Integration of Abandoned Lands in Sustainable Agriculture: The Case of Terraced Landscape Re-Cultivation in Mediterranean Island Conditions

Agriculture terraces constitute a significant element of the Mediterranean landscape, enabling crop production on steep slopes while protecting land from desertification. Despite their ecological and historical value, terrace cultivation is threatened by climate change leading to abandonment and further marginalization of arable land imposing serious environmental and community hazards. Re-cultivation of terraced landscapes could be an alternative strategy to mitigate the climate change impacts in areas of high vulnerability encouraging a sustainable agroecosystem to ensure food security, rural development and restrain land desertification. The article presents the case study of abandoned terrace re-cultivation in the Aegean Island of Andros, using a climate smart agriculture system, which involves the establishment of an extensive meteorological network to monitor the local climate and hydrometeorological forecasting. Along with terrace site mapping and soil profiling the perfomance of cereal and legume crops was assessed in a low-input agriculture system. The implementation of a land stewardship (LS) plan was indispensable to overcome mainly land fragmentation issues and to transfer know-how. It was found that climate data are key drivers for crop cultivation and production in the island rainfed farming system. The study revealed that terrace soil quality could be improved through cultivation to support food safety and stall land degradation. In line with global studies this research suggest that cultivation of marginal terraced land is timely through a climate smart agriculture system as a holistic approach to improve land quality and serve as means to combat climate change impacts. The study also discusses land management and policy approaches to address the issue of agricultural land abandonment and the benefits gained through cultivation to the local community, economy and environment protection and sustainability.

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Climate Change Impacts and Adaptation in Rainfed Farming Systems: A Modeling Framework for Scaling-Out Climate Smart Agriculture in Sub-Saharan Africa

American Journal of Climate Change ◽

10.4236/ajcc.2015.44025 ◽

2015 ◽

Vol 04 (04) ◽

pp. 313-329 ◽

Cited By ~ 16

Author(s):

Berhanu F. Alemaw ◽

Timothy Simalenga

Keyword(s):

Climate Change ◽

Climate Change Impacts ◽

Farming Systems ◽

Sub Saharan Africa ◽

Modeling Framework ◽

Rainfed Farming ◽

Sub Saharan ◽

Smart Agriculture ◽

Scaling Out

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Toward climate-smart agriculture in West Africa: a review of climate change impacts, adaptation strategies and policy developments for the livestock, fishery and crop production sectors

Agriculture & Food Security ◽

10.1186/s40066-016-0075-3 ◽

2016 ◽

Vol 5 (1) ◽

Cited By ~ 40

Author(s):

Robert Zougmoré ◽

Samuel Partey ◽

Mathieu Ouédraogo ◽

Bamidele Omitoyin ◽

Timothy Thomas ◽

...

Keyword(s):

Climate Change ◽

West Africa ◽

Crop Production ◽

Climate Change Impacts ◽

Adaptation Strategies ◽

Smart Agriculture

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A Comparison of Approaches to Regional Land-Use Capability Analysis for Agricultural Land-Planning

Land ◽

10.3390/land10050458 ◽

2021 ◽

Vol 10 (5) ◽

pp. 458

Author(s):

Tara A. Ippolito ◽

Jeffrey E. Herrick ◽

Ekwe L. Dossa ◽

Maman Garba ◽

Mamadou Ouattara ◽

...

Keyword(s):

Land Use ◽

Land Use Planning ◽

Crop Production ◽

Agricultural Land ◽

Arable Land ◽

Agricultural Activity ◽

Field Samples ◽

Agricultural Potential ◽

Fertility Data ◽

Using Data

Smallholder agriculture is a major source of income and food for developing nations. With more frequent drought and increasing scarcity of arable land, more accurate land-use planning tools are needed to allocate land resources to support regional agricultural activity. To address this need, we created Land Capability Classification (LCC) system maps using data from two digital soil maps, which were compared with measurements from 1305 field sites in the Dosso region of Niger. Based on these, we developed 250 m gridded maps of LCC values across the region. Across the region, land is severely limited for agricultural use because of low available water-holding capacity (AWC) that limits dry season agricultural potential, especially without irrigation, and requires more frequent irrigation where supplemental water is available. If the AWC limitation is removed in the LCC algorithm (i.e., simulating the use of sufficient irrigation or a much higher and more evenly distributed rainfall), the dominant limitations become less severe and more spatially varied. Finally, we used additional soil fertility data from the field samples to illustrate the value of collecting contemporary data for dynamic soil properties that are critical for crop production, including soil organic carbon, phosphorus and nitrogen.

