Javier Cabello

Evaluating the consistency of the 1982-1999 NDVI trends in the Iberian Peninsula across four time-series derived from the AVHRR sensor: LTDR, GIMMS, FASIR, and PAL-II.

Successive efforts have processed the Advanced Very High Resolution Radiometer (AVHRR) sensor archive to produce Normalized Difference Vegetation Index (NDVI) datasets (i.e., PAL, FASIR, GIMMS, and LTDR) under different corrections and processing schemes. Since NDVI datasets are used to evaluate carbon gains, differences among them may affect nations’ carbon budgets in meeting international targets (such as the Kyoto Protocol). This study addresses the consistency across AVHRR NDVI datasets in the Iberian Peninsula (Spain and Portugal) by evaluating whether their 1982–1999 NDVI trends show similar spatial patterns. Significant trends were calculated with the seasonal Mann-Kendall trend test and their spatial consistency with partial Mantel tests. Over 23% of the Peninsula (N, E, and central mountain ranges) showed positive and significant NDVI trends across the four datasets and an additional 18% across three datasets. In 20% of Iberia (SW quadrant), the four datasets exhibited an absence of significant trends and an additional 22% across three datasets. Significant NDVI decreases were scarce (croplands in the Guadalquivir and Segura basins, La Mancha plains, and Valencia). Spatial consistency of significant trends across at least three datasets was observed in 83% of the Peninsula, but it decreased to 47% when comparing across the four datasets. FASIR, PAL, and LTDR were the most spatially similar datasets, while GIMMS was the most different. The different performance of each AVHRR dataset to detect significant NDVI trends (e.g., LTDR detected greater significant trends (both positive and negative) and in 32% more pixels than GIMMS) has great implications to evaluate carbon budgets. The lack of spatial consistency across NDVI datasets derived from the same AVHRR sensor archive, makes it advisable to evaluate carbon gains trends using several satellite datasets and, whether possible, independent/additional data sources to contrast.

The ecosystem functioning dimension in conservation: insights from remote sensing

An important goal of conservation biology is the maintenance of ecosystem processes. Incorporating quantitative measurements of ecosystem functions into conservation practice is important given that it provides not only proxies for biodiversity patterns, but also new tools and criteria for management. In the satellite era, the translation of spectral information into ecosystem functional variables expands and complements the more traditional use of satellite imagery in conservation biology. Remote sensing scientists have generated accurate techniques to quantify ecosystem processes and properties of key importance for conservation planning such as primary production, ecosystem carbon gains, surface temperature, albedo, evapotranspiration, and precipitation use efficiency; however, these techniques are still unfamiliar to conservation biologists. In this article, we identify specific fields where a remotely-sensed characterization of ecosystem functioning may aid conservation science and practice. Such fields include the management and monitoring of species and populations of conservation concern; the assessment of ecosystem representativeness and singularity; the use of protected areas as reference sites to assess global change effects; the implementation of monitoring and warning systems to guide adaptive management; the direct evaluation of supporting ecosystem services; and the planning and monitoring of ecological restorations. The approaches presented here illustrate feasible ways to incorporate the ecosystem functioning dimension into conservation through the use of satellite-derived information.

Agricultural development vs biodiversity conservation: the Mediterranean semiarid vegetation in El Ejido (Almera, southeastern Spain)

The development of a greenhouse agriculture in the traditionally impoverished region of Poniente de Almería, on the Mediterranean coast of Spain, has caused an enormous rise in living standards. However, the environmental impact of this badly-planned growth threatens the every dynamics of the exploitation system. A special examination must be made of the use of the three major resources responsible for the functioning of greenhouse production and its impact on the ecosystems and particularly on the vegetation. These resources are: clayey soils, sand from fossil dunes and ground water. While the use of the clayey soils and sand have negative effects on the conservation of ecologically valuable communities found nowhere else in Europe, ground water overexploitation has produced an increase in salinity in most of the aquifers. Of these, sand has been by far the best monitored resource and restoration programmes have been implemented in the extraction zones. This survey deals with the recent evolution of areas where the arto (Maytenus senegalensis subsp. europaeus) and the sabina (Juniperus phoenicea subsp. turbinata) have long been the dominant species, although the presence of the former is nowadays notoriously diminished. The study is based on aerial photographs taken in 1957, 1977 and 1985, together with our own field work. Curiously enough, all this man-made process of degradation has stimulated ornithological diversity. Finally, we propose here some measures which aim to preserve the most important enclaves of these Mediterranean shrub formations, specially those of the arto, since sabina-dominated communities already belong to existing conservation areas.

