Land Degradation Neutrality Research Articles

Multiscale analysis framework for assessing land degradation neutrality with ecosystem services: A case study of the Yellow River basin

As a component of sustainable development goals, Land Degradation Neutrality (LDN) is an overarching tool to curb global land degradation. Since LDN requires realization at a specific spatiotemporal scale, how to bridge the pixel-scale degraded area and the regional-scale LDN unrealized area needs further study. Thus, a multiscale analysis framework for LDN was constructed, with the Yellow River Basin (YRB) in China as a case study and 2000–2020 as the study period. Concretely, the land types were divided into land for ecosystem function and services (LEFS) and land for food security (LFS) by combining the concepts and the “like for like” principle. Then, an attempt was made to replace or supplement the original LDN indicators with some of the ecosystem service indicators, which were then divided into dominant and recessive indicators. Finally, the LDN assessment was conducted at “basin-provincial-city-county” multiscale and at pixel scale following the “one out-all out” principle. The following results were obtained: (1) at the pixel scale, the improved areas of both LEFS and LFS were greater than the degraded areas. However, the degraded LEFS remained severe in sporadic areas, while the degraded LFS was mostly concentrated around the built-up areas of large cities. (2) At the regional scale, positive outcomes in LEFS conservation were achieved in the YRB in the last 20a. However, LDN remained unachieved on the watershed scale due to insufficient efforts toward LFS. Besides, very few districts achieved LDN on the “provincial-city-county” scale. (3) The LDN should be integrated into land-use planning to establish a progressive system at the multiscale level, which could articulate between physical geography and administrative districts. Furthermore, differentiated protection and rehabilitation solutions were applied to LEFS and LFS, following the “Avoid > Reduce > Reverse” principle. (4) The degradation of the LEFS and LFS caused by large-scale construction was almost inevitable during the extensive economic growth phase. Therefore, future promotion of LDN ought to follow the “common but differentiated principle” and consider differentiated base times tailored to economic development levels. Overall, this study provided a new tool for LDN assessment efficiently and conveniently, thus making a marginal contribution to global action for curbing land degradation.

Land cover degradation in the reference and monitoring periods of the SDG Land Degradation Neutrality Indicator for Switzerland

Land degradation impacts most terrestrial biomes across all world regions. To address global change challenges emanating from degrading natural resources, many countries voluntarily set themselves the goal of achieving Land Degradation Neutrality (LDN). Baseline conditions are to be established over a reference period (2000 – 2015). With seven more years to monitor this Sustainable Development Goal 15 indicator — SDG15.3.1 until the year 2030, the scientific basis for operationalizing LDN is still evolving. The non-availability of annual land use-land cover maps of sufficient resolution in various countries, among them Switzerland, is a major factor hampering the assessment at national and local levels. Land cover change is assessed for seven land categories (that is, Tree-covered area, Grassland, Cropland, Wetland, Artificial Surfaces, Otherland, and Waterbody). Land cover change is a major LDN sub-indicator required to assess the proportion of degraded land to total land area (SDG15.3.1). Annual land cover datasets from 2015 to 2020 were produced at 10 m from Sentinel-1 and Sentinel-2 images using a Remote Sensing and Geographic Information System-based workflow. An evaluation of degradation in land cover is presented in support of the operationalization of LDN in Switzerland. Drawing upon the understanding that changes made to land use-land cover may act as precursors to land degradation processes, transitions relating to the loss of natural cover were identified based on the land cover change criteria during the reference and the monitored periods. The criteria were developed for relating land cover transitions to degrading and non-degrading processes. Such transitions were grasslands to tree-covered areas and croplands to artificial surfaces due to settlement development. For example, the amount of cropland converted to artificial surface areas was greater in absolute terms during the monitored period than during the reference period. Also, the regeneration of natural cover involving transitions from otherland to grassland and from grasslands to tree-covered areas was found. Overall trends between 2000 and 2020 in Switzerland are the increasing settlement areas in the Central Plateau, the Alpine valleys of Valais and Ticino, largely at the expense of croplands and the bush encroachment of pastures such as in the Jura. This study’s contributions include an enhanced workflow for annual land cover mapping for the entire Switzerland and the adaptation of the land cover change criteria to fit the Swiss context. The proposed mapping method has the potential to fill the gap between the production cycles of the Swiss Corine and Arealstatistik land use data.

