Indicator macroinvertebrate species in a temporary Mediterranean river: Recognition of patterns in binary assemblage data with a Kohonen artificial neural network

Sroczyńska, Katarzyna; Claro, Marilia; Kruk, Andrzej; Wojtal-Frankiewicz, Adrianna; Range, Pedro; Chı́charo, Luis

doi:10.1016/j.ecolind.2016.09.010

Cited by 7 publications

(9 citation statements)

References 77 publications

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“…In the relatively clean areas (cluster II and III), sites in different seasons were grouped into different neurons. This seasonal pattern overlapped with the spatial zonation pattern, which was consistent with Sroczyńska et al (2017) for a temporary Mediterranean river.…”

Section: Community Patterning and The Environmental Predictorssupporting

confidence: 83%

“…Substrate is very important to macroinvertebrates (Connolly and Pearson, 2007;Sroczyńska et al, 2017). However, in this case it showed intermediate influence for the community classification.…”

Section: Community Patterning and The Environmental Predictorsmentioning

confidence: 92%

“…As mentioned above, family level was used to identify the indicators. It was considered satisfactory to characterize the ecological status because investigations at the species level at large spatial scales are particularly costly (Heino et al, 2002;Rosenberg and Resh, 1993;Sroczyńska et al, 2017). In this regard, some researcher compared the taxonomic resolution's influence to macroinvertebrate community patterning and found that only little information (<6%) was lost using family level, as opposed to species level.…”

Section: Family Indicators and The Relationships With The Environmentmentioning

confidence: 99%

“…Nevertheless, each ordination technique may have important limitations and assumptions that are incompatible with the over-dispersion and nonlinear nature of ecological data (Paliy and Shankar, 2016). Researchers have advocated for the use of a type of unsupervised artificial neural network called Kohonen Self-Organizing Maps (SOMs) (Kohonen, 1982), which have been demonstrated to be particularly competent in analyses such as macroinvertebrate community delineations (Chon, 2011;Park et al, 2007;Kim et al, 2013;Sroczyńska et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Determining the macroinvertebrate community indicators and relevant environmental predictors of the Hun-Tai River Basin (Northeast China): A study based on community patterning

Zhang

Muñoz‐Mas

Martínez‐Capel

et al. 2018

Science of The Total Environment

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It is essential to understand the patterning of biota and environmental influencing factors for proper rehabilitation and management at the river basin scale. The Hun-Tai River Basin was extensively sampled four times for macroinvertebrate community and environmental variables during one year. Self-Organizing Maps (SOMs) were used to reveal the aggregation patterns of the 355 samples. Three community types (i.e., clusters) were found (at the family level) based on the community composition, which showed a clearly gradient by combining them with the representative environmental variables: minimally impacted source area, intermediately anthropogenic impacted sites, and highly anthropogenic impacted downstream area, respectively. This gradient was corroborated by the decreasing trends in density and diversity of macroinvertebrates. Distance from source, total phosphorus and water temperature were identified as the most important variables that distinguished the delineated communities. In addition, the sampling season, substrate type, pH and the percentage of grassland were also identified as relevant variables. These results demonstrated that macroinvertebrates communities are structured in a hierarchical manner where geographic and water quality prevail over temporal (season) and habitat (substrate type) features at the basin scale. In addition, it implied that the local-scale environment variables affected macroinvertebrates under the longitudinal gradient of the geographical and anthropogenic pressure. More than one family was identified as the indicator for each type of community. Abundance contributed significantly for distinguishing the indicators, while Baetidae with higher density indicated minimally and intermediately impacted area and lower density indicated highly impacted area. Therefore, we suggested the use of abundance data in community patterning and classification, especially in the identification of the indicator taxa.

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Section: Community Patterning and The Environmental Predictorssupporting

confidence: 83%

Section: Community Patterning and The Environmental Predictorsmentioning

confidence: 92%

Section: Family Indicators and The Relationships With The Environmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Determining the macroinvertebrate community indicators and relevant environmental predictors of the Hun-Tai River Basin (Northeast China): A study based on community patterning

Zhang

Muñoz‐Mas

Martínez‐Capel

et al. 2018

Science of The Total Environment

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show abstract

“…In addition, they motivate the implementation of integrated water management policies [7,9]. At present, new indices are being generated on the basis of bioindicators using computational methods in order to reduce the intrinsic and subjective uncertainties of environmental problems [10]. However, in order to provide information on the historical state of a body of water and not only on the moment of sampling, multimetric indices have been developed based on communities of macroinvertebrates and benthic algae.…”

mentioning

confidence: 99%

Behavior of Physicochemical Parameters and Potentially Toxic Metals in Surface Water Evaluated by Means of Multimetric Indices: a Case Study in a Protected Natural Area of Peru

Custodio¹,

Chirinos²,

Peñaloza³

2020

Pol. J. Environ. Stud.

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Livelihoods in developing countries depend largely on intact and functioning wetlands. Water permanence and quality have been identified as factors affecting the structure and composition of biological communities, such as macroinvertebrates and benthic algae [1, 2]. The natural variability of these communities in wetlands faces challenges because of the severe anthropogenic impacts that are being generated in both their structure and the services they provide (groundwater recharge, flood water retention, lotic-based flow contributions, biogeochemical processing, water quality improvement, and wildlife habitat) [2, 4], which is leading to its degradation on both local and global scales [5, 6]. Global wetland studies have revealed a significant decline of 6% in just 14 years (1993-2007) due to

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Food web structure of three Mediterranean stream reaches along a gradient of anthropogenic impact

et al. 2020

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Anthropogenic impact can alter food web structure through changes in species interactions. In this study, we explored the food web of three Mediterranean stream reaches (two seasonal and one permanent) along an anthropogenic impact gradient to test the hypothesis that increasing impact simplifies food webs. To test this, we applied the isotopic (d 13 C and d 15 N) niche concept to compare reaches using isotopic metrics (isotopic richness, divergence, dispersion, evenness, and redundancy). The isotopic indices were useful to identify differences in food web architecture among the three reaches. The least impacted site had the highest isotopic richness, dispersion, and isotopic redundancy, suggesting higher ecological resilience at this site. The effect of disturbance in the remaining two sites was masked by the presence of invasive crayfish, which increased isotopic divergence and was responsible for higher food-chain length in the most impacted reach, but not in the moderately impacted reach. Consumers displayed generalistic feeding habits, with Bayesian mixing models indicating that they relied primarily on a mixture of periphyton, other macroinvertebrates, and to a lesser extent, detritus. Some taxa displayed Handling editor: Marı ´a del Mar Sa ´nchez-Montoya

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Indicator macroinvertebrate species in a temporary Mediterranean river: Recognition of patterns in binary assemblage data with a Kohonen artificial neural network

Cited by 7 publications

References 77 publications

Determining the macroinvertebrate community indicators and relevant environmental predictors of the Hun-Tai River Basin (Northeast China): A study based on community patterning

Determining the macroinvertebrate community indicators and relevant environmental predictors of the Hun-Tai River Basin (Northeast China): A study based on community patterning

Behavior of Physicochemical Parameters and Potentially Toxic Metals in Surface Water Evaluated by Means of Multimetric Indices: a Case Study in a Protected Natural Area of Peru

Food web structure of three Mediterranean stream reaches along a gradient of anthropogenic impact

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