Baseline characterization of major Iberian vegetation types based on the NDVI dynamics

We present an approach to derive baseline conditions for the radiation intercepted by vegetation in the largest remaining patches of homogeneous vegetation of the Iberian Peninsula. These baseline conditions can serve as a reference to assess environmental changes. We also characterized the major vegetation types of the Peninsula in the functional space defined by the NDVI dynamics and analyzed the climatic controls of NDVI dynamics. We analysed the attributes of the NDVI seasonal dynamics: annual mean (NDVI-I), relative range (RREL), NDVI maximum and minimum values (MAX and MIN), months of MAX and MIN (MMAX and MMIN), and their inter-annual variabilities (1982–1999). We selected as reference sites only homogeneous pixels occupied by natural vegetation. We described their relationship with climatic variables using regression models. NDVI-I and RREL captured most of the variability of the NDVI annual profile. Eurosiberian vegetation types were more productive, with winter minima and summer maxima. Mediterranean vegetation had summer minima and maxima distributed from autumn to spring. Inter-annual differences (higher in the Mediterranean) were low for NDVI-I and MAX and high for RREL and MIN. Precipitation was the main driver of NDVI-I for the Mediterranean pixels while temperature constrained it in the Eurosiberian ones. Seasonality (RREL) was associated with winter temperatures in Eurosiberian areas and with summer drought in Mediterranean ones. The Iberian vegetation types mainly differed in terms of total production and seasonality. Such differences were related to mean and inter-annual variation in precipitation and temperature associated with the Eurosiberian and Mediterranean climate zones. The NDVI dynamics allowed us to identify a functional signature for each vegetation type which captures differences that go beyond their range of climatic factors. Our baseline descriptions, based on a common approach to characterize vegetation functioning, are proposed as reference situations to evaluate the impact of environmental changes on the remaining large patches of single major natural and seminatural vegetation types.

Temporal and spatial patterns of ecosystem functioning in protected arid areas in southeastern Spain

Abstract We characterized the spatial variability and temporal dynamics of the photosynthetic active radiation absorbed (APAR) by the canopy, a descriptor of ecosystem functioning, in Cabo de Gata - Níjar Natural Park (CGNNP) (Spain). Ecosystem functioning was characterized for five landscape classes using the Normalized Difference Vegetation Index (NDVI) derived from NOAA/AVHRR LAC (1 km × 1 km) images. We also used a 19-year time series of NDVI PAL data (8 km × 8 km) to analyse the relationship APAR-precipitation inside and outside the park. The vegetation of CGNNP absorbed less than 20% of the incoming radiation. Plains intercepted 37% and hills 14% less photosynthetic active radiation than mountains, the most productive landscape of the park. CGNNP showed a well-defined growing season with a unique peak of APAR. Plains and piedmont, covered by annual vegetation displayed an earlier development of the leaf area index than the shrublands and grasslands typical of the other landscapes. APAR had a significant relationship with the sum of the precipitation of the current and two previous growing seasons, except for the plains. We found that the APAR of the areas more modified by humans (outside the park) showed a lower sensitivity to changes in precipitation than those under protection. The differences were higher if the accumulated precipitation of the previous three growing seasons was considered. The description of such differences in the response of absorbed PAR to water availability are proposed as the base of a monitoring system for semi-arid and arid areas. Abbreviations: ANPP = Above-ground net primary production; APAR = Photosynthetic active radiation absorbed by green vegetation; CGNNP = Cabo de Gata - Níjar Natural Park; fAPAR = Fraction of incoming photosynthetic active radiation absorbed by green vegetation; NPP = Net primary production; PPT = Precipitation; PUE = Precipitation use efficiency.

From supply to social demand: a landscape-scale analysis of the water regulation service

Worldwide water managers and policy makers are faced by the increasing demands for limited and scarce water resources, particularly in semi-arid ecosystems. This study assesses water regulation service in semi-arid ecosystems of the southeastern Iberian Peninsula. Comparisons between the supply–demand sides were analyzed across different landscape units. We mapped the biophysical supply as the potential groundwater recharged by aquifers and water supplies from reservoirs. The social demand was focused on an analysis of water consumed or used for irrigation and the stakeholder’s perceptions regarding water regulation importance and vulnerability. Results show that some landscape units are able to maintain and conserve water regulation service when the volume of recharge water by aquifers and the water supply from reservoirs is greater than its consumption (e.g. rural landscape units). However, we also found potential social conflicts in landscape units where water consumption and use is much greater than the water recharge and supply. This particularly occurs in the non-protected littoral areas with the highest water consumption and where water is perceived as a non-important and vulnerable natural resource. Overall, our results emphasized the importance of assessing ecosystem services from both supply to demand sides, for identifying social conflicts and potential trade-offs, and to provide practical information about how to integrate the ecosystem service research into landscape management and planning.

