Chlorophyll a concentration (Chla) is a well-proven proxy of biocrust development, photosynthetic organisms' status, and recovery monitoring after environmental disturbances. However, laboratory methods for the analysis of chlorophyll require destructive sampling and are expensive and time consuming. Indirect estimation of chlorophyll a by means of soil surface reflectance analysis has been demonstrated to be an accurate, cheap, and quick alternative for chlorophyll retrieval information, especially in plants. However, its application to biocrusts has yet to be harnessed. In this study we evaluated the potential of soil surface reflectance measurements for non-destructive Chla quantification over a range of biocrust types and soils. Our results revealed that from the different spectral transformation methods and techniques, the first derivative of the reflectance and the continuum removal were the most accurate for Chla retrieval. Normalized difference values in the red-edge region and common broadband indexes (e.g., normalized difference vegetation index (NDVI)) were also sensitive to changes in Chla. However, such approaches should be carefully adapted to each specific biocrust type. On the other hand, the combination of spectral measurements with non-linear random forest (RF) models provided very good fits (R 2 > 0.94) with a mean root mean square error (RMSE) of about 6.5 µg/g soil, and alleviated the need for a specific calibration for each crust type, opening a wide range of opportunities to advance our knowledge of biocrust responses to ongoing global change and degradation processes from anthropogenic disturbance.

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Land degradation is one of the main threats to dryland sustainability in the next decades, hence restoration of the degraded land from drylands is an urgent need to maintain ecosystem functionality and their ability to provide ecosystem services. To achieve this goal, restoration practices should pursue the recovery of the main ground components, arranged in an optimal spatial configuration, to mimic undisturbed natural conditions. Drylands function as complex ecohydrologically coupled systems in which interplant source areas, frequently covered by biocrusts, act as sources of runoff and nutrients to adjacent vegetation, which act as sinks for these resources. Thus, one way to increase dryland restoration success is through an optimal spatial configuration of biocrusts and plants that maximizes an efficient use of the limited resources within the system. In this study, we selected a degraded slope from a limestone quarry located in Almería province (SE Spain) and modeled how active restoration of the biocrust through soil inoculation with cyanobacteria and its combination with different spatial configurations of vegetation affected runoff redistribution and erosion. For that, we applied the spatially distributed Limburg Soil Erosion Model (LISEM) which was able to predict the erosion measured on the slope during the study period with low error (RMSE = 17.8%). Modeling results showed that the introduction of vegetation on the degraded slope reduced runoff between 2 and 24% and erosion between 4 and 17% for the scenario with plants compared to the one without restoration management. Of all the vegetation spatial configurations tested, the one that provided better results was the scenario in which plants were located in the areas of higher water accumulation (higher topographic wetness index). Moreover, we found that active biocrust restoration by cyanobacteria inoculation significantly reduced erosion by 70–90%, especially during the first stages of plant development, while maintaining water supply to vegetation. These findings highlight the potential of water redistribution and erosion simulation models to identify the most optimal spatial configuration of ground covers that maximizes water and nutrient supply to vegetation, while minimizes water, sediment, and nutrient losses by erosion, thus serving as an efficient tool to plan restoration actions in drylands.

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The effects of feeds containing several food by‐products on the fatty acid compositions of Hermetia illucens larvae were studied. Coconut, tomato, apple, and viscera by‐products, as well as combinations of control feed containing carbohydrate‐rich additives were assayed. Final live weight (mg) and daily growth coefficient (%/day) ranged from 41 and 0.548 (tomato) to 93 and 1.292 (coconut), respectively. Oils containing lauric acid were obtained from larvae‐fed vegetable by‐products, especially those fed feed containing apple, coconut, and tomato (65.3, 54.4 and 52.3% of total fatty acids, respectively). Feed containing apple and a 1:1 (w/w) mix of control feed and apple by‐products yielded the highest proportion of fatty acids in the larvae (23.5 and 15.6 g fatty acids/100 g fresh larvae, respectively). The properties of biodiesel that could be produced from larvae fatty acids were calculated and the following values were obtained: cetane number (58.5–60.2), higher heating value (38.3–39.0 MJ·kg−1), density (0.869–0.873 g·cm−3), and induction period, an index of oxidation stability (8.4–150 hours). Such values were within the ranges specified by the ASTM D6751 and Europe EN 14214:2008 standards, while values for cold filter plugging point (−9.6 to 2.8 °C) were adequate for biodiesels intended for use in temperate climates. However, values for kinematic viscosity (2.93–3.58 mm2·s−1) were slightly below the requirements of EN 14214:2008 (3.5–5.0). Overall, larvae fed food by‐products produced lauric acid‐rich oils, and the calculated properties of the oils were largely suitable for biodiesel production.