Suchergebnisse

Mediterranean temporary ponds on Doñana's aeolian sands form an extensive system of small dynamic water bodies, dependent on precipitation and groundwater, of considerable importance for biodiversity conservation. Different areas of the aeolian sands have received different levels of environmental protection since 1969, and this has influenced the degree of conservation and the flooding dynamic of these temporary surface waters. We use the Landsat series of satellite images from 1985 to 2014 to study the temporal dynamic of small temporary water bodies on the aeolian sands in relation to the protection level and to distance to water abstraction pressures from agriculture and residential areas. The results show that even with small and ephemeral water bodies optical remote sensing time-series are an effective way to study their flooding temporal dynamics. The protected areas of the aeolian sands hold a better preserved system of temporary ponds, with a flooding dynamic that fluctuates with precipitation. The unprotected area shows an increase in mean hydroperiod duration, and surface flooded, and a decline in hydroperiod variability. This seems to be due to the creation of irrigation ponds and the artificialization of the flooding regime of the natural temporary ponds, that either receive excess irrigation water or dry-up due to the lowering of the groundwater table level. Although a decline in hydroperiod duration of temporary ponds is seen as negative to the system, an increase in hydroperiod of surface waters due to artificialization, or a decline in variability cannot be considered as positive compensatory effects. ; This study has been funded by the Spanish Ministry of Science and Innovation through the research projects HYDRA (#CGL2006-02247/BOS) and HYDRA2 (CGL2009-09801/BOS), and by funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 641762 to ECOPOTENTIAL project. We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI)

This paper presents a semi-automatic procedure to discriminate seasonally flooded areas in the shallow temporary marshes of Doñana National Park (SW Spain) by using a radiommetrically normalized long time series of Landsat MSS, TM, and ETM+ images (1974–2014). Extensive field campaigns for ground truth data retrieval were carried out simultaneous to Landsat overpasses. Ground truth was used as training and testing areas to check the performance of the method. Simple thresholds on TM and ETM band 5 (1.55–1.75 μm) worked significantly better than other empirical modeling techniques and supervised classification methods to delineate flooded areas at Doñana marshes. A classification tree was applied to band 5 reflectance values to classify flooded versus non-flooded pixels for every scene. Inter-scene cross-validation identified the most accurate threshold on band 5 reflectance (ρ < 0.186) to classify flooded areas (Kappa = 0.65). A joint TM-MSS acquisition was used to find the MSS band 4 (0.8 a 1.1 μm) threshold. The TM flooded area was identical to the results from MSS 4 band threshold ρ < 0.10 despite spectral and spatial resolution differences. Band slicing was retrospectively applied to the complete time series of MSS and TM images. About 391 flood masks were used to reconstruct historical spatial and temporal patterns of Doñana marshes flooding, including hydroperiod. Hydroperiod historical trends were used as a baseline to understand Doñana's flooding regime, test hydrodynamic models, and give an assessment of relevant management and restoration decisions. The historical trends in the hydroperiod of Doñana marshes show two opposite spatial patterns. While the north-western part of the marsh is increasing its hydroperiod, the southwestern part shows a steady decline. Anomalies in each flooding cycle allowed us to assess recent management decisions and monitor their hydrological effects. ; : This study was funded by the Spanish Ministry of Science and Innovation through the research projects HYDRA (#CGL2006-02247/BOS) and HYDRA2 (CGL2009-09801/BOS), and by funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 641762 to ECOPOTENTIAL project. The Espacio Natural de Doñana provided permits for fieldwork in protected areas with restricted access and historical data from water column readings. We are grateful to many MSc students who helped in image processing and field sampling. We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI).