Restoring soil quality and carbon sequestration potential of waterlogged saline land using subsurface drainage technology to achieve land degradation neutrality in India

Subsurface drainage (SSD) has been proved to be an effective technology to reclaim waterlogged saline soils. Three SSD projects were implemented in Haryana, India in 2009, 2012 and 2016 to study the long term effect of SSD (10, 7 and 3 years) operation on restoring productivity and carbon sequestration potential of degraded waterlogged saline soils under prevalent rice-wheat cropping system. These studies indicated that successful operation of SSD improved soil quality parameters such as bulk density, BD (from 1.58 to 1.52 Mg m−3), saturated hydraulic conductivity, SHC (from 3.19 to 5.07 cm day−1); electrical conductivity, ECe (from 9.72 to 2.18 dS m−1), soil organic carbon, OC (from 0.22 to 0.34 %), dehydrogenase activity, DHA (from 15.44 to 31.65 μg g−1 24 h−1), and alkaline phosphatase, ALPA (from 16.66 to 40.11 μg P-NP g−1 h−1) in upper soil surface (0–30 cm). The improved soil quality resulted in increased rice-wheat system yield (rice equivalent yield) by 328 %, 465 % and 665 % at Kahni, Siwana Mal and Jagsi sites, respectively. Studies also revealed that carbon sequestration potential of degraded land increased with the implementation of SSD projects. The principal component analysis (PCA) showed that % OC, ECe, ALPA, available N and K content were the most contributing factor for soil quality index (SQI). The overall result of the studies showed that SSD technology holds great potential to improve soil quality, increase crop productivity, farmers' income and ensure land degradation neutrality and food security in waterlogged saline areas of western Indo Gangetic Plain of India. Hence, it can be concluded that large scale adoption of SSD may fulfill the promise “No poverty, Zero hunger, and Life on land” sustainable development goals of United Nation in degraded waterlogged saline areas.

Improving satellite-based global rainfall erosivity estimates through merging with gauge data

Rainfall erosivity is a key factor that influences soil erosion by water. Rain-gauge measurements are commonly used to estimate rainfall erosivity. However, long-term gauge records with sub-hourly resolutions are lacking in large parts of the world. Satellite observations provide spatially continuous estimates of rainfall, but they are subject to biases that affect estimates of rainfall erosivity. We employed a novel approach to map global rainfall erosivity based on a high-temporal-resolution (30-min), long-term (2001–2020) satellite-based precipitation product—the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM-IMERG)—and mean annual rainfall erosivity from the Global Rainfall Erosivity Database (GloREDa) stations (n = 3286). We used a residual-based merging scheme to integrate GPM-IMERG-based rainfall erosivity with GloREDa using Geographically Weighted Regression (GWR). The accuracy of the GWR-based merging scheme was evaluated with a 10-fold cross-validation against GloREDa stations. Based on GPM-IMERG-only, the global mean annual rainfall erosivity was estimated to be 1173 MJ mm ha−1 h−1 yr−1 with a standard deviation of 1736 MJ mm ha−1 h−1 yr−1. The mean value estimated via GPM-IMERG merged with GloREDa was 2020 MJ mm ha−1 h−1 yr−1 with a standard deviation of 3415 MJ mm ha−1 h−1 yr−1. Overall, GPM-IMERG-only estimates underestimated rainfall erosivity. The underestimations were greatest in areas of high rainfall erosivity. The accuracy of rainfall erosivity estimates from GPM-IMERG merged with GloREDa substantially improved (Nash-Sutcliffe efficiency = 0.83, percent bias = −2.4%, and root mean square error = 1122 MJ mm ha−1 h−1 yr−1) compared to estimates by GPM-IMERG-only (Nash-Sutcliffe efficiency = 0.51, percent bias = 27.8%, and root mean square error = 1730 MJ mm ha−1 h−1 yr−1). Improving satellite-based global rainfall erosivity estimates through integrating with gauge data is relevant as it can contribute to enhancing soil erosion modeling and, in turn, support land degradation neutrality programs.

