Seguimiento de aves acuáticas amenazadas en lagunas de la Reserva de la Biosfera de La Mancha Húmeda (España Central)

Gosálvez, Rafael U.; Gil‐Delgado, José A.; Vives-Ferrándiz, Carmen; Sánchez, Gema María Varo; Beltrán, Máximo Florín

doi:10.18002/pol.v0i22.101

Cited by 7 publications

(10 citation statements)

References 2 publications

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“…Climate in this area shows a pronounced dry season with average annual rainfall of 400-500 mm [29]. Sediments of the studied area are of continental nature; the terrain is flat; and the dominant lithology is limestone [2]. In brackets, the lake identification number (from Figure 1); * 2 source: Guadiana River Basin Administration (http://www.chguadiana.es/); +, these lakes receive treated wastewater inputs that artificially increase the water supply.…”

Section: Study Areamentioning

confidence: 97%

Monitoring Hydrological Patterns of Temporary Lakes Using Remote Sensing and Machine Learning Models: Case Study of La Mancha Húmeda Biosphere Reserve in Central Spain

et al. 2016

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Abstract:The Biosphere Reserve of La Mancha Húmeda is a wetland-rich area located in central Spain. This reserve comprises a set of temporary lakes, often saline, where water level fluctuates seasonally. Water inflows come mainly from direct precipitation and runoff of small lake watersheds. Most of these lakes lack surface outlets and behave as endorheic systems, where water withdrawal is mainly due to evaporation, causing salt accumulation in the lake beds. Remote sensing was used to estimate the temporal variation of the flooded area in these lakes and their associated hydrological patterns related to the seasonality of precipitation and evapotranspiration. Landsat 7 ETM+ satellite images for the reference period 2013-2015 were jointly used with ground-truth datasets. Several inverse modeling methods, such as two-band and multispectral indices, single-band threshold, classification methods, artificial neural network, support vector machine and genetic programming, were applied to retrieve information on the variation of the flooded areas. Results were compared to ground-truth data, and the classification errors were evaluated by means of the kappa coefficient. Comparative analyses demonstrated that the genetic programming approach yielded the best results, with a kappa value of 0.98 and a total error of omission-commission of 2%. The dependence of the variations in the water-covered area on precipitation and evaporation was also investigated. The results show the potential of the tested techniques to monitor the hydrological patterns of temporary lakes in semiarid areas, which might be useful for management strategy-linked lake conservation and specifically to accomplish the goals of both the European Water Framework Directive and the Habitats Directive.

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Section: Study Areamentioning

confidence: 97%

Monitoring Hydrological Patterns of Temporary Lakes Using Remote Sensing and Machine Learning Models: Case Study of La Mancha Húmeda Biosphere Reserve in Central Spain

et al. 2016

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“…1). The MHBR is one of the most important wetland complexes of the Iberian Peninsula (Florı´n et al 1993), with a network of over 190 wetlands spread over three geographical areas-Campo de San Juan, Campo de Montiel and the Serrania de Cuenca (Gosa´lvez et al 2012), of which 50 are temporary lakes (Florı´n and Montes, 1999). The Table 1 average temperature in the region is 14°C, and the minimum temperature in extreme years can reach À20°C in winter and the maximum can rise to 42°Ci n July.…”

Section: Study Areamentioning

confidence: 99%

“…Monthly counts of Pied Avocet, Black-winged Stilt and Kentish Plover were conducted in 23 wetlands between October 2010 and February 2014. The study wetlands were selected as a representative sample of the types and conditions of lakes in the region within the framework of a previous project on the ecology of inland lakes in Central Spain (Gosa´lvez et al 2012). They cover a wide range of sizes, depths, extent of vegetation in the edges (Table 1), as well as salinity (Florı´n et al 1993).…”

