BUSCADOR RECOLECTA

We explored the relative importance of climate oscillations and human-driven disturbances on the change in vegetation biomass in agroecosystems, and whether it is associated with land use. Our main contribution is a quantitative treatment of these factors in equivalent terms, i.e. not assuming any of them to be principal. The study was carried out in the drylands of the Iberian Peninsula, NW Maghreb, Palestinian West Bank, Mozambique, China and NE Brazil, using satellite time-series and the corresponding climate fields, at ten-year observation periods with spatial and temporal resolutions of 1000 m (250 m in Palestine) and one year, respectively. For each region, we separated the relative weights of climate and time by fitting multiple-stepwise regressions to a vegetation index as the dependent variable, and annual aridity (Aridity) and year number (Time) as predictors. The relative strength of the resulting standard partial regression coefficients was then compared by the Wilcoxon Signed Ranks test, and their combined associations with land uses were determined using chi-square tests. Some points of convergence are: 1. The relative weights of Aridity and Time depend on particular regional conditions and can be determined. 2. Such weights are associated with land use intensification, such that if vegetation increases over Time, Aridity increases its relative importance with intensification; if vegetation is degrading, Aridity is always more important than Time. 3. Aridity is an indicator of vulnerability to climate warming. Resilience can be improved by reducing land use intensification. 4. Vulnerability may worsen under constant climate if agriculture is intensified. These patterns enhance an integrated understanding of Sustainable Development Goals Indicator 15.3.1, particularly its land cover and productivity trend components., This study was funded by the European Commission [LifeWatch ERIC – SUMHAL ref. LIFEWATCH-2019-09-CSIC-13, MELODIES – FP7 Contract 603525 and BIODESERT – ERC Grant Agreement 647038], the European Space Agency [DUE – DesertWatch Extension Contract 18487/04/I-LG, and Dragon Projects 10367 and 32396] and Tragsatec (Grupo Tragsa) [Contract 25.604].

Climate archives are time series. They are used to assess temporal trends of a climate-dependent target variable, and to make climate atlases. A high-resolution gridded dataset with 1728 layers of monthly mean maximum, mean and mean minimum temperatures and precipitation for the NW Maghreb (28ºN-37.3ºN, 12ºW-12ºE, 1-km resolution) from 1973 through 2008 is presented. The surfaces were spatially interpolated by ANUSPLIN, a thin-plate smoothing spline technique approved by the World Meteorological Organization (WMO), from georeferenced climate records drawn from the Global Surface Summary of the Day (GSOD) and the Global Historical Climatology Network-Monthly (GHCN-Monthly version 3) products. Absolute errors for surface temperatures are approximately 0.5ºC for mean and mean minimum temperatures, and peak up to 1.76ºC for mean maximum temperatures in summer months. For precipitation, the mean absolute error ranged from 1.2 to 2.5 mm, but very low summer precipitation caused relative errors of up to 40% in July. The archive successfully captures climate variations associated with large to medium geographic gradients. This includes the main aridity gradient which increases in the S and SE, as well as its breaking points, marked by the Atlas mountain range. It also conveys topographic effects linked to kilometric relief mesoforms., Focus on Morocco, Algeria and Tunisia North of 28ºN, DeSurvey IP (European Commission FP6 contract No. 003950), MesoTopos (Junta de Andalucia PE P08-RNM-04023) and MELODIES (European Commission FP7, contract No. 603525), Yes

This article belongs to the Special Issue Geospatial Data., Climate archives are time series. They are used to assess temporal trends of a climate-dependent target variable, and to make climate atlases. A high-resolution gridded dataset with 1728 layers of monthly mean maximum, mean and mean minimum temperatures and precipitation for the NW Maghreb (28°N–37.3°N, 12°W–12°E, ~1-km resolution) from 1973 through 2008 is presented. The surfaces were spatially interpolated by ANUSPLIN, a thin-plate smoothing spline technique approved by the World Meteorological Organization (WMO), from georeferenced climate records drawn from the Global Surface Summary of the Day (GSOD) and the Global Historical Climatology Network-Monthly (GHCN-Monthly version 3) products. Absolute errors for surface temperatures are approximately 0.5 °C for mean and mean minimum temperatures, and peak up to 1.76 °C for mean maximum temperatures in summer months. For precipitation, the mean absolute error ranged from 1.2 to 2.5 mm, but very low summer precipitation caused relative errors of up to 40% in July. The archive successfully captures climate variations associated with large to medium geographic gradients. This includes the main aridity gradient which increases in the S and SE, as well as its breaking points, marked by the Atlas mountain range. It also conveys topographic effects linked to kilometric relief mesoforms., This dataset was constructed with funding from the following projects: DeSurvey IP (European Commission FP6 contract No. 003950), MesoTopos (Junta de Andalucia PE P08-RNM-04023) and MELODIES (European Commission FP7, contract No. 603525). The latter also covered the open access publishing costs., Peer reviewed