The Role of Sustainable Forest Management in Achieving Land Degradation Neutrality Target

The rapidly increasing human population and the needs rise the threats to the future of the world. In order to avoid this situation, all countries come together under the umbrella of the United Nations (UN) and seek common solutions to this issue. One of these solutions is Land Degradation Neutrality (LDN), which was founded under the aim of the “Life on Land” number 15 of the Sustainable Development Goals (SDGs) and was embodied in UNCCD COP 12 in 2015. So much so that the LDN, by looking at the environmental problems experienced in a high dimension, adopted firstly the prevention of land degradation, then its reduction and the recovery of lost lands. At this point, Sustainable Forest Management (SFM) is of great importance. This study has been prepared to indicate the importance of the SFM to reaching the LDN target.

Managing rain-fed uplands of cascaded tank village systems: What stakeholders really suggest?

CONTEXTAchieving land degradation neutrality through sustainable land management requires stakeholder collaboration. Understanding of stakeholders' worldviews facilitates fostering stakeholder collaboration. Reported lack of stakeholder collaboration in CTVS-related conservation and development programs may be due to stakeholders' competing worldviews and marginalizing primary stakeholders' viewpoints. OBJECTIVEThis study systematically investigates stakeholders' worldviews on sustainable management of the rain-fed uplands of CTVS. METHODSThe Q-Methodology was used with a Q set of 54 land management activities. Twenty-seven respondents with different expertise were given a forced-choice distribution grid (Q-sorts): an 11-point scale (ranging from −5 = least important I think to +5 most important I think) to rank the Q-Set. Using the principal component analysis with varimax rotation in Ken-Q Analysis Desktop Edition Q sorts were analyzed. RESULTS AND CONCLUSIONSStakeholders' worldviews towards sustainable rain-fed uplands are four-fold (extension-driven approaches, community-driven approaches, solution-based approaches and punitive control approaches), based on power and facilitation and irrespective of their social backgrounds. Many worldviews do not compete and can facilitate stakeholder collaboration, whereas the worldview that relies on coercion to achieve conservation behavior may be a potential bottleneck for stakeholder reconciliation. SIGNIFICANCEThis study has demonstrated how useful it is to utilize a systematic investigation to understand stakeholders' worldviews towards conservation solutions. As a result, it facilitates exploring challenges and opportunities by policymakers to facilitate cooperation between stakeholders while avoiding bottlenecks to achieve sustainable management of rain-fed uplands in CTVS.

Towards Land Consumption Neutrality and Natural Capital Enhancement at Urban Landscape Scale

Among the UNCCD SDGs 2030, there is the recognition that land consumption can strongly affect the provision of ecosystem services. From the perspective of land degradation neutrality, urban level is the right scale when planning actions against land consumption. The aims of this research are: (1) to assess land consumption at urban landscape scale and its effects on natural capital flow provision; and (2) to identify sustainable strategic planning choices for land consumption mitigation and natural capital enhancement. We propose and test an approach based on multi-temporal landscape spatial analysis (land use/land cover map, land consumption map, and landscape metrics) and ecosystem services’ flow assessment for the identification of areas at risk of loss of natural capital flow. The results have shown that from 2006 to 2019, land consumption has increased with a consequent decrease of natural capital flow. LULC dynamics has been analyzed in terms of landscape risk to lose natural capital flow, highlighting that the management of Galatone urban landscape is still far from land consumption neutrality. Landscape metrics have allowed the analysis of the aggregation among land consumption areas. The mitigation of land consumption should be based on the identification of suitable nature-based solutions towards the balance between past land consumption and future land recovery.