Section: Bird Counts and Environmental Variablesmentioning

confidence: 99%

“…On other hand, later abundance peaks occurred synchronously in the same lakes for Pied Avocet and Black-winged Stilt (Lakes Veguilla and Pedro Mun˜oz). Lakes that receive effluents from urban wastewater treatment plants present inappropriate bio-physical conditions in late summer (Vidal et al 2013;Anza et al 2014), but display high organic productivity (Anza et al 2014) and are attractive sites to waterbirds during breeding periods (Gosa´lvez et al 2012). Unlike the other lakes that receive wastewater and present long hydroperiods, Veguilla and Pedro Mun˜oz have large concentration of emerging macrophytes on its edges, and few flat shallow areas for foraging of waders in the breeding season.…”

Section: Spatial Synchrony and Hydroperiod Effectmentioning

confidence: 99%

“…In our study, most wetlands were temporary lakes, either with or without wastewater input. In general, the vegetation surrounding lakes was predominantly halophilous and some lakes were characterized by vegetation islands dominated by Reed (Phragmites australis), Cattail (Typha dominguensis), Common Clubrush (Schoenoplectus lacustris) and Alkali-bulrush (Bolboschoenus maritimus) (Gosa´lvez et al 2012).…”

Section: Study Areamentioning

confidence: 99%

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Spatial synchrony of wader populations in inland lakes of the Iberian Peninsula

Gonçalves

Gil‐Delgado

Gosálvez

et al. 2016

Ecological Research

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Seasonal differences in drivers of species richness of waders in inland wetlands of La Mancha Húmeda Biosphere Reserve

Gonçalves

Gil‐Delgado

Gosálvez

et al. 2018

Aquatic Conservation

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Temporary inland wetlands are among the most threatened ecosystems worldwide, and recognition of the factors that determine species richness in different seasons is key for developing conservation plans for these systems. La Mancha Húmeda Biosphere Reserve in central Spain has many inland wetlands of this type, but the driving ecological processes of species richness are poorly understood. This study examines the association of landscape and local variables with species richness patterns of inland wetlands of La Mancha Húmeda Biosphere Reserve during winter and the breeding season. The number of lakes in several increasing radii was a proxy of connectivity, and maximum flooded surface and shoreline length were surrogates of the species–area relationship. Other landscape and local habitat variables, such as hydroperiod (length of inundation period), distance from human settlements, shoreline development index, vegetation surface cover, average lake depth, number of islands and surface area of islands were also analysed. Hierarchical partitioning analysis was used to evaluate the contribution of the environmental variables to explain the species richness of waders. Species richness (26 species, four threatened in Europe) had different associations with the variables during the wintering and breeding seasons. The richness of breeding and wintering species was positively associated with hydroperiod and maximum flooded surface area respectively. No variable measured was negatively associated with species richness in any season. Hydroperiod and flooded surface area are altered directly by human activities. Water extraction for irrigation reduces hydroperiod in some wetlands, whereas wastewater input extends hydroperiod in others, promoting wader concentrations in lakes flooded in summer and potentially favouring botulism outbreaks. In addition, the lack of protection and management on most of the lakes in La Mancha Húmeda Biosphere Reserve also favours encroachment of agriculture, destroying and degrading habitat for wintering and breeding waders.

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Seguimiento de aves acuáticas amenazadas en lagunas de la Reserva de la Biosfera de La Mancha Húmeda (España Central)

Cited by 7 publications

References 2 publications

Monitoring Hydrological Patterns of Temporary Lakes Using Remote Sensing and Machine Learning Models: Case Study of La Mancha Húmeda Biosphere Reserve in Central Spain

Monitoring Hydrological Patterns of Temporary Lakes Using Remote Sensing and Machine Learning Models: Case Study of La Mancha Húmeda Biosphere Reserve in Central Spain

Spatial synchrony of wader populations in inland lakes of the Iberian Peninsula

Seasonal differences in drivers of species richness of waders in inland wetlands of La Mancha Húmeda Biosphere Reserve

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