1991. The increment analysis updates of temperature, increments analysis update (IAU) (T), the predicted variable, was obtained from the ERA15 (1979–1993) reanalysis. The research consists of both spatial and vertical analyses, as well as the potential synergies of selected variables. The spatial geographic analysis is divided into three categories; (1) coarse region; (2) subregion analysis; and (c) a “small cell” of 4° × 4° analysis covering the global domain. It is shown that the following three factors, topography, TOMS-AI and NDVI, are statistically significant (at the p < 0.05 level) in the relationship with the IAU (T), which means that they are the most effective predictors of IAU (T), especially at the 700-hPa level during March–June. The 850-hPa level presents the weakest contribution to IAU (T), probably due to the contradicting influences of the various variables at this level. It was found that the land use effect, as expressed by the NDVI trends factor, shows a strong decrease with height and is one of the most influential near-surface factors over the East Mediterranean (EM), which explains up to 20% of the temperature increments in January at 700 hPa. Moreover, its influence is significant (p < 0.05) through all of the different stages of the multiple regression runs, a major finding not quantified earlier. The choice of monthly means was found to be not optimal, particularly for the tropospheric vertical velocity, due to the averaging of the synoptic systems within a month. Full article
(This article belongs to the Special Issue Land Use Change Feedbacks with Climate)
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1400 KiB  
Article
The Positive Feedback Loop between the Impacts of Climate Change and Agricultural Expansion and Relocation
by Bojana Bajželj and Keith S. Richards
Land 2014, 3(3), 898-916; https://doi.org/10.3390/land3030898 - 25 Jul 2014
Cited by 19 | Viewed by 19111
Abstract
Climate change and agriculture influence each other. The effects of climate change on agriculture seem to be predominantly negative, although studies show a large variation in impacts between crops and regions. To compensate for these effects, agriculture can either intensify or expand in [...] Read more.
Climate change and agriculture influence each other. The effects of climate change on agriculture seem to be predominantly negative, although studies show a large variation in impacts between crops and regions. To compensate for these effects, agriculture can either intensify or expand in area; both of these options increase greenhouse gas emissions. It is therefore likely that such negative effects will increase agriculture’s contribution to climate change, making this feedback a positive, self-reinforcing one. We have previously used a data-driven model to examine greenhouse gas emissions in 2050 related to agricultural scenarios of increasing demand for food. Here, we extend this approach by introducing the impacts of climate change on agricultural yields. We estimate the additional losses of natural habitats and increases in greenhouse gas emissions resulting from agricultural expansion and relocation induced by the negative effects of climate change. We studied two climate change scenarios and different assumptions about trade. These additional impacts caused by climate change are found to be relatively moderate compared to demand-driven impact, but still significant. They increase greenhouse gas emissions from land use change by an additional 8%–13%. Climate change tends to aggravate the effects of demand drivers in critical regions. Current emission scenarios are underestimates in that they do not include these feedback effects. Full article
(This article belongs to the Special Issue Land Use Change Feedbacks with Climate)
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1406 KiB  
Article
Comparing Path Dependence and Spatial Targeting of Land Use in Implementing Climate Change Responses
by Iain Brown, Marie Castellazzi and Diana Feliciano
Land 2014, 3(3), 850-873; https://doi.org/10.3390/land3030850 - 23 Jul 2014
Cited by 12 | Viewed by 6821
Abstract
Land use patterns are the consequence of dynamic processes that often include important legacy issues. Evaluation of past trends can be used to investigate the role of path dependence in influencing future land use through a reference “business as usual” (BAU) scenario. These [...] Read more.
Land use patterns are the consequence of dynamic processes that often include important legacy issues. Evaluation of past trends can be used to investigate the role of path dependence in influencing future land use through a reference “business as usual” (BAU) scenario. These issues are explored with regard to objectives for woodland expansion in Scotland as a major pillar of climate change policy. Land use changes based upon recent trends and future transient scenarios to 2050 are used to assess viability of targets for reducing greenhouse gas emissions using analysis based on net emission change factors. The BAU scenario is compared with alternative future scenarios incorporating policy targets and stronger spatial targeting of land use change. Analysis highlights recent trends in new woodland planting on lower quality agricultural land due to socioeconomic and cultural factors. This land is mainly in the wetter uplands and often on carbon-rich soils. Woodland planting following this path dependence can therefore result in net carbon emissions for many years into the future due to soil disturbance during establishment. In contrast, alternative scenarios with more lowland woodland planting have net sequestration potential, with greatest benefits when carbon-rich soils are excluded from afforestation. Spatial targeting can also enhance other co-benefits such as habitat networks and climate change adaptation. Full article
(This article belongs to the Special Issue Land Use Change Feedbacks with Climate)
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Review

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794 KiB  
Review
Climate–Human–Land Interactions: A Review of Major Modelling Approaches
by Melania Michetti and Matteo Zampieri
Land 2014, 3(3), 793-833; https://doi.org/10.3390/land3030793 - 22 Jul 2014
Cited by 22 | Viewed by 8579
Abstract
International agreements on climate change have highlighted the role of land in climate and human dynamics, making it an issue of global importance. The modelling of land-related processes, sectors, and activities has recently become a central topic in economic and policy theory, as [...] Read more.
International agreements on climate change have highlighted the role of land in climate and human dynamics, making it an issue of global importance. The modelling of land-related processes, sectors, and activities has recently become a central topic in economic and policy theory, as well as within environmental sciences. Modelling strategies have been improved and new datasets have come into light for land-cover and land-use change analysis. However, unexpected human behavior and natural constraints challenge the modelling of interdependences and feedback mechanisms amongst economies, societies, and the environment, resulting from land-use and cover change. This paper provides a detailed overview of the most representative and advanced methods and models developed to represent climate–human–land interactions. It offers a critical discussion about relevant methodological aspects, missing knowledge, and areas for future research. Full article
(This article belongs to the Special Issue Land Use Change Feedbacks with Climate)
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