Evaluation of future wetland changes under optimal scenarios and land degradation neutrality analysis in the Guangdong-Hong Kong-Macao Greater Bay Area

Wetlands are one of the most productive ecosystems on Earth and are also focused on by the Sustainable Development Goals (SDGs). However, global wetlands have suffered from considerable degradation due to rapid urbanization and climate change. To support wetland protection and SDG reporting, we predicted future wetland changes and assessed land degradation neutrality (LDN) from 2020 to 2035 under four scenarios in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). A simulation model combining random forest (RF), CLUE-S and multi-objective programming (MOP) methods was developed to predict wetland patterns under the natural increase scenario (NIS), economic development scenario (EDS), ecological protection and restoration scenario (ERPS) and harmonious development scenario (HDS). The simulation results indicated that the integration of RF and CLUE-S achieved good simulation accuracy, with OA over 0.86 and kappa indices over 0.79. From 2020 to 2035, the mangrove, tidal flat and agricultural pond increased while the coastal shallow water decreased under all scenarios. The river decreased under NIS and EDS, while increased under ERPS and HDS. The Reservoir decreased under NIS, while increased under the remaining scenarios. Among scenarios, the EDS had the largest built-up land and agricultural pond, and the ERPS had the largest forest and grassland. The HDS was a coordinated scenario that balanced economic development and ecological protection. Its natural wetlands were almost equal to these of ERPS, and its built-up land and cropland were almost equal to these of EDS. Then, the land degradation and SDG 15.3.1 indicators were calculated to support the LDN target. From 2020 to 2035, the ERPS had a smallest gap of 705.51 km2 from the LDN target, following the HDS, EDS and NIS. The SDG 15.3.1 indicator was lowest under the ERPS, with a value of 0.85 %. Our study could offer strong support for urban sustainable development and SDGs reporting.

Quantifying the Unvoiced Carbon Pools of the Nilgiri Hill Region in the Western Ghats Global Biodiversity Hotspot—First Report

Accelerating land-use change (LUC) in the Nilgiri Hill Region (NHR) has caused its land to mortify. Although this deterioration has been documented, the destruction of buried gem soil has not been reported. Therefore, this study was conducted to assess the impact of LUC on soil-carbon dynamics in the six major ecosystems in the NHR: croplands (CLs), deciduous forests (DFs), evergreen forests (EFs), forest plantations (FPs), scrublands (SLs), and tea plantations (TPs). Sampling was conducted at selected sites of each ecosystem at three depth classes (0–15, 15–30, and 30–45 cm) to quantify the carbon pools (water-soluble carbon, water-soluble carbohydrates, microbial biomass carbon, microbial biomass nitrogen, dehydrogenase, and different fractions of particulate organic carbon). We found that the LUC significantly decreased the concentration of carbon in the altered ecosystems (49.44–78.38%), with the highest being recorded at EF (10.25%) and DF (7.15%). In addition, the effects of the LUC on the aggregate size of the organic carbon were dissimilar across all the aggregate sizes. The relatively high inputs of the aboveground plant residues and the richer fine-root biomass were accountable for the higher concentration of carbon pools in the untouched EFs and DFs compared to the SLs, FPs, TPs, and CLs. The results of the land-degradation Index (LDI) depicted the higher vulnerability of TP (−72.67) and CL (−79.00). Thus, our findings highlight the global importance of LUC to soil quality. Henceforth, the conservation of carbon pools in fragile ecosystems, such as the NHR, is crucial to keep soils alive and achieve land-degradation neutrality.

Assessment of changes in water conservation capacity under land degradation neutrality effects in a typical watershed of Yellow River Basin, China

Large-scale implementation of the Grain for Green Project since 1999, which took the Yellow River Basin (YRB) as the core ecological restoration area, has had an important impact on the hydrological processes and ecological environment. Whether such forest restoration construction is conducive to achieving land degradation neutrality as well as improving water conservation capacity has become a hot research topic. The Yiluo River basin (YLRB), one of the most important water conservation areas in the YRB, was selected as the study area. Firstly, the transfer matrix was used to analyze the changes in the two land use maps in 1990 and 2015 and to determine the transformation relationship between different land use types. Furthermore, land degradation was also investigated for further exploration of the correlation between land degradation neutrality and water conservation. The effects of land use and cover changes (LUCC) on the water conservation capacity across the YLRB were investigated by combining the Soil and Water Assessment Tool (SWAT) model, water conservation assessment method and land use change scenarios method. The results showed that the land degradation area was mainly located in the residential area and agricultural land in the downstream of the YLRB, and the execution of the Grain for Green Project is beneficial in promoting land degradation neutrality and increasing the water conservation capacity. The water conservation capacity across the YLRB approximately increased by 19.30 mm yr−1 as every 10% of agricultural land converted to forest, showing a greater increase in the upstream than that in the downstream. Rainfall, Normalized Difference Vegetation Index (NDVI), and temperature were the primary factors affecting water conservation in the YLRB, while geological lithology also affects the spatial distribution of water conservation. The findings of this study could provide a theoretical basis for water resources and ecological environment protection.

