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A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Land–Climate Interactions".

Deadline for manuscript submissions: closed (24 February 2023) | Viewed by 35037

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Special Issue Editors

Dr. Dongxue Zhao

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Guest Editor

Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Brisbane, Australia
Interests: soil; soil and plant properties; agriculture; soil water content and crop water use
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Daniel Rodriguez

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Guest Editor

Centre for Crop Sciences, Queensland Alliance for Agriculture and Food Innovation (QAAFI), The University of Queensland, Gatton Campus, QLD 4343, Australia
Interests: climate science; climate variability; food security; sustainable agriculture; crop science; agronomy; soil science
Special Issues, Collections and Topics in MDPI journals

Dr. Feng Liu

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Guest Editor

State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
Interests: soil science; digital soil mapping; geophysics

Dr. Tibet Khongnawang

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Guest Editor

Land Development Regional Office 5, Land Development Department, Khon Kaen 40000, Thailand
Interests: soil science; digital soil mapping; agriculture; environmental science

Special Issue Information

Dear Colleagues,

Over the past century, global temperature has increased due to the steadily rising CO2 levels. The effects of climate change are increasingly observable (IPCC 2021). Droughts, flooding, fires, and storms have become more frequent and extreme. This has adversely challenged natural ecosystems and agricultural productivity on which food, fiber, and nutrition security depend (Rolnick et al., 2019).

Addressing these challenges requires sustainable, actionable, and financially viable actions to miti-gate (reduce emissions of greenhouse gasses (GHGs)) and adapt (prepare for unavoidable changes). Land is both a source and sink of GHGs and drives energy, water, and aerosol exchange in the land–atmosphere system (Arneth et al., 2019). The adoption of more sustainable land management prac-tices (SLM) thus has great potential to address the global challenges of our time through reducing GHG emissions (The Emissions Gap Report 2021) and implementing resilience and disaster man-agement strategies.

SLM practices incorporate soil, water, and vegetation conservation measures. They were developed according to the principles of enhancing the productivity and protection of natural resources on an economically viable and socially acceptable basis. The development of SLM practices requires inte-grations of multiple sectors, including agriculture, pasture, forest, and water, various environmental and socioeconomic conditions, and multiple responses across local, regional, and national scales. In this sense, the successful implication of SLM practices requires widening the spectrum of studies to integrate different conditions and take into account different scales. Moreover, new strategies, technologies, and practices also need to be identified, tested, and adopted to reach Sustainable De-velopment Goals (SDGs) targets. New out-of-the-box ideas are needed from science.

We welcome submissions which develop (1) technological, (2) environmental, (3) political, (4) so-cial, and (5) economic innovations for sustainable land management and production under the global challenges of climate change. This Special Issue is open to relevant submissions from all dis-ciplines.

References

Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., ... & Bengio, Y. (2019). Tackling climate change with machine learning. arXiv preprint arXiv:1906.05433.

The Emissions Gap Report 2021 (United Nations Environment Programme, 2021).

IPCC, 2021: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press. In Press.

Arneth, A., Barbosa, H., Benton, T., Calvin, K., Calvo, E., Connors, S., ... & Zommers, Z. (2019). IPCC special report on climate change, desertification, land degradation, sustainable land management, food security, and greenhouse gas fluxes in terrestrial ecosystems. Summary for Policy Makers. Ge-neva: Intergovernmental Panel on Climate Change (IPCC).

Dr. Dongxue Zhao
Prof. Dr. Daniel Rodriguez
Dr. Feng Liu
Dr. Tibet Khongnawang
Guest Editors

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

climate adaption
environment
risks
crop yield
drought resilience
agronomy
smart agriculture
soil security
ecology
machine learning

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Published Papers (12 papers)

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20 pages, 2717 KiB

Open AccessArticle

Soil-to-Atmosphere GHG Fluxes in Hemiboreal Deciduous Tree and Willow Coppice Based Agroforestry Systems with Mineral Soil

by Andis Bārdulis, Dana Purviņa, Kristaps Makovskis, Arta Bārdule and Dagnija Lazdiņa