Plant primary production is a key driver of several ecosystem functions in seasonal marshes, such as water purification and secondary production by wildlife and domestic animals. Knowledge of the spatio-temporal dynamics of biomass production is therefore essential for the management of resources—particularly in seasonal wetlands with variable flooding regimes. We propose a method to estimate standing aboveground plant biomass using NDVI Land Surface Phenology (LSP) derived from MODIS, which we calibrate and validate in the Doñana National Park's marsh vegetation. Out of the different estimators tested, the Land Surface Phenology maximum NDVI (LSP-Maximum-NDVI) correlated best with ground-truth data of biomass production at five locations from 2001–2015 used to calibrate the models (R 2 = 0.65). Estimators based on a single MODIS NDVI image performed worse (R 2 ≤ 0.41). The LSP-Maximum-NDVI estimator was robust to environmental variation in precipitation and hydroperiod, and to spatial variation in the productivity and composition of the plant community. The determination of plant biomass using remote-sensing techniques, adequately supported by ground-truth data, may represent a key tool for the long-term monitoring and management of seasonal marsh ecosystems. ; We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI). ; David Aragonés, Isabel Afán, Ricardo Díaz-Delgado and Diego García Díaz (EBD-LAST) provided support for remote-sensing and LSP analyses. Alfredo Chico, José Luis del Valle and Rocío Fernández Zamudio (ESPN, ICTS-RBD) provided logistic support and taxonomic expertise during the field work (validation dataset). Ernesto García and Cristina Pérez assisted with biomass harvesting and processing (calibration dataset). Gerrit Heil provided support in the project design. This study received funding from Ministerio de Medio Ambiente-Parque Nacional de Doñana, Consejeria de Medio Ambiente, Junta de Andalucia (1999–2000): RNM118 Junta de Andalucia (2003); the European Union's Horizon 2020 Research and Innovation Program under grant agreement No. 641762 to ECOPOTENTIAL project; and the Spanish Ministry of Economy, Plan Estatal de I+D+i 2013–2016, under grant agreement CGL2016-81086-R to GRAZE project.

In this study we examined long-term variation in the selection of nesting cliffs for the recovering population of the Bearded Vulture Gypaetus barbatus inhabiting the Spanish Pyrenees. We focussed on variables indicating a high probability of cliff occupancy as determined by a previously published model. Although the breeding population increased from 53 to 93 territories between 1991 and 2002, the breeding range expanded only slightly. New and old nesting cliffs had similar habitat features in relation to topography, altitude and degree of human influence, but the distance between occupied cliffs was reduced (from 11.1 to 8.9 km). Thus the probabilities of occupation predicted by the model were lower for newly colonized locales. Our study shows that territory compression may occur without serious modification of nesting habitat quality. These results may arise from the lack of strong territorial behaviour by Bearded Vultures and the availability of high-quality cliffs. The relatively low quality of sites in adjacent mountains may prevent the expansion of the breeding range, but conspecific attraction may also play a role. Our study confirms that monitoring changes in key variables important to habitat selection is useful in determining long-term trends in settlement patterns in heterogeneous environments. The results also suggest that the available nest-site selection model may accurately predict cliff occupancy by Bearded Vultures in those areas where the distance to the nearest neighbour is not a limiting factor. In particular, the model may be useful in establishing priority areas for reintroduction ; This work was financed by the Ministry of Environment of the Autonomous Government of Andalusía, within the Project 'Studies of viability for the reintroduction of the Bearded Vulture in Andalusía'. Support was also obtained from the BBVA Foundation through its award for scientific research in Conservation Biology (2004). ; Peer reviewed

Context The guanaco is the largest wild herbivore inhabiting the Patagonian steppes. Since the end of the 19th Century, it has suffered a progressive decline in numbers owing to poaching and unregulated hunting because of on an assumed competition with sheep. Unfortunately, there has never been a management program for guanaco populations in Argentine Patagonia. Consequently, the guanaco is still considered a pest species by ranchers and has never been considered profitable in the range management model implemented in Patagonia. Aims The present article updates the distribution limits of guanaco and estimate its abundance across Chubut, a large province of Patagonia, Argentina. The relative effects of several environmental and anthropogenic factors on guanaco distribution are also assessed. Methods Road surveys (7010km) and species distribution modelling were used to build a habitat suitability model and a distribution map. A distance sampling method was used to estimate guanaco population densities and size. The survey effort required to monitor population trends in this region was also calculated. Key results According to the best habitat suitability model, guanaco distribution decreased with altitude and primary productivity, as measured by Normalised Difference Vegetation Index (NDVI), and increased with the distance to the nearest urban centre and oil field. Guanaco distribution showed a clear geographical pattern in Chubut, with low to medium occurrence probability towards the west and higher values towards the east. Guanaco population size was estimated as 657304 individuals (95% CI 457437 to 944059), with a mean density of 2.97 guanacos km–2. Finally, through simulations of guanaco monitoring, it was estimated that an annual survey effort of 10 to thirty 30-km road transects is needed to detect with confidence a significant population decrease or increase over the next 6 or 10 years. Conclusions The habitat suitability map presented herein highlights areas with high guanaco densities in Chubut, where it would be possible to identify ranches suitable for performing profitable herding and shearing experiences. Implications The maps of guanaco distribution and density, as well as the survey effort required to monitor population trends, may be used to inform decisions concerning the sustainable use of this species.