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Regional biogeographical model of vegetation zones in doctoral programme Regional Biography in Olomouc (Case study for Norway spruce)

(Teaching) Regional Geography. Proceedings of 27th Central European Conference. 17th October 2019, Brno ◽

10.5817/cz.muni.p210-9694-2020-11 ◽

2020 ◽

Author(s):

Ivo Machar ◽

Marián Halás ◽

Zdeněk Opršal

Keyword(s):

Climate Change ◽

Regional Climate ◽

Climate Change Impacts ◽

Climate Data ◽

Ecological Data ◽

The Czech Republic ◽

Climate Conditions ◽

Vegetation Zones ◽

Landscape Research

Regional climate changes impacts induce vegetation zones shift to higher altitudes in temperate landscape. This paper deals with applying of regional biogeography model of climate conditions for vegetation zones in Czechia to doctoral programme Regional Geography in Palacky University Olomouc. The model is based on general knowledge of landscape vegetation zonation. Climate data for model come from predicted validated climate database under RCP8.5 scenario since 2100. Ecological data are included in the Biogeography Register database (geobiocoenological data related to landscape for cadastral areas of the Czech Republic). Mathematical principles of modelling are based on set of software solutions with GIS. Students use the model in the frame of the course “Special Approaches to Landscape Research” not only for regional scenarios climate change impacts in landscape scale, but also for assessment of climate conditions for growing capability of agricultural crops or forest trees under climate change on regional level.

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Growing climatic sensitivity of U.S. agriculture linked to technological change and regional specialization

Science Advances ◽

10.1126/sciadv.aat4343 ◽

2018 ◽

Vol 4 (12) ◽

pp. eaat4343 ◽

Cited By ~ 23

Author(s):

Ariel Ortiz-Bobea ◽

Erwin Knippenberg ◽

Robert G. Chambers

Keyword(s):

Climate Change ◽

Crop Production ◽

Agricultural Sector ◽

State Level ◽

The United States ◽

Climate Data ◽

Specialty Crops ◽

Regional Specialization ◽

Vulnerability To Climate Change ◽

Climatic Sensitivity

A pressing question for climate change adaptation is whether ongoing transformations of the agricultural sector affect its ability to cope with climatic variations. We examine this question in the United States, where major increases in productivity have fueled most of agricultural production growth over the past half-century. To quantify the evolving climate sensitivity of the sector and identify its sources, we combine state-level measures of agricultural productivity with detailed climate data for 1960–2004. We find that agriculture is growing more sensitive to climate in Midwestern states for two distinct but compounding reasons: a rising climatic sensitivity of nonirrigated cereal and oilseed crops and a growing specialization in crop production. In contrast, other regions specialize in less climate-sensitive production such as irrigated specialty crops or livestock. Results suggest that reducing vulnerability to climate change should consider the role of policies in inducing regional specialization.

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Future humidity extremes in an urban-rural context - using regional climate model projections down to convection permitting scales for Berlin

10.5194/egusphere-egu21-12054 ◽

2021 ◽

Author(s):

Gaby S. Langendijk ◽

Diana Rechid ◽

Daniela Jacob

Keyword(s):

Climate Change ◽

Urban Areas ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Climate Change Impacts ◽

Regional Climate Models ◽

Climate Projections ◽

Climate Data ◽

Urban Rural

<p>Urban areas are prone to climate change impacts. A transition towards sustainable and climate-resilient urban areas is relying heavily on useful, evidence-based climate information on urban scales. However, current climate data and information produced by urban or climate models are either not scale compliant for cities, or do not cover essential parameters and/or urban-rural interactions under climate change conditions. Furthermore, although e.g. the urban heat island may be better understood, other phenomena, such as moisture change, are little researched. Our research shows the potential of regional climate models, within the EURO-CORDEX framework, to provide climate projections and information on urban scales for 11km and 3km grid size. The city of Berlin is taken as a case-study. The results on the 11km spatial scale show that the regional climate models simulate a distinct difference between Berlin and its surroundings for temperature and humidity related variables. There is an increase in urban dry island conditions in Berlin towards the end of the 21st century. To gain a more detailed understanding of climate change impacts, extreme weather conditions were investigated under a 2&#176;C global warming and further downscaled to the 3km scale. This enables the exploration of differences of the meteorological processes between the 11km and 3km scales, and the implications for urban areas and its surroundings. The overall study shows the potential of regional climate models to provide climate change information on urban scales.</p>

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Performance evaluation of global hydrological models in six large Pan-Arctic watersheds

Climatic Change ◽

10.1007/s10584-020-02892-2 ◽

2020 ◽

Vol 163 (3) ◽

pp. 1329-1351 ◽

Cited By ~ 1

Author(s):

Anne Gädeke ◽

Valentina Krysanova ◽

Aashutosh Aryal ◽

Jinfeng Chang ◽

Manolis Grillakis ◽

...