Land 2023, 12(3), 715; https://doi.org/10.3390/land12030715 - 21 Mar 2023

Cited by 1 | Viewed by 2062

Abstract

In this study, we estimated the magnitude of soil-to-atmosphere carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) fluxes in deciduous tree and willow coppice based agroforestry systems in hemiboreal Latvia. We studied systems combining hybrid alder, hybrid aspen, silver birch, black alder, and willow clones with perennial reed canary grass (RCG), which were established in the spring of 2011 in former cropland with mineral soil. Three different soil fertilisation practices were initially applied (control without fertilisation, fertilisation with wood ash, and sewage sludge). Measurements of fluxes of greenhouse gases were taken in both deciduous tree, willow coppice and RCG plots using a closed opaque manual chamber method, from June 2020 to October 2021. Soil CO₂ fluxes (the sum of autotrophic and heterotrophic respiration) were increased in RCG plots compared to plots under willow and deciduous tree canopies, while the highest mean CH₄ fluxes were found in willow coppice plots. No impact of dominant vegetation type on instantaneous soil N₂O fluxes was found. Temperature was the key determinant of the magnitude of CO₂ and N₂O fluxes. The highest soil CO₂ and N₂O fluxes were detected during the summer and decreased in the following order: summer, autumn, spring, winter. There were no pronounced relationships between soil CH₄ fluxes and temperature. Full article

(This article belongs to the Special Issue Climate Change and Sustainable Land Production)

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22 pages, 3616 KiB

Open AccessArticle

The Farm’s Orientation towards Sustainability: An Assessment Using FADN Data in Italy

by Concetta Cardillo, Antonella Di Fonzo and Claudio Liberati

Land 2023, 12(2), 301; https://doi.org/10.3390/land12020301 - 20 Jan 2023

Cited by 6 | Viewed by 1954

Abstract

The new Common Agricultural Policy (CAP) for the period 2023–2027 commits farmers towards achieving ambitious environmental objectives through farm organization and management. This European agricultural policy has adapted to the contemporary challenges faced by the new model of agricultural development. It aims to enhance the contribution of agriculture to the EU’s environmental and climate objectives while providing better targeted support to small-scale farmers to promote farms’ competitiveness. The main objective of this paper is to describe Italian farms and classify them into groups based on their main characteristics, as well as to analyze their performance and behavior in terms of sustainability and competitiveness. The novelty and innovativeness of this study are found in the data used; a 2020 dataset from the Italian Farm Accounting Data Network (FADN) was used. The quality of FADN data in farm sustainability assessment is widely acknowledge in the literature. To achieve the purpose of this study, a multivariate analysis, in particular, the Principal Components Analysis (PCA), and a Cluster Analysis (CA) were applied. These analyses helped us to obtain the factorial axes which then enabled us to identify economic information on farms, and a better interpretation of farmers’ aptitude to undertake environmentally friendly actions. As a result, eight groups of farms were identified, and their characteristics and performance were described at Italian district level. The results of the study reflect the influence of European interventions towards encouraging farmers to use more environmentally friendly agricultural practices. Under this perspective, the findings contribute to the current debate on green architecture pursued by the future European agricultural policy. Full article

(This article belongs to the Special Issue Climate Change and Sustainable Land Production)

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16 pages, 3195 KiB

Open AccessArticle

Climate Change and Diurnal Warming: Impacts on the Growth of Different Vegetation Types in the North–South Transition Zone of China

by Li Li, Lianqi Zhu, Nan Xu, Ying Liang, Zhengyu Zhang, Junjie Liu and Xin Li

Land 2023, 12(1), 13; https://doi.org/10.3390/land12010013 - 21 Dec 2022

Cited by 4 | Viewed by 1428

Abstract

Since land use/cover change profoundly impacts climate change and global warming has become an irreversible trend in the Anthropocene, there have been numerous global studies on the impact of climate change on vegetation growth (VG). However, the effects of climate extremes on the growth and direction of various vegetation types need to be better investigated, especially in the climate transition zones. In this paper, we examined the effect of diurnal warming on the growth of various types of vegetation in China’s north–south transition zone. Based on the daily observation data of 92 meteorological stations in the Qinling-Daba (Qinba) mountainous area from 1982 to 2015, coupled with the Normalized Difference Vegetation Index (NDVI) and data on the type of vegetation. This research examined the temporal changes in the highest and lowest temperatures during the last 33 years using trend analysis. Second-order correlation analysis was used to investigate vegetation NDVI response characteristics to diurnal warming and to examine the effect of diurnal warming on the growth of different vegetation types. Our results showed that maximum temperature (T_max) and minimum temperature (T_min) showed an obvious upward trend, with the daytime temperature increase rate 1.2 times that at night, but failing the t-test. In addition, diurnal warming promoted vegetation growth, with NDVI associated positively correlated with T_max at approximately 91.2% of the sites and 3492 rasters and with T_min at roughly 53.25% of the sites and 2864 rasters. Spatial significance analysis showed an apparent difference, but few areas passed the t-test. Furthermore, daytime warming enhanced the growth of grasses, shrubs, deciduous broad-leaved forests, crops, and conifers, while the effect of nighttime warming on VG had a positive effect only on the growth of evergreen broad-leaved forest vegetation. These findings reveal the mechanisms of the impact of climate extremes on VG under global change, particularly the extent to which different vegetation types in climatic transitional zones respond to climate extremes. Full article