The Lesser Rhea (Rhea pennata pennata) has suffered a marked decline in numbers over recent decades, probably mainly as a result of livestock production and overhunting. Our aim was to investigate the factors that determine the distribution of Lesser Rheas in southern Patagonia and to generate a predictive regional distribution map. We surveyed 8000 km of roads and sighted 795 Lesser Rhea individuals or flocks. We also estimated environmental predictors from remotely sensed data and analysed the occurrence of Lesser Rheas in relation to these predictors. The predictors we examined were associated with four hypotheses explaining the distribution of Lesser Rheas: the persecution by ranchers, primary productivity, topography, and anthropogenic disturbance hypotheses. We built models for each hypothesis. Our results suggest that the distribution of Lesser Rheas is not negatively affected by persecution by ranchers, as the species is more abundant in areas with high stocking levels of sheep, but is positively influenced by primary productivity and negatively by the proximity of human habitation. The resulting distribution map can be used as a management tool for government agencies and highlights the conservation priorities for managing this declining and emblematic species. ; Peer reviewed

We test the use of hyperspectral sensors for the early detection of the invasive dense-flowered cordgrass ( Spartina densiflora Brongn.) in the Guadalquivir River marshes, Southwestern Spain. We flew in tandem a CASI-1500 (368–1052 nm) and an AHS (430–13,000 nm) airborne sensors in an area with presence of S. densiflora . We simplified the processing of hyperspectral data (no atmospheric correction and no data-reduction techniques) to test if these treatments were necessary for accurate S. densiflora detection in the area. We tested several statistical signal detection algorithms implemented in ENVI software as spectral target detection techniques (matched filtering, constrained energy minimization, orthogonal subspace projection, target-constrained interference minimized filter, and adaptive coherence estimator) and compared them to the well-known spectral angle mapper, using spectra extracted from ground-truth locations in the images. The target S. densiflora was easy to detect in the marshes by all algorithms in images of both sensors. The best methods (adaptive coherence estimator and target-constrained interference minimized filter) on the best sensor (AHS) produced 100% discrimination (Kappa = 1, AUC = 1) at the study site and only some decline in performance when extrapolated to a new nearby area. AHS outperformed CASI in spite of having a coarser spatial resolution (4-m vs. 1-m) and lower spectral resolution in the visible and near-infrared range, but had a better signal to noise ratio. The larger spectral range of AHS in the short-wave and thermal infrared was of no particular advantage. Our conclusions are that it is possible to use hyperspectral sensors to map the early spread S. densiflora in the Guadalquivir River marshes. AHS is the most suitable airborne hyperspectral sensor for this task and the signal processing techniques target-constrained interference minimized filter (TCIMF) and adaptive coherence estimator (ACE) are the best performing target detection techniques that can be employed operationally with a simplified processing of hyperspectral images. ; This study has been funded by the Spanish Ministry of Science and Innovation through the research projects HYDRA (No. CGL2006-02247/BOS) and HYDRA2 (CGL2009-09801/BOS), by the National Parks Authority (Organismo Autonomo de Parques Nacionales) of the Spanish Ministry of Environment to project OAPN 042/2007, and by funding from the European Union (EU) Horizon 2020 research and innovation program under grant agreement No. 641762 to ECOPOTENTIAL project. The Espacio Natural de Doñana provided permits for field work in protected areas with restricted access. We are grateful to the Instituto Nacional de Técnica Aeroespacial (INTA), Spain, for performing the airborne campaign and the geometric correction of the images. J.B. has to acknowledge a sabbatical stay at Pye Laboratory of the Commonwealth Scientific and Research Organization (CSIRO) Marine and Atmospheric Sciences, Australia, and at the Climate Change Cluster (C3) of the University of Technology Sydney, Australia, funded by the Spanish Ministry of Education, during data analysis and writing of this paper. This publication is a contribution from CEIMAR and also a contribution from CEICAMBIO. We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI)

