Equity in ecosystem restoration

The importance of equity has been emphasized in climate change, biodiversity loss, land degradation, and ecosystem restoration. However, equity implications are rarely considered explicitly in restoration projects. Although the role of equity has been studied in the context of biodiversity conservation and environmental governance, environmental variables are often ignored in equity studies, and spatial analyses of equity are lacking. To address these gaps, we use a mixed methods approach, integrating spatially explicit ecological and social data to evaluate, through an equity lens, a restoration project in a semi-arid rangeland socioecological system in Kenya. We use questionnaires and semi-structured key informant interviews to explore four dimensions of equity: distributional, procedural, recognitional, and contextual. Our results show that restoration employment and distance to the restoration site strongly influence perceived distributional and procedural equity. Employment and distance to restoration site can interact in counterintuitive ways in their influence on aspects of perceived equity, in this case, the fairness of site selection. Our findings exemplify that equity dimensions are intimately linked, and trade-offs can occur between equity dimensions, across socio-temporal scales, and in choosing the ethical framework to apply. Our work demonstrates how restoration is influenced by different dimensions of equity and we opine that incorporating equity in project planning and implementation processes can improve restoration outcomes. We emphasize the importance of respecting plurality in the values systems and ethical frameworks that underlie what is considered equitable, while negotiating trade-offs between diverse ethical positions in the design and implementation of ecosystem restoration projects

Restoring Rangelands for Nutrition and Health for Humans and Livestock

Drylands cover 40% of the global land area and host 2 billion people, of which 90% live in low- or middleincome countries. Drylands often face severe land degradation, low agricultural productivity, rapid population growth, widespread poverty, and poor health. Governance structures and institutions are often eroded. Livestock-based livelihoods, largely depending on seasonal migration are common. Pastoralist communities and their land are highly vulnerable to climate shocks, while there are also changes in land tenure, insecurity/conflicts and rapid infrastructure development. Drylands Transform is an interdisciplinary research project revolving around the UN Sustainable Development Goals (SDGs). The project aim is to contribute new knowledge to a transformative change and sustainable development of drylands in East Africa to help escape the ongoing negative spiral of land, livestock and livelihood degradation. We investigate the links between land health, livelihoods, human well-being, and land management and governance with several study sites along the Kenya-Uganda border. Through strong stakeholder engagement we will explore challenges and pathways towards a social-ecological transformation in these drylands. The entry point is the urgent need to identify and enhance synergies between food and nutrition security (SDG2), land and ecosystem health (SDG15) and governance and justice (SDG16) for sustainable dryland development, aiming to improve health and equity (SDGs 3 and 5), while minimizing trade-offs between agricultural productivity, natural resources management and climate change. We are using innovative field research approaches focusing on livelihood improvement through rangeland (grazing areas) restoration and governance interventions. We will present results from the initial work to assess land health using the Land Degradation Surveillance Framework and explore the links with human health and well-being through household survey data. We will also show how we will co-develop sustainable dryland management options (e.g., field experiments with fodder grasses and shrubs) with local communities and set-up knowledge sharing hubs

Spatio-temporal land use/cover dynamics and its implication for sustainable land use in Wanka watershed, northwestern highlands of Ethiopia

Long-term land use and land cover (LULC) dynamics information is essential to understand the trends and make necessary land management interventions, such as in the highlands of Ethiopia. This study analyzed six decades of LULC dynamics of Wanka watershed, Northwestern Ethiopian highlands. Two sets of aerial photographs (1957 and 2017), SPOT 5 and sentinel satellite imageries were analyzed. In addition, key informant interviews, focus group discussions and field observations were used to identify the drivers and impact of LULC change. It was found that cultivated and rural settlement land (CRSL), bare land, and urban built up area have been continuously expanded at the expenses of mainly forest and shrub lands. Over the entire study period (1957–2017) while the bare land and CRSL have increased by about 59% and 20% respectively, forest and shrub lands have declined by 59% and 57% respectively. Urban built up area has also expanded. The impact of popula- tion pressure and expansion of CRSL land were considerable. The trend of LULC dynamics in the study watershed implies adverse impact on the quality and quantity of the land resource. Hence, appropriate land use planning and strategies that reduce expansion of cultivated land need to be practiced

