Functional redundancy as a tool for bioassessment: A test using riparian vegetation.
There is an urgent need to track how natural systems are responding to global change in order to better guide management efforts. Traditionally, taxonomically based metrics have been used as indicators of ecosystem integrity and conservation status. However, functional approaches offer promising advantages that can improve bioassessment performance. In this study, we aim to test the applicability of functional redundancy (FR), a functional feature related to the stability, resistance and resilience of ecosystems, as a tool for bioassessment, looking at woody riparian communities in particular. We used linear mixed-effect models to investigate the response of FR and other traditional biomonitoring indices to natural (drought duration) and anthropogenic stress gradients (flow regulation and agriculture) in a Mediterranean basin. Such indices include species richness, a taxonomic index, and the Riparian Quality Index, which is an index of ecological status. Then, we explored the ability of FR and the other indices to discriminate between different intensities of human alteration. FR showed higher explanatory capacity in response to multiple stressors, although we found significant negative relationships between all the biological indices (taxonomic, functional and ecological quality) and stress gradients. In addition, FR was the most accurate index to discriminate among different categories of human alteration in both perennial and intermittent river reaches, which allowed us to set threshold values to identify undisturbed (reference condition), moderately disturbed and highly disturbed reaches in the two types of river. Using these thresholds and the best-fitting model, we generated a map of human impact on the functional redundancy of riparian communities for all the stretches of the river network. Our results demonstrate that FR presents clear advantages over traditional methods, which suggests that it should be part of the biomonitoring toolbox used for environmental management so as to obtain better predictions of ecosystem response to environmental changes.
Departamento de Ecología e Hidrología, Universidad de Murcia, Facultad de Biología, Campus de Excelencia Internacional Regional 'Campus Mare Nostrum', 30100 Murcia, Spain. Electronic address: dbrunocollados@um.es.
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Bruno
Departamento de Ecología e Hidrología, Universidad de Murcia, Facultad de Biología, Campus de Excelencia Internacional Regional 'Campus Mare Nostrum', 30100 Murcia, Spain; Catchment Research Group, Cardiff University, School of Biosciences, The Sir Martin Evans Building, Museum Avenue, Cardiff CF10 3AX, UK.
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Gutiérrez-Cánovas
Departamento de Ecología e Hidrología, Universidad de Murcia, Facultad de Biología, Campus de Excelencia Internacional Regional 'Campus Mare Nostrum', 30100 Murcia, Spain.
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Velasco
Departamento de Ecología de Humedales, Estación Biológica de Doñana (CSIC), C/ Americo Vespucio, s/n, 41092, Isla de la Cartuja, Sevilla, Spain; Instituto de Ciencias Ambientales, Universidad de Castilla-La Mancha, Campus Tecnológico de la Fábrica de Armas, Toledo 45071, Spain.
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Sánchez-Fernández
D058448:Biota; D003247:Conservation of Natural Resources / Q000379:methods*; D017753:Ecosystem; D004784:Environmental Monitoring / Q000379:methods*; D016014:Linear Models; D008954:Models, Biological; D010944:Plants / Q000145:classification; D013030:Spain
Biomonitoring; Drought; Ecological indicators; Functional traits; Human impact; Mediterranean rivers