We test the use of hyperspectral sensors for the early detection of the invasive denseflowered cordgrass (Spartina densiflora Brongn.) in the Guadalquivir River marshes, Southwestern Spain. We flew in tandem a CASI-1500 (368–1052 nm) and an AHS (430–13,000 nm) airborne sensors in an area with presence of S. densiflora. We simplified the processing of hyperspectral data (no atmospheric correction and no data-reduction techniques) to test if these treatments were necessary for accurate S. densiflora detection in the area. We tested several statistical signal detection algorithms implemented in ENVI software as spectral target detection techniques (matched filtering, constrained energy minimization, orthogonal subspace projection, target-constrained interference minimized filter, and adaptive coherence estimator) and compared them to the well-known spectral angle mapper, using spectra extracted from ground-truth locations in the images. The target S. densiflora was easy to detect in the marshes by all algorithms in images of both sensors. The best methods (adaptive coherence estimator and target-constrained interference minimized filter) on the best sensor (AHS) produced 100% discrimination (Kappa = 1, AUC = 1) at the study site and only some decline in performance when extrapolated to a new nearby area. AHS outperformed CASI in spite of having a coarser spatial resolution (4-m vs. 1-m) and lower spectral resolution in the visible and near-infrared range, but had a better signal to noise ratio. The larger spectral range of AHS in the short-wave and thermal infrared was of no particular advantage. Our conclusions are that it is possible to use hyperspectral sensors to map the early spread S. densiflora in the Guadalquivir River marshes. AHS is the most suitable airborne hyperspectral sensor for this task and the signal processing techniques target-constrained interference minimized filter (TCIMF) and adaptive coherence estimator (ACE) are the best performing target detection techniques that can be employed operationally with a simplified processing of hyperspectral images. ; This study has been funded by the Spanish Ministry of Science and Innovation through the research projects HYDRA (No. CGL2006-02247/BOS) and HYDRA2 (CGL2009-09801/BOS), by the National Parks Authority (Organismo Autonomo de Parques Nacionales) of the Spanish Ministry of Environment to project OAPN 042/2007, and by funding from the European Union (EU) Horizon 2020 research and innovation program under grant agreement No. 641762 to ECOPOTENTIAL project. The Espacio Natural de Donana provided permits for field work in protected areas with restricted access. We are grateful to the Instituto Nacional de Tecnica Aeroespacial (INTA), Spain, for performing the airborne campaign and the geometric correction of the images. J.B. has to acknowledge a sabbatical stay at Pye Laboratory of the Commonwealth Scientific and Research Organization (CSIRO) Marine and Atmospheric Sciences, Australia, and at the Climate Change Cluster (C3) of the University of Technology Sydney, Australia, funded by the Spanish Ministry of Education, during data analysis and writing of this paper. This publication is a contribution from CEIMAR and also a contribution from CEICAMBIO.

Many of the world's wetlands may be profoundly affected by climate change over the coming decades. Although wetland managers may have little control over the causes of climate change, they can help to counteract its effects through local measures. This is because direct anthropogenic impacts, such as water extraction and nutrient loading, work in concert with climate change to damage wetlands. Control of these local stressors may therefore ameliorate undesired effects of climate change, such as a shift towards dominance by invasive floating plants, increasingly frequent cyanobacteria blooms, or extinction of key species. Using the iconic Doñana wetlands in Spain as a case study, we illustrate how the concept of creating a "safe operating space" may be implemented to better ensure that ecosystems do not surpass thresholds for collapse during an era of global change. ; WIMEK grant for a research stay at WUR. JAE DOCTORES. European Union. European Social Fund. Grant Number: ESF2007‐2013. Spanish Ministry for Economy and Competitiveness. EU FP7 project FAST. Grant Number: 607131. European Union's Horizon 2020 research and innovation program. Grant Number: 641762 ; Peer reviewed

Many of the world's wetlands may be profoundly affected by climate change over the coming decades. Although wetland managers may have little control over the causes of climate change, they can help to counteract its effects through local measures. This is because direct anthropogenic impacts, such as water extraction and nutrient loading, work in concert with climate change to damage wetlands. Control of these local stressors may therefore ameliorate undesired effects of climate change, such as a shift towards dominance by invasive floating plants, increasingly frequent cyanobacteria blooms, or extinction of key species. Using the iconic Doñana wetlands in Spain as a case study, we illustrate how the concept of creating a "safe operating space" may be implemented to better ensure that ecosystems do not surpass thresholds for collapse during an era of global change. ; AJG was supported by a WIMEK grant for a research stay at WUR. EPM was supported by a JAE DOCTORES 2010 contract funded by the European Union (European Social Fund, ESF2007-­2013) and the Spanish Ministry for Economy and Competitiveness, as well as the EU FP7 project FAST (grant 607131). Funding was also provided by the European Union's Horizon 2020 research and innovation program under grant agreement number 641762 to the ECOPOTENTIAL project. C Perennou provided helpful comments on earlier versions of the manuscript. Maps were made using data from CHG­ uadalquivir (www.chguadalquivir.es/ide) with QGIS (www.qgis.org) and the Google Maps API. ; PDF 9 pages