The ecological role of mosquito larvae in aquatic environments

The ecological role of mosquito larvae in aquatic environments

The ecological role of mosquito larvae in aquatic environments

Assessing the community role and trophic interactions of Anopheles gambiae larvae in the Volta Region of Ghana.

IMAGE CREDIT: Michelle L. D’Souza

 The Anopheles gambiae mosquito complex, which consists of eight species, is the prevalent malaria vector in Sub-Saharan Africa1. While we have a reasonable understanding of predation rates, resource availability, and competition among aquatic invertebrate2-7, we lack a comprehensive appreciation of the larval ecology of An. gambiae, including their trophic role, diets, and population dynamics. My research aims to address this gap, crucial in integrating aquatic habitat management with vector control programs8.

With the advance of DNA technologies such as metabarcoding, we can now identify prey to a species level by examining the stomach contents of aquatic predators. When using these insights with network analyses, it is possible to quantify direct and indirect ecological interactions in the environment9. I will take advantage of these techniques for my research which aims to assess the trophic interactions of An. gambiae larvae in water bodies within two agricultural communities in Ghana.

I will collect mosquito larvae with a dipper, and a larger subset of invertebrates with an aquatic net (with a mesh size of 250 μm).  Each specimen’s gut contents will be analyzed using DNA barcoding and this data will be used to gain an understanding of the larval niche and ultimately An. gambiae’s role within the aquatic community. I will examine network interaction metrics such as connectance (the number of realized connections between species relative to what is available), degree (the number of interaction partners), betweenness (the importance of a species as a connector between different groups), and closeness (how central a focal species is in the community) to aid in niche construction. Temperature, pH, dissolved oxygen, salinity, and conductivity of the target water bodies will also be measured while sampling as these factors affect the occurrence and abundance of larvae by influencing the breeding behaviours of mosquitoes10.

In addition, I plan to study how different species of mosquito larvae compete for key resources. In the laboratory, the densities of local-caught larval populations of An. gambiae and other mosquito species will be manipulated to help determine the strongest competitor. While maintaining optimal rearing conditions by measuring the physio-chemical properties of the water daily, I will examine four indicators of overall growth and survival (the mean time to pupation, percentage of larvae that did not reach the adult stage, sex ratio, and mean female wing length) and therefore infer competitive strength among species. These data will provide important insights into predicting whether another mosquito species would dominate if the number of An. gambiae is reduced in the habitat.

An. gambiae is relatively small, constituting about half to one-third the mass of many Aedes mosquito species12. Foraging theory indicates that small, mobile insects of low profitability, do not form a preferred food source to predators unless they are massively clustered13. Though many species feed on mosquitos, these animals also feed on other small organisms that typically co-occur with An. gambiae14. For these reasons, I do not foresee that An. gambiae larvae will be a key food source for any predator in the aquatic environments in Ghana or that they will have a central role in local trophic systems.

If this is proven to be true, it will provide evidence that malaria-intervention methods that aim to suppress or reduce An. gambiae mosquitoes will not have detrimental consequences for the larger community.

Written by

Afia S. Karikari

Afia S. Karikari

African Regional Postgraduate Programme