(This article belongs to the Special Issue Climate Change and Sustainable Land Production)

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15 pages, 11031 KiB

Open AccessArticle

Investigating the Impacts of Urbanization on Vegetation Net Primary Productivity: A Case Study of Chengdu–Chongqing Urban Agglomeration from the Perspective of Townships

by Jianshu Li, Mo Bi and Guoen Wei

Land 2022, 11(11), 2077; https://doi.org/10.3390/land11112077 - 18 Nov 2022

Cited by 5 | Viewed by 1872

Abstract

As an emerging national strategic urban agglomeration in China, the changing trend of vegetation net primary productivity (NPP) and the impact of the urbanization level (UL) on carbon cycle functions in the Chengdu–Chongqing urban agglomeration (CUA) have received increasing attention. Previous studies have largely overlooked externalities and the heterogeneity of urbanization effects, and urbanization has also been analyzed in isolation (with focus being on land and population urbanization). In this study, the spatial evolution of NPP was evaluated from 2000 to 2020 at the township level (3859) using multivariate remote sensing data and a comprehensive index (UL) that included population urbanization, land urbanization, and economic urbanization. Bivariate spatial autocorrelation, spatial Durbin models, and geographically weighted regression models were used to analyze the spatial externalities of urbanization impacts and assess the global and local effects. The results show that the region’s mean NPP increased by 177.25 g*c/m² (annual growth of 1.59%), exhibiting a distribution of “low in the middle and high in the periphery” and low-value clustering along major traffic arteries and rivers. Low-value-NPP areas were mainly located in urban centers, while the high-level areas were in the mountainous region (in the southwest and southeast) and significantly expanded over time. Negative correlation clusters were the main clustering types between the UL and NPP; the “High-Low” negative correlation clusters accelerated outward from the urban centers of Chengdu and Chongqing. Overall, urbanization had negative direct and spillover effects on NPP, exhibiting spatial non-stationarity of the negative driving effect within the urban agglomeration. The results indicate the need to strengthen regional ecological joint governance and adopt more place-based urbanization optimization strategies. This study offers new insights to help to reduce the constraining effects of urbanization on vegetation productivity and ecological functions from the perspectives of population agglomeration, land expansion, and industrial construction. Full article

(This article belongs to the Special Issue Climate Change and Sustainable Land Production)

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19 pages, 1795 KiB

Open AccessArticle

Impact of Internet Use on Farmers’ Organic Fertilizer Application Behavior under the Climate Change Context: The Role of Social Network

by Qianhui Ma, Shaofeng Zheng and Peng Deng

Land 2022, 11(9), 1601; https://doi.org/10.3390/land11091601 - 18 Sep 2022

Cited by 22 | Viewed by 3425

Abstract

Climate change and global warming significantly influence farmers’ activity and lead to lower production yield. To increase production without deteriorating the environment, it is vital to substitute chemical fertilizer with organic fertilizer. The utilization of organic fertilizer not only improves the soil quality but also protects the environment and helps mitigate global warming repercussions. So, there is a need to promote organic fertilizer utilization. The Internet, as an essential information medium, presently has a profound influence on farmers’ production behavior. However, the relationship between Internet use and the application of organic fertilizer is explicitly sparse, especially in China. Using the survey data of 797 vegetable growers, the current study explores the impact of Internet use on farmers’ organic fertilizer application behavior. The present study employs the propensity score matching (PSM) method to meet the study objective. According to the findings, it is unveiled that the Internet significantly promotes behavior towards applying organic fertilizer by approximately 10%. Further, the heterogeneity results show that the degree of impact varies due to differences in the level of education, vegetable farming income, and the number of vegetable laborers in the family. Moreover, social networks are also used to explore the nexus between the Internet and organic fertilizer application. The findings reveal that social networks favorably play the mediating role. The overall results propose that policymakers should establish the Internet infrastructure and an official online platform to help farmers consolidate and extend the scale of their social networks and exchange information more conveniently to improve their ability to apply environment-friendly production technology. Full article

