All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Permission for printing and for reprinting the material contained herein has been obtained by the publisher. Prediction of Soil Fertility Properties from a Globally Distributed Soil Mid-Infrared Spectral Library Nutrient Management & Soil & Plant Analysis S oil chemical and physical information is needed to give advice on land management. Th is is especially true in developing countries, where soil diagnostic surveillance systems have been proposed to overcome data shortages (Shepherd and Walsh, 2007). Mid-infrared (MIR) diff use refl ectance spectroscopy is a reliable and fast soil analytical tool (Janik et al., 1998) that could form a basis for diagnostic surveillance systems. Soil properties are predicted either by direct absorption of the light associated with functional groups (properties such as organic C, total N, or clay composition; Van der Marel and Beutelspacher, 1976) or by correlation to such properties and the mineral composition of the soil (properties such as cation exchange capacity [CEC] and soil texture). New samples can be predicted only if they fall within the property range of the calibration set (Naes et al., 2002). In many situations, a rapid and approximate estimate of soil chemical and physical properties is adequate, and resources for an elaborate analysis may not be available. A global calibration may meet this purpose. Some studies have tested soil infrared spectroscopy on diverse data sets at the regional scale. Reeves and Smith (2009), working with a North American library of 720 samples, came to the conclusion that neither MIR nor near-infrared (NIR) spectra yielded suitable calibrations even for organic C. Th ey attributed the poor performance to the extreme sample diversity in parent material, land

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.

Soil erosion has long been recognized as a major process of land degradation globally, affecting millions of hectares of land in the tropics and resulting in losses in productivity and biodiversity, decreased resilience of both marine and terrestrial ecosystems, and increased vulnerability to climate change. This paper presents an assessment of the extent of soil erosion in the global tropics at a moderate spatial resolution (500 m) based on a combination of systematic field surveys using the Land Degradation Surveillance Framework (LDSF) methodology and Earth observation data from the Moderate Resolution Imaging Spectroradiometer (MODIS) platform. The highest erosion prevalence was observed in wooded grassland, bushland, and shrubland systems in semi-arid areas, while the lowest occurrence was observed in forests. Observed erosion decreased with increasing fractional vegetation cover, but with high rates of erosion even at 50–60% fractional cover. These findings indicate that methods to assess soil erosion need to be able to detect erosion under relatively dense vegetation cover. Model performance was good for prediction of erosion based on MODIS, with high accuracy (~89% for detection) and high overall precision (AUC = 0.97). The spatial predictions from this study will allow for better targeting of interventions to restore degraded land and are also important for assessing the dynamics of land health indicators such as soil organic carbon. Given the importance of soil erosion for land degradation and that the methodology gives robust results that can be rapidly replicated at scale, we would argue that soil erosion should be included as a key indicator in international conventions such as the United Nations Convention to Combat Desertification.

No abstract

Land degradation is a major threat to food security in Sub Saharan Africa. Low infiltration rates in degraded soils increase the risk of surface runoff and decrease soil and groundwater recharge, resulting in further loss of soil fertility, water scarcity and crop failure. Increasing woody vegetation typically enhances soil infiltrability but little is known about how species may have differential effects on the soil hydrological properties. The aim of this study is to understand how woody vegetation and its functional properties affect soil fertility and infiltrability. We measured field‐saturated soil hydraulic conductivity (Kfs) and soil organic carbon (SOC) in 38 plots across agricultural landscapes in Muminji, Kenya. Woody vegetation and land use inventories took place and species functional traits were measured on the 63 most abundant species. We systematically tested the effects of vegetation quantity (aboveground woody biomass and vegetation cover) and quality (functional properties and diversity) on soil health (Kfs as a proxy for soil infiltrability and SOC for soil fertility). We found that both vegetation quantity and quality affected soil health. Aboveground woody biomass increased the Kfs and we found a nearly significant positive effect of vegetation cover on SOC. Woody plants with a low leaf thickness positively affected Kfs and a nearly significant negative effect of wood moisture content on SOC was found. Synthesis and applications. This study demonstrates that the systematic assessment of vegetation can lead to evidence‐based recommendations to guide land restoration. We found that avoiding bare soil and promoting woody plants, while favouring species with thin leaves and avoiding species with a very low wood density and water storage strategy, is beneficial for soil health across agricultural landscapes in East African drylands.