Assessment of Land Degradation at the Local Level in Response to SDG 15.3: A Case Study of the Inner Mongolia Region from 2000 to 2020

SDG15.3 aims to achieve “Land Degradation Neutrality (LDN)”, but its only indicator (SDG15.3.1) is designed for national-level assessment and monitoring, and is not suitable for local-level applications. Thus, taking Inner Mongolia as the study area, this paper provides a localized reform of SDG15.3.1 based on the local context, and assesses the progress of SDG15.3 in the study area (2000-2020) at multiple levels (indicator, specific, and overall). The Moran’I and Standard Deviation Ellipse (SDE) are also utilized to analyze the spatial–temporal change of land degradation. The results show that as of 2020, the proportion of land degradation and improvement areas to the total area was 7.51% and 9.42%, respectively. Inner Mongolia had generally met the goal of SDG15.3, but on the indicator level, water erosion still falls far below the standard of SDG15.3. Additionally, at the spatial level, 3 out of 12 municipalities and 71 out of 103 counties had not achieved LDN, with a pattern of low LDN levels in the southeast and high in the northwest at the county scale. This indicates that the progress of SDG15.3 is extremely uneven both at the indicator and spatial levels. Thus, it is essential to continue to promote land degradation management in Inner Mongolia to achieve LDN in the entire area and across all aspects.

Agricultural innovation to increase climate change resilience in Tapin Regency

Agriculture is one of top best-selling non-oil-and-gas products. However, environmental-related purposes for production, based on the Regulation of Forestry Ministry of Republic of Indonesia No P50/Menhut-II/2010 for the Right to Exploit, not meet the Ecosystem Reforestation Rights. Land degradation means loss of the productive capacity of the soils that has huge risk to food insecurity, loss of ecosystem biodiversity and climate change. In Tapin, one of the most productive agriculture in South Kalimantan Province, dramatic decline in the productivity of croplands can be one of the most important contributors of climate change. The action of Land Degradation Neutrality (LDN) by adapting innovation has been a solution of reducing vulnerability and increase climate change resilience to combat rising demands for agriculture product and the agricultural production system. Smallholder farmers and rural community need to intensify the production of food for sustainable agriculture and food security, as mentioned in Sustainable Develompent Goals (SDGs) Goals 15.

Assessment of the Dynamics of Land Cover at the Local Level to achieve Land Degradation Neutrality (for Desertified Lands of the Dry-Steppe Zavolzh’e)

Assessment of the Dynamics of Land Cover at the Local Level to achieve Land Degradation Neutrality (for Desertified Lands of the Dry-Steppe Zavolzh’e)

Assessing and Monitoring Sustainable Land Management for Land Degradation Neutrality in Wadi El Farigh

Assessing and Monitoring Sustainable Land Management for Land Degradation Neutrality in Wadi El Farigh

Social–Ecological System Understanding of Land Degradation in Response to Land Use and Cover Changes in the Greater Sekhukhune District Municipality