Modeling spatial distribution of European badger in arid landscapes: an ecosystem functioning approach

Understanding the factors determining the spatial distribution of species is a major challenge in ecology and conservation. This study tests the use of ecosystem functioning variables, derived from satellite imagery data, to explore their potential use in modeling the distribution of the European badger in Mediterranean arid environments. We found that the performance of distribution models was enhanced by the inclusion of variables derived from the Enhanced Vegetation Index (EVI), such as mean EVI (a proxy for primary production), the coefficient of variation of mean EVI (an indicator of seasonality), and the standard deviation of mean EVI (representing spatial heterogeneity of primary production). We also found that distributions predicted by remote sensing data were consistent with the ecological preferences of badger in those environments, which may be explained by the link between EVI-derived variables and the spatial and temporal variability of food resource availability. In conclusion, we suggest the incorporation of variables associated with ecosystem function into species modeling exercises as a useful tool for improving decision-making related to wildlife conservation and management.

Deep-learning versus OBIA for scattered shrub detection with Google Earth imagery: Ziziphus lotus as case study

There is a growing demand for accurate high-resolution land cover maps in many fields, e.g., in land-use planning and biodiversity conservation. Developing such maps has been traditionally performed using Object-Based Image Analysis (OBIA) methods, which usually reach good accuracies, but require a high human supervision and the best configuration for one image often cannot be extrapolated to a different image. Recently, deep learning Convolutional Neural Networks (CNNs) have shown outstanding results in object recognition in computer vision and are offering promising results in land cover mapping. This paper analyzes the potential of CNN-based methods for detection of plant species of conservation concern using free high-resolution Google EarthTM images and provides an objective comparison with the state-of-the-art OBIA-methods. We consider as case study the detection of Ziziphus lotus shrubs, which are protected as a priority habitat under the European Union Habitats Directive. Compared to the best performing OBIA-method, the best CNN-detector achieved up to 12% better precision, up to 30% better recall and up to 20% better balance between precision and recall. Besides, the knowledge that CNNs acquired in the first image can be re-utilized in other regions, which makes the detection process very fast. A natural conclusion of this work is that including CNN-models as classifiers, e.g., ResNet-classifier, could further improve OBIA methods. The provided methodology can be systematically reproduced for other species detection using our codes available through (https://github.com/EGuirado/CNN-remotesensing).

What is socio-ecological research delivering? A literature survey across 25 international LTSER platforms

With an overarching goal of addressing global and regional sustainability challenges, Long Term Socio-Ecological Research Platforms (LTSER) aim to conduct place-based research, to collect and synthesize both environmental and socio-economic data, and to involve a broader stakeholder pool to set the research agenda. To date there have been few studies examining the output from LTSER platforms. In this study we enquire if the socio-ecological research from 25 self-selected LTSER platforms of the International Long-Term Ecological Research (ILTER) network has produced research products which fulfil the aims and ambitions of the paradigm shift from ecological to socio-ecological research envisaged at the turn of the century. In total we assessed 4983 publically available publications, of which 1112 were deemed relevant to the socio-ecological objectives of the platform. A series of 22 questions were scored for each publication, assessing relevance of responses in terms of the disciplinary focus of research, consideration of human health and well-being, degree of stakeholder engagement, and other relevant variables. The results reflected the diverse origins of the individual platforms and revealed a wide range in foci, temporal periods and quantity of output from participating platforms, supporting the premise that there is a growing trend in socio-ecological research at long-term monitoring platforms. Our review highlights the challenges of realizing the top-down goal to harmonize international network activities and objectives and the need for bottom-up, self-definition for research platforms. This provides support for increasing the consistency of LTSER research while preserving the diversity of regional experiences.

Comunidades vegetales rupícolas y subrupícolas del sudeste ibérico (Sierra de Los Filabres)

La sierra de Los Filabres es una interesante encrucijada biogeografica donde existen grandes contrastes ambientales, produciendose muchos gradientes ecologicos. Tras una estratificacion territorial, se reconocieron los diversos habitats rupicolas y subrupicolas, donde fueron muestreadas mediante el metodo fitosociologico clasico las comunidades vegetales colonizantes. Como resultado se encontraron once fitocenosis diferentes pertenecientes a cinco clases fitosociologicas, donde destacan Teucrio-Kerneretum boissieri subas. alyssetosum cadevaliani, Cosentinio-Teucrietum freynii o Centrantho nevadensis-Sedetum brevifolii, y se describen como novedosas una comunidad de Saxifraga trabutiana y la asociacion Diantho broteroi-Launaetum laniferae.