(This article belongs to the Special Issue Climate Change and Sustainable Land Production)

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23 pages, 1038 KiB

Open AccessArticle

Influence of Natural Disaster Shock and Collective Action on Farmland Transferees’ No-Tillage Technology Adoption in China

by Chenle Xue, Dan Qiao and Noshaba Aziz

Land 2022, 11(9), 1511; https://doi.org/10.3390/land11091511 - 8 Sep 2022

Cited by 2 | Viewed by 2411

Abstract

Climate change in natural disasters such as droughts and floods has caused people to adopt, extend, and diffuse adaptive agricultural technologies. Meanwhile, the development of the farmland leasing market has pushed agricultural laborers to migrate from rural to urban areas, resulting in less participation in collective action. It is generally believed that no-tillage technology lessens the agricultural production risks instigated by climate change and natural disasters. However, previous literature has given little attention to this phenomenon, especially in the context of China. So, to fill this gap, the current study explores the influence of natural disaster shock and collective action on farmland transferees’ no-tillage technology adoption using the data of 621 farmland transferees from Shaanxi, Gansu, and Ningxia provinces, China. By using Heckman’s two-stage and moderating-effect models, the findings initially reveal that in the sample, 249 farmland transferees adopt no-tillage technology, accounting for 40.10% of farmland transferees. The farmland area in which no-tillage technology is adopted accounts for 23.90% of the total farmland area. Natural disaster shock exerts a positive and significant influence on transferees’ no-tillage technology adoption, i.e., if the intensity of natural disaster shock increases by one unit, the adoption rate and adoption degree will increase by 24.9% and 9.5%, respectively. Meanwhile, collective action also positively and significantly impacts transferees’ no-tillage technology adoption. If the number of transferees participating in collective action increases by one unit, the adoption rate and degree will increase by 13.3% and 6.5%, respectively. Further, it is found that collective action positively moderates the relationship between natural disaster shock and the adoption of no-tillage technology by farmland transferees. Additionally, educational level, agricultural income, farmland area, etc., are also found to influence transferees’ no-tillage technology adoption significantly. Moreover, based on gender and organizational participation differences, the findings reveal that the effects of natural disaster shock and collective action are heterogeneous. The results propose that policymakers should take countermeasures such as providing training in no-tillage skills, raising no-tillage subsidy standards, and guiding long-term farmland transference. Full article

(This article belongs to the Special Issue Climate Change and Sustainable Land Production)

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19 pages, 5902 KiB

Open AccessArticle

Spatial Relationship between Land Use Patterns and Ecosystem Services Value—Case Study of Nanjing

by Ming Lu, Yan Zhang, Fan Liang and Yuanxiang Wu

Land 2022, 11(8), 1168; https://doi.org/10.3390/land11081168 - 27 Jul 2022

Cited by 12 | Viewed by 2387

Abstract

The degree of land use reflects the progress of social and economic development; however, it also has a direct impact on land resources. Maximizing the ecosystem services of land resources in a limited space is a key issue in China’s rapid urbanization. Therefore, this study aims to analyze the spatial relationship between land use patterns and ecosystem services to enhance the benefits of urban ecology. First, we used the landscape pattern index to represent land use patterns and the equivalence factor method to quantify the ecosystem services value (ESV); second, spatial autocorrelation and spatial autoregression were used to explore the spatial relationship between the landscape pattern index and ESV. Our main conclusions were that (1) the landscape pattern index and ESV both showed obvious spatial aggregation, but that of ESV was more significant; (2) the largest patch index and contagion index had a greater degree of influence on ESV than other variables, with the largest patch index having a positive effect and the contagion index having a negative effect; (3) it was necessary to cultivate the landscape dominance of land patches in ecological spatial regulation and to form large-scale ecological agglomeration in key ecological source areas and nodes. The research results can ensure that land resources exert a higher level of ecological value by adjusting the spatial form of the landscape patch. Full article