States of ecological maturity and temporal trends of drylands in Morocco, Algeria and Tunisia north of 28°N are reported for 1998–2008. The input data were Normalized Difference Vegetation Index databases and corresponding climate fields, at a spatial resolution of 1 km and a temporal resolution of one month. States convey opposing dynamics of human exploitation and ecological succession. They were identified synchronically for the full period by comparing each location to all other locations in the study area under equivalent aridity. Rain Use Efficiency (RUE) at two temporal scales was used to estimate proxies for biomass and turnover rate. Biomass trends were determined for every location by stepwise regression using time and aridity as predictors. This enabled human-induced degradation to be separated from simple responses to interannual climate variation. Some relevant findings include large areas of degraded land, albeit improving over time or fluctuating with climate, but rarely degrading further; smaller, but significant areas of mature and reference vegetation in most climate zones; very low overall active degradation rates throughout the area during the decade observed; biomass accumulation over time exceeding depletion in most zones; and negative feedback between land states and trends suggesting overall landscape persistence. Semiarid zones were found to be the most vulnerable. Those results can be disaggregated by country or province. The combination with existing land cover maps and national forest inventories leads to the information required by the two progress indicators associated with the United Nations Convention to Combat Desertification strategic objective to improve the conditions of ecosystems and with the Sustainable Development Goal Target 15.3 to achieve land degradation neutrality. Beyond that, the results are also useful as a basis for land management and restoration., This research was funded by the following projects: DeSurvey IP (European Commission
FP6 Contract No. 003950), CLIMEDE (NATO Collaborative Linkage Grant ref. 983596), MesoTopos (Junta de
Andalucia PE P08-RNM-04023) and MELODIES (European Commission FP7, Contract No. 603525), which also
covered open access publishing. Four anonymous reviewers made constructive comments and suggestions that
improved the manuscript.
We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI).

We explored the relative importance of climate oscillations and human-driven disturbances on the change in vegetation biomass in agroecosystems, and whether it is associated with land use. Our main contribution is a quantitative treatment of these factors in equivalent terms, i.e. not assuming any of them to be principal. The study was carried out in the drylands of the Iberian Peninsula, NW Maghreb, Palestinian West Bank, Mozambique, China and NE Brazil, using satellite time-series and the corresponding climate fields, at ten-year observation periods with spatial and temporal resolutions of 1000 m (250 m in Palestine) and one year, respectively. For each region, we separated the relative weights of climate and time by fitting multiple-stepwise regressions to a vegetation index as the dependent variable, and annual aridity (Aridity) and year number (Time) as predictors. The relative strength of the resulting standard partial regression coefficients was then compared by the Wilcoxon signed ranks test, and their combined associations with land uses were determined using Chi-square tests. Some points of convergence are as follows: (1) The relative weights of Aridity and Time depend on particular regional conditions and can be determined. (2) Such weights are associated with land use intensification, such that if vegetation increases over Time, Aridity increases its relative importance with intensification; if vegetation is degrading, Aridity is always more important than Time. (3) Aridity is an indicator of vulnerability to climate warming. Resilience can be improved by reducing land use intensification. 4. Vulnerability may worsen under constant climate if agriculture is intensified. These patterns enhance an integrated understanding of Sustainable Development Goals Indicator 15.3.1, particularly its land cover and productivity trend components., This study was funded by the European Commission [LifeWatch ERIC—SUMHAL ref. LIFEWATCH-2019-09-CSIC-13, MELODIES— FP7 Contract 603525 and BIODESERT—ERC Grant Agreement 647038], the European Space Agency [DUE—DesertWatch Extension Contract 18487/04/I-LG, and Dragon Projects 10367 and 32396] and Tragsatec (Grupo Tragsa) [Contract 25.604]., Peer reviewed

Mitigation strategies are crucial for desertification given that once degradation starts, other solutions are extremely expensive or unworkable. Prevention is key to handle this problem and solutions should be based on spotting and deactivating the stressors of the system. Following this topic, the Spanish Plan of Action to Combat Desertification (SPACD) created the basis for implementing two innovative approaches to evaluate the threat of land degradation in the country. This paper presents tools for preventing desertification in the form of a geomatic approach to enable the periodic assessments of the status and trends of land condition. Also System Dynamics modelling has been used to integrate bio-physical and socio-economic aspects of desertification to explain and analyse degradation in the main hot spots detected in Spain. The 2dRUE procedure was implemented to map the land-condition status by comparing potential land productivity according to water availability, the limiting factor in arid lands, with plant-biomass data. This assessment showed that 20% of the territory is degraded and an additional 1% is actively degrading. System Dynamics modelling was applied to study the five desertification landscapes identified by the SPACD. The risk analysis, implemented on these models, concluded that 'Herbaceous crops affected by soil erosion' is the landscape most at risk, while the Plackett-Burman sensitivity analysis used to rank the factors highlighted the supremacy of climatic factors above socioeconomic drivers., This work was financed by the Public Enterprise TRAGSATEC on behalf of the Spanish Ministry of Agriculture, Food, and Environment (General Secretary for Agriculture and Food; General Directorate for Rural Development and Forestry Policies) through the Contract of Technical Support 23.674. It was also supported by R&D Projects DeSurvey IP (European Commission FP6 Contract No. 003950), MesoTopos (Junta de Andalucia PE P08-RNM-04023) and MELODIES (European Commission FP7, contract No. 603525).
The authors also acknowledge the contribution of the Ecuatorian SENESCYT Research Project PROMETEO-CEB-014-2015 and the Chilean FONDECYT Research Project 1161105., Peer reviewed