Two faces of agricultural intensification hanging over aquatic biodiversity: The case of chironomid diversity from farm ponds vs. natural wetlands in a coastal region

Fenoy, Encarnación; Casas, J. Jesús

doi:10.1016/j.ecss.2015.03.003

Cited by 5 publications

(2 citation statements)

References 59 publications

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“…Chironomids also respond sensitively to changes in land use, including urbanization, agriculture, deforestation, and subsequent nutrient enrichment (Campbell et al., 2009 ; Fenoy & Casas, 2015 ; Francis & Foster, 2001 ). These activities can have significant impacts on the water quality and habitat conditions.…”

Section: Introductionmentioning

confidence: 99%

Diversity and distribution of chironomids in Central European ponds

Přidalová,

Hamerlík,

Novikmec

et al. 2024

Ecology and Evolution

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Ponds are common freshwater habitats in the European landscape that substantially contribute to local and regional biodiversity. Chironomids often dominate invertebrate communities in ponds but are usually disregarded in ecological studies due to relatively complicated taxonomy and identification issues. We present a comprehensive overview of the chironomid diversity in 246 ponds spanning a wide range of conditions extending from the Pannonian Plain to the Carpathians. Altogether, we recorded 225 taxa including 192 species from six subfamilies (Podonominae, Tanypodinae, Diamesinae, Prodiamesinae, Orthocladiinae and Chironominae). However, the chironomid taxa inventory is far from complete and about 16% of the total diversity of pond‐dwelling chironomids remains undetected. Chironomid alpha diversity showed a significant unimodal pattern along the elevation gradient with the highest number of taxa per pond expected around 790 m a.s.l. Gamma diversity also peaked in mid‐elevations (600–800 m), and the common chironomid taxa partitioned the 2100‐m long altitudinal gradient relatively evenly. The heterogeneity of chironomid communities among ponds measured as beta diversity was significantly higher in elevations below 800 m. Temperature and the proportion of surrounding forests significantly influenced alpha diversity of chironomid communities, while urban land cover and pond size had no significant effect. Ponds with a mean annual air temperature of approximately 4.8°C and a low proportion of surrounding forests are expected to harbour the most diverse chironomid communities. Our study showed that chironomids represent a very diverse and often exceptionally rich group of pond‐dwelling macroinvertebrates. Given the high diversity and broad range of occupied niches, chironomids should not be overlooked in pond ecology studies. On the contrary, they should be considered a potential model group.

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Section: Introductionmentioning

confidence: 99%

Diversity and distribution of chironomids in Central European ponds

Přidalová,

Hamerlík,

Novikmec

et al. 2024

Ecology and Evolution

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“…The coastal aquaculture industry has been one of the most dynamic growth sectors over the past 20 years for reasons such as addressing employment, developing the economy, and eradicating poverty [5,6]. Expansion of aquaculture ponds has been found along the coastline worldwide [7][8][9][10][11][12][13][14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Improving Satellite Retrieval of Coastal Aquaculture Pond by Adding Water Quality Parameters

et al. 2022

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Coastal aquaculture is an important supply of animal proteins for human consumption, which is expanding globally. Meanwhile, extensive aquaculture may increase nutrient loadings and environmental concerns along the coast. Accurate information on aquaculture pond location is essential for coastal management. Traditional methods use morphological parameters to characterize the geometry of surface waters to differentiate artificially constructed conventional aquaculture ponds from other water bodies. However, there are other water bodies with similar morphology (e.g., saltworks, rice fields, and small reservoirs) that are difficult to distinguish from aquaculture ponds, causing a lot of omission/commissioning errors in areas with complex land-use types. Here, we develop an extraction method with shape and water quality parameters to map aquaculture ponds, including three steps: (1) Sharpen normalized difference water index to detect and binarize water pixels by the Otsu method; (2) Connect independent water pixels into water objects through the four-neighbor connectivity algorithm; and (3) Calculate the shape features and water quality features of water objects and input them into the classifier for supervised classification. We selected eight sites along the coast of China to evaluate the accuracy and generalization of our method in an environment with heterogeneous pond morphology and landscape. The results showed that six transfer characteristics including water quality characteristics improved the accuracy of distinguishing aquaculture ponds from salt pans, rice fields, and wetland parks, which typically had F1 scores > 85%. Our method significantly improved extraction efficiency on average, especially when aquaculture ponds are mixed with other morphological similar water bodies. Our identified area was in agreement with statistics data of 12 coastal provinces in China. In addition, our approach can effectively improve water objects when high-resolution remote sensing images are unavailable. This work was applied to open-source remote sensing imagery and has the potential to extract long-term series and large-scale aquaculture ponds globally.

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