(This article belongs to the Special Issue Climate Change and Sustainable Land Production)

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19 pages, 9538 KiB

Open AccessArticle

Estimation of Heavy Metal Content in Soil Based on Machine Learning Models

by Shuaiwei Shi, Meiyi Hou, Zifan Gu, Ce Jiang, Weiqiang Zhang, Mengyang Hou, Chenxi Li and Zenglei Xi

Land 2022, 11(7), 1037; https://doi.org/10.3390/land11071037 - 8 Jul 2022

Cited by 21 | Viewed by 4009

Abstract

Heavy metal pollution in soil is threatening the ecological environment and human health. However, field measurement of heavy metal content in soil entails significant costs. Therefore, this study explores the estimation method of soil heavy metals based on remote sensing images and machine learning. To accurately estimate the heavy metal content, we propose a hybrid artificial intelligence model integrating least absolute shrinkage and selection operator (LASSO), genetic algorithm (GA) and error back propagation neural network (BPNN), namely the LASSO-GA-BPNN model. Meanwhile, this study compares the accuracy of the LASSO-GA-BPNN model, SVR (Support Vector Regression), RF (Random Forest) and spatial interpolation methods with Huanghua city as an example. Furthermore, the study uses the LASSO-GA-BPNN model to estimate the content of eight heavy metals (including Ni, Pb, Cr, Hg, Cd, As, Cu, and Zn) in Huanghua and visualize the results in high resolution. In addition, we calculate the Nemerow index based on the estimation results. The results denote that, the simultaneous optimization of BPNN by LASSO and GA can greatly improve the estimation accuracy and generalization ability. The LASSO-GA-BPNN model is a more accurate model for the estimate heavy metal content in soil compared to SVR, RF and spatial interpolation. Moreover, the comprehensive pollution level in Huanghua is mainly low pollution. The overall spatial distribution law of each heavy metal content is very similar, and the local spatial distribution of each heavy metal is different. The results are of great significance for soil pollution estimation. Full article

(This article belongs to the Special Issue Climate Change and Sustainable Land Production)

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13 pages, 573 KiB

Open AccessArticle

How Does Land Tenure Security Affect Farm Succession? Evidence from Apple Growers in China

by Qiangqiang Zhang, Jiaying Tian, Jie Zheng, Nazir Muhammad Abdullahi and Xuexi Huo

Land 2022, 11(7), 1036; https://doi.org/10.3390/land11071036 - 8 Jul 2022

Cited by 7 | Viewed by 2148

Abstract

The security of farmland property rights is an important factor that affects farmland investment and succession, and farm succession is highly significant for achieving sustainable agricultural development. In this study, based on survey data obtained from 1012 apple growers in Shandong and Shaanxi Provinces, we analyzed the impact of land tenure security on the farm succession willingness of farmers and related paths by constructing binary logistic regression and mediating effect models. The results showed that: (1) land tenure security plays a significant role in promoting the farm succession willingness of farmers; and that (2) land tenure security promotes farm succession willingness by improving the farmland investment intentions of farmers. In the future, reforms of the farmland property rights system need to ensure the security of farmland property rights. In addition, with the influence of climate change, it is necessary to encourage farmers with advantageous agricultural resource endowments to invest in farmland and intergenerational transfers, as well as inducing farmers who lack advantageous agricultural resource endowments to conduct non-agricultural transfers, thereby providing more opportunities and a greater development area for agricultural land transfers and agricultural-scale operations. Full article

(This article belongs to the Special Issue Climate Change and Sustainable Land Production)

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16 pages, 5432 KiB

Open AccessArticle

Determinants of Soil Bacterial Diversity in a Black Soil Region in a Large-Scale Area

by Jiacheng Niu, Huaizhi Tang, Qi Liu, Feng Cheng, Leina Zhang, Lingling Sang, Yuanfang Huang, Chongyang Shen, Bingbo Gao and Zibing Niu