Keyword(s):

Climate Change ◽

Performance Evaluation ◽

Land Surface ◽

Snow Water Equivalent ◽

Explanatory Power ◽

Model Performance ◽

Climate Change Impacts ◽

Hydrological Processes ◽

Climate Data ◽

Seasonal Discharge

AbstractGlobal Water Models (GWMs), which include Global Hydrological, Land Surface, and Dynamic Global Vegetation Models, present valuable tools for quantifying climate change impacts on hydrological processes in the data scarce high latitudes. Here we performed a systematic model performance evaluation in six major Pan-Arctic watersheds for different hydrological indicators (monthly and seasonal discharge, extremes, trends (or lack of), and snow water equivalent (SWE)) via a novel Aggregated Performance Index (API) that is based on commonly used statistical evaluation metrics. The machine learning Boruta feature selection algorithm was used to evaluate the explanatory power of the API attributes. Our results show that the majority of the nine GWMs included in the study exhibit considerable difficulties in realistically representing Pan-Arctic hydrological processes. Average APIdischarge (monthly and seasonal discharge) over nine GWMs is > 50% only in the Kolyma basin (55%), as low as 30% in the Yukon basin and averaged over all watersheds APIdischarge is 43%. WATERGAP2 and MATSIRO present the highest (APIdischarge > 55%) while ORCHIDEE and JULES-W1 the lowest (APIdischarge ≤ 25%) performing GWMs over all watersheds. For the high and low flows, average APIextreme is 35% and 26%, respectively, and over six GWMs APISWE is 57%. The Boruta algorithm suggests that using different observation-based climate data sets does not influence the total score of the APIs in all watersheds. Ultimately, only satisfactory to good performing GWMs that effectively represent cold-region hydrological processes (including snow-related processes, permafrost) should be included in multi-model climate change impact assessments in Pan-Arctic watersheds.

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Consequences of Climate Change Impacts and Incidences of Extreme Weather Events in Relation to Crop Production in Bhutan

Sustainability ◽

10.3390/su12104319 ◽

2020 ◽

Vol 12 (10) ◽

pp. 4319 ◽

Cited By ~ 1

Author(s):

Ngawang Chhogyel ◽

Lalit Kumar ◽

Yadunath Bajgai

Keyword(s):

Climate Change ◽

Crop Production ◽

Climatic Factors ◽

Climate Change Impacts ◽

Extreme Weather ◽

Crop Damage ◽

Extreme Weather Events ◽

Cropping Pattern ◽

The People ◽

Weather Events

Being a country in the Himalayas, Bhutan is highly prone to the vagaries of weather events that affect agricultural production and the subsequent livelihood of the people. To identify the main issues that affect crop production and the decisions of farmers, a survey was conducted in three different agro-ecosystems in Bhutan. Our key findings indicate that farming and the decisions of farmers were largely affected by different climatic and non-climatic factors. These were in descending order of importance: irrigation availability > farm labour > crop seasonality > crop damage (climatic) > land holding > crop damage (wildlife) > crop damage (diseases and pests). The most important consequences of climate change impacts were the drying of irrigation sources (4.35) and crop losses due to weather events (4.10), whereas land fallowing, the occurrence of flood and soil erosion, weed pressure and changes in cropping pattern (with mean ratings of 2.53–3.03) experienced lesser consequences. The extreme weather events, such as untimely rains, drought and windstorms, were rated as the ‘most common’ to ‘common’ occurrences, thus inflicting a crop loss of 1–19%. These confirm our hearsay knowledge that extreme weather events have major consequences on irrigation water, which is said to be either drying or getting smaller in comparison to the past. Therefore, Bhutan must step up its on-ground farmer-support system towards improving the country’s food production, whilst embracing climate smart farm technologies for adapting to the impacts of change.

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Impact of Climate Change on Crops Adaptation and Strategies to Tackle Its Outcome: A Review

Plants ◽

10.3390/plants8020034 ◽

2019 ◽

Vol 8 (2) ◽

pp. 34 ◽

Cited By ~ 91

Author(s):

Ali Raza ◽

Ali Razzaq ◽

Sundas Mehmood ◽

Xiling Zou ◽

Xuekun Zhang ◽

...

Keyword(s):

Climate Change ◽

Food Security ◽

Crop Production ◽

Climate Changes ◽

Heat Waves ◽

Negative Impact ◽

Global Climate ◽

Climate Change Impacts ◽

Annual Rainfall ◽

Ozone Level

Agriculture and climate change are internally correlated with each other in various aspects, as climate change is the main cause of biotic and abiotic stresses, which have adverse effects on the agriculture of a region. The land and its agriculture are being affected by climate changes in different ways, e.g., variations in annual rainfall, average temperature, heat waves, modifications in weeds, pests or microbes, global change of atmospheric CO2 or ozone level, and fluctuations in sea level. The threat of varying global climate has greatly driven the attention of scientists, as these variations are imparting negative impact on global crop production and compromising food security worldwide. According to some predicted reports, agriculture is considered the most endangered activity adversely affected by climate changes. To date, food security and ecosystem resilience are the most concerning subjects worldwide. Climate-smart agriculture is the only way to lower the negative impact of climate variations on crop adaptation, before it might affect global crop production drastically. In this review paper, we summarize the causes of climate change, stresses produced due to climate change, impacts on crops, modern breeding technologies, and biotechnological strategies to cope with climate change, in order to develop climate resilient crops. Revolutions in genetic engineering techniques can also aid in overcoming food security issues against extreme environmental conditions, by producing transgenic plants.

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