Land degradation is a major risk to the sustainability and functioning of socioecological systems (SES), especially in arid/semiarid regions. By understanding a system and its interlinkages, the socioecological approach offers an innovative way to explore degradation. This is achieved through a synergistic analytical approach to improve the ability of identifying and understanding systems, predicting their behaviour, and modifying them to achieve the desired effects. This research provides a roadmap for an integrated interdisciplinary approach that is a critical factor in understanding the drivers of land degradation. It can be used to determine appropriate land management action. The aim of this study was, therefore, to apply an integrated SES approach to a degraded rural semiarid context to address the land degradation problem using the Greater Sekhukhune District Municipality in South Africa as a case study. The Drive Pressure State Condition and four Responses (DPSCR4) framework (modified from Drive Pressure State Impact and Response (DPSIR)) was used as the SES to assess land degradation. Key informant interviews, focus group discussions with local pastoralists and traditional authorities, and the scientific literature were triangulated to systemically analyse DPSCR4. Land degradation neutrality (LDN) was integrated into the framework to draw conclusions on sustainable land management (SLM). The results show that the main anthropogenic activities driving land degradation are overgrazing, land tenure, poverty and disenfranchisement, unsustainable land use, and cropland abandonment, which favour bush encroachment. Natural factors such as topography, dispersive duplex soils, and climate variability and change predispose the district to soil erosion and gully formation. In combination with human activities, this exacerbates land degradation. The study recommends measures to enable informed integrated land use planning and management using the DPSCR4 and LDN frameworks to improve landscape conditions in rural semiarid regions and provide sustainable livelihoods for the rural poor in developing countries who depend on natural resources.

SOC-reactivity analysis for a newly defined class of two-dimensional soil organic carbon dynamics

To evaluate changes in the Soil Organic Carbon (SOC) index, one of the key indicators of land degradation neutrality, soil carbon modeling is of primary importance. In literature, the analysis has been focused on the stability characterization of soil carbon steady states and in the calculation of the resilience of the stable equilibria. Neither stability nor resilience, however, provide any information about transient dynamics, and models with highly resilient equilibria can exhibit dramatic transient responses to perturbations. To trace how environmental changes affect the transient dynamics of SOC indicator, we use the concept of generalized reactivity (g-reactivity) to models belonging to two main classes: the first-order, linear and semilinear carbon transfer models and fully nonlinear microbe-explicit models. A novel formulation of a general two-dimensional model allows to deal with different functional forms and to perform a systematic analysis of both stability of soil carbon equilibria and SOC-reactivity. Using temperatures and Net Primary Production (NPP) data of Alta Murgia National Park, the RothC, MOMOS and the fully implicit dynamical planar system are compared in predicting the impact of increased temperatures in the years 2005–2019 on the asymptotic stability of carbon steady states and in increasing the SOC-reactivity.

Assessment of land degradation in Inner Mongolia between 2000 and 2020 based on remote sensing data

Achieving land degradation neutrality (LDN) worldwide is a significant target of the Sustainable Development Goal (SDG15.3). Inner Mongolia, as a typical dryland region in northern China, has carried out several large-scale ecological restoration programs to combat land degradation. However, there is a lack of comprehensive assessment of its land degradation situation after ecological programs implementation, which is of great significance to supporting SDG15.3 in China. This study analyzed the land degradation situation using the improved SDG15.3.1 calculation framework based on fine resolution data in Inner Mongolia from 2000 to 2020, and finally comprehensively evaluated the land status of the whole region and those subject to ecological programs. The results show that net land restoration proportion of various ecological project regions and whole region continues to increase. The scope of the Grain for Green Program (GGP) had the largest proportion of net land restoration while the Natural Reserve Program (NRP) had the lowest proportion from 2000 to 2020. The net land restoration area of Inner Mongolia during 2000–2010 and 2010–2020 was 35,800 km² and 65,300 km², respectively. Overall, Inner Mongolia has achieved statistically zero growth in land degradation under the governance of ecological restoration programs. Therefore, reasonable planning, well monitoring, and timely assessment of ecological restoration programs are crucial to support SDG15.3.

Improved mapping and understanding of land system states for achieving land degradation neutrality using remote sensing surface endmembers—temperature space: A case‐study in Minqin, China

AbstractThe identification and understanding of land system states are critical for achieving land degradation neutrality (LDN). However, present conventional approaches can hardly generate a state space with both complex linear and abrupt shift relationships. Therefore, with the remote sensing surface endmembers—temperature space, this study developed a framework to identify, map and understand land system states and their associated trajectories based on the alternative state theory. Combined with three variables of land cover and landscape, our proposed vegetation productivity index (VPI) can highly improve the mapping accuracy of land system states in Minqin, without considering the variable of soil type. We built the three‐dimensional state catastrophe space with variables of soil organic matter (SOM), VPI, and cover function index (LCI). Thanks to the ball‐and‐cup model, two alternative stable states and five unstable states were identified at the landscape level in Minqin; then, we further explored the desired threshold of VPI and LCI were 13.11 and 0.39, while their undesired threshold were 5.15 and 0.76, respectively. The state space can reveal the linear or non‐linear relationship between VPI/LCI and SOM; besides, it can also present the hysteresis of land system state. Moreover, our established model in 2015 proved to be stable and thus can be used to accurately estimate the states in 2018. Therefore, our proposed framework can be an effective way of mapping and understanding present and future land system states, which can provide useful information on proactive conservation and restorative interventions for LDN management.

Implementing climate change projections in System Dynamics models

Desertification is the degradation of drylands, which occupy an increasing proportion of the Earth's surface due to global warming. It is currently the most extensive biome on Earth, occupying 45% and one out of every three inhabitants of the planet live in them. One of the most effective ways to face desertification, as Land Degradation Neutrality points out, is prevention. For this purpose, simulation models are very useful tools. Specifically, System Dynamics models are particularly effective, since they allow bringing together the biophysical and socioeconomic variables involved in the formation of the problem. These integrative models, coupled with other tools such as sensitivity analyses, are used to generate desertification early warning indicators. The objective of this programming routine is to implement climate change scenarios in these simulation models. The script presented here was used to evaluate the sensitivity of dehesa rangelands productivity to the increase in the frequency and intensity of droughts due to climate change.•Integrated simulation models are useful tools to understand complex socioecosystems.•Land-use changes foster the alteration of key hydro-bio-geochemical processes.•By means of automated import processes and data analysis programming, it is possible to implement desertification early warning systems.

DYNAMICS OF LAND PRODUCTIVITY IN TERMS OF NET PRIMARY PRODUCTION AS SUB-INDICATOR FOR LAND RESTORATION IN ETHIOPIA: IMPLICATION FOR IMPLEMENTATION OF SUSTAINABLE DEVELOPMENT GOAL-15

Land productivity is described as biological productive capacity of a land used as source of food, fiber and fuel to sustain human needs. Land degradation is one of global challenges of our time resulting to food insecurity and migration of people due to lack of inappropriate land use plan and management practices. Sustainable forest land scape restoration interventions can improve land productivity in meeting for Sustainable Development Goal-15. Study was conducted to analyze dynamics of land productivity in terms of net primary production on six land use and cover class from 2001-2015 using secondary information from Global Earth Trend Observation under Praise-3 portal of UNCCD. Ethiopia has total land mass of 1,119,715.5 km2. The dynamics of land productivity net primary production on six different land use and land cover class were analyzed from baseline year 2000 to target year 2015. The analyses of land productivity change from 2000-2015 showed that a land mass 204,462.9 km2 accounting 18.26% was improved, while, 328,213 km2 accounting 29.31% was degraded and land mass of 555,726.8 km2 accounting 49.63% was remained stable. Result indicated that specifically tree-covered area exhibited the highest productive land by 85,126.99km2, while the least land improvement was exhibited on artificial land by 95.40 km2. Similarly, grass land exhibited the highest stable land by 97,547.88 km2, while the least was exhibited on water bodies by 184.90km2. On the other hand, grass land exhibited the highest stressed land by 97,547.88 km2, while the least was exhibited by water body 184.90km2. Grass land exhibited the highest declined land by 37,936.88 km2, while the least was exhibited on artificial land by 98.88km2. Even though; Ethiopia has made progressive land restoration intervention through sustainable forest/land management, the proportion of improved land is 18.26% which is much lower than the area proportionally degraded by 29.31%. There was fast trend of urbanization in rural area with drastic population growth where large area is being under pressure due to degradation which implies more efforts is needed in reversing land degradation and increase the productivity for increasing the biological and economic return from land. Therefore; additional sustainable forest management strategies and programs are needed to be put in place to bring more land under improved in productivity in line with meeting the national land degradation neutrality targets of Ethiopia by 2030; that ultimately reverse land degradation and combat desertification.