Land 2022, 11(5), 731; https://doi.org/10.3390/land11050731 - 12 May 2022

Cited by 7 | Viewed by 2720

Abstract

Soils in black soil areas are high in organic matter and rich in nutrients. Soil microorganisms are particularly critical to cultivated land. The objective of this study was to explore the influencing factors of soil bacterial diversity under special regional conditions in a black soil region. In this study, the cultivated land in a black soil area was used as the study area and a random forest was used to map the bacterial abundance in the black soil area based on 1810 sample points. DbMEM analysis was used to quantify the spatial effect of the black soil area and to identify the influencing factors of soil bacterial abundance in the black soil area in combination with soil properties, terrain, and climate. Results of a variation division showed that broad (8.336%), AT (accumulated temperature, 5.520%), and pH (4.184%) were the main factors affecting soil bacterial diversity. The broad effect was more significant in the spatial effect, which may be related to the local landscape configuration. Overall, our research showed that the influencing factors of soil bacteria will be affected by regional characteristics. Full article

(This article belongs to the Special Issue Climate Change and Sustainable Land Production)

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25 pages, 1874 KiB

Open AccessArticle

Exploring the Role of Contiguous Farmland Cultivation and Adoption of No-Tillage Technology in Improving Transferees’ Income Structure: Evidence from China

by Ruishi Si, Yumeng Yao, Xueqian Zhang, Qian Lu and Noshaba Aziz

Land 2022, 11(4), 570; https://doi.org/10.3390/land11040570 - 13 Apr 2022

Cited by 5 | Viewed by 2392

Abstract

Seasonal alternations of extreme weather such as continuous drought and rare rainstorms significantly influence farmers’ adoption of agricultural technologies. Compared with traditional tillage, no-tillage technology has more advantages to cope with extreme weather. It is hypothesized that the cultivation of contiguous farmland is still minimal in spite of the transference of farmland on a large scale in China, which ultimately halts the adoption of no-tillage technology and influences the income of households. The current study used 793 farmland transferees’ data from Shaanxi, Gansu, and Ningxia provinces of China to explore this phenomenon empirically. By employing the endogenous switching regression model, the study revealed that contiguous farmland significantly promotes the adoption of no-tillage technology and positively influences households’ agricultural and non-agricultural income. Meanwhile, the moderating effect of the stability of farmland rental contracts is explored. Further, it was also found that education level, organizational participation, relationship networks, and information acquisition channels influence the income of transferees who opt for no-tillage technology. The study further revealed that if a transferee who opts for no-tillage technology switches to traditional technology, their agricultural and non-agricultural income will decrease by 0.2893 and 1.6979 ten thousand yuan (RMB), respectively. In contrast, if a transferee who opts for traditional technology then switches to adopt no-tillage technology, their agricultural and non-agricultural income will increase by 0.1919 and 1.3044 ten thousand yuan (RMB), respectively. Conclusively, the current study’s empirical findings offer policymakers possible guidelines to devise strategies and encourage transferees to opt for no-tillage applications to increase their families’ income. Full article

(This article belongs to the Special Issue Climate Change and Sustainable Land Production)

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27 pages, 5077 KiB

Open AccessPerspective

Sustainable Land Management and Climate Change Adaptation for Small-Scale Land Users in Sub-Saharan Africa

by William Critchley, Nicole Harari, Eefke Mollee, Rima Mekdaschi-Studer and Joana Eichenberger

Land 2023, 12(6), 1206; https://doi.org/10.3390/land12061206 - 10 Jun 2023

Cited by 13 | Viewed by 5961

Abstract

Land is both a source and a sink of carbon dioxide (CO₂), the chief greenhouse gas. Through sustainable land management (SLM), it can capture extra CO₂ and store it as carbon in vegetation and soil. SLM can also reduce CO₂ emissions from the land. Thus, SLM is viewed as the key land-based solution for climate change mitigation. Yet, SLM also provides effective climate change (CC) adaptation practices—such as agroforestry, mulching and water harvesting—which confer resilience, and simultaneously help secure production. This is especially valuable for land users in sub-Saharan Africa (SSA) who depend on rainfed agriculture. They are amongst the poorest on Earth and the most vulnerable to CC impacts, despite their minimal carbon footprint. The World Overview of Conservation Approaches and Technologies (WOCAT) manages the Global SLM Database: this holds a rich and ever-growing collection of SLM practices. Analysis of the database for rainfed SSA sheds light on which SLM technologies are effective in CC adaptation, and how well they cope with changing rainfall and temperature. Both “mechanisms” and “attributes” are explored, yielding new insights. This perspective paper showcases current developments in the field, and summarizes future directions for SLM as a CC adaptation solution for land users in SSA. Full article

(This article belongs to the Special Issue Climate Change and Sustainable Land Production)

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