Seasonal variation of carbon fluxes in a sparse savanna in semi arid Sudan

<p>Abstract</p> <p>Background</p> <p>Large spatial, seasonal and annual variability of major drivers of the carbon cycle (precipitation, temperature, fire regime and nutrient availability) are common in the Sahel region. This causes large variability in net ecosystem exchange and in vegetation productivity, the subsistence basis for a major part of the rural population in Sahel. This study compares the 2005 dry and wet season fluxes of CO₂for a grass land/sparse savanna site in semi arid Sudan and relates these fluxes to water availability and incoming photosynthetic photon flux density (PPFD). Data from this site could complement the current sparse observation network in Africa, a continent where climatic change could significantly impact the future and which constitute a weak link in our understanding of the global carbon cycle.</p> <p>Results</p> <p>The dry season (represented by Julian day 35–46, February 2005) was characterized by low soil moisture availability, low evapotranspiration and a high vapor pressure deficit. The mean daily NEE (net ecosystem exchange, Eq. 1) was -14.7 mmol d^-1for the 12 day period (negative numbers denote sinks, i.e. flux from the atmosphere to the biosphere). The water use efficiency (WUE) was 1.6 mmol CO₂mol H₂O^-1and the light use efficiency (LUE) was 0.95 mmol CO₂mol PPFD^-1. Photosynthesis is a weak, but linear function of PPFD. The wet season (represented by Julian day 266–273, September 2005) was, compared to the dry season, characterized by slightly higher soil moisture availability, higher evapotranspiration and a slightly lower vapor pressure deficit. The mean daily NEE was -152 mmol d^-1for the 8 day period. The WUE was lower, 0.97 mmol CO₂mol H₂O^-1and the LUE was higher, 7.2 <it>μ</it>mol CO₂mmol PPFD^-1during the wet season compared to the dry season. During the wet season photosynthesis increases with PPFD to about 1600 <it>μ</it>mol m^-2s^-1and then levels off.</p> <p>Conclusion</p> <p>Based on data collected during two short periods, the studied ecosystem was a sink of carbon both during the dry and wet season 2005. The small sink during the dry season is surprising and similar dry season sinks have not to our knowledge been reported from other similar savanna ecosystems and could have potential management implications for agroforestry. A strong response of NEE versus small changes in plant available soil water content was found. Collection and analysis of flux data for several consecutive years including variations in precipitation, available soil moisture and labile soil carbon are needed for understanding the year to year variation of the carbon budget of this grass land/sparse savanna site in semi arid Sudan.</p

A global spectral library to characterize the world's soil

Soil provides ecosystem services, supports human health and habitation, stores carbon and regulates emissions of greenhouse gases. Unprecedented pressures on soil from degradation and urbanization are threatening agro-ecological balances and food security. It is important that we learn more about soil to sustainably manage and preserve it for future generations. To this end, we developed and analyzed a global soil visible-near infrared (vis-NIR) spectral library. It is currently the largest and most diverse database of its kind. We show that the information encoded in the spectra can describe soil composition and be associated to land cover and its global geographic distribution, which acts as a surrogate for global climate variability. We also show the usefulness of the global spectra for predicting soil attributes such as soil organic and inorganic carbon, clay, silt, sand and iron contents, cation exchange capacity, and pH. Using wavelets to treat the spectra, which were recorded in different laboratories using different spectrometers and methods, helped to improve the spectroscopic modelling. We found that modelling a diverse set of spectra with a machine learning algorithm can find the local relationships in the data to produce accurate predictions of soil properties. The spectroscopic models that we derived are parsimonious and robust, and using them we derived a harmonized global soil attribute dataset, which might serve to facilitate research on soil at the global scale. This spectroscopic approach should help to deal with the shortage of data on soil to better understand it and to meet the growing demand for information to assess and monitor soil at scales ranging from regional to global. New contributions to the library are encouraged so that this work and our collaboration might progress to develop a dynamic and easily updatable database with better global coverage. We hope that this work will reinvigorate our community's discussion towards larger, more coordinated collaborations. We also hope that use of the database will deepen our understanding of soil so that we might sustainably manage it and extend the research outcomes of the soil, earth and environmental sciences towards applications that we have not yet dreamed of

Africa Soil Information Service (AfSIS) - Soil Health Mapping

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Continuous monitoring of forest change dynamics with satellite time series

Several forest change detection algorithms are available for tracking and quantifying deforestation based on dense Landsat and Sentinel time series satellite data. Only few also capture regrowth after clearing in an accurate and continuous way across a diversity of forest types (including dry and seasonal forests) and are thus suitable to address the need for better information on secondary forest succession and for assessing forest restoration activities. We present a new change detection algorithm that makes use of the flexibility of kernel density estimations to create a forest reference phenology, taking into account all historical phenological variations of the forest rather than smoothing these out by curve fitting. The AVOCADO (Anomaly Vegetation Change Detection) algorithm allows detection of anomalies with a spatially explicit likelihood measure. We demonstrate the flexibility of the algorithm for three contrasting sites using all available Landsat time series data; ranging from tropical rainforest to dry miombo forest ecosystems, with different time series data densities, and characterized by different forest change types (e.g. selective logging, shifting cultivation). We found that the approach produced in general high overall accuracies (> 90%) across these varying conditions, but had lower accuracies in the dry forest site with a slight overestimation of disturbances and regrowth. The latter was due to the similarity of crops in the time series NDMI signal, causing false regrowth detections. In the moist forest site the low producer accuracies in the intact forest and regrowth class was due to its very small area class (most forest disappeared by the nineties). We showed that the algorithm is capable of capturing small-scale (gradual) changes (e.g. selective logging, forest edge logging) and the multiple changes associated to shifting cultivation. The performance of the algorithm has been shown at regional scale, but if larger scale studies are required a representative selection of reference forest types need to be selected carefully. The outputs of the change maps allow the estimation of the spatio-temporal trends in the proportions of intact forest, secondary forest and non-forest - information that is useful for assessing the areas and potential of secondary forests to accumulate carbon and forest restoration targets. The algorithm can be used for disturbance and regrowth monitoring in different ecozones, is user friendly, and open source

Regreening Africa: A bottom-up transformation of degraded lands

It is estimated that 20% of global land is either degraded or undergoing degradation, leading to an annual loss of 12 million hectares of productive land (UNCCD 2017). In Africa, some 715 million ha are degraded, including 65% of all arable land, 30% of all grazing land and 20% of all forests. This is due to increasing populations, poor land management, institutional challenges and climate change (Gnacadja and Wiese 2016). The benefits of taking action against land degradation outweigh the costs by up to seven times, implying that inaction will cost countries US$490 billion per year, while action to reverse land degradation could generate benefits worth up to US$1.4 trillion (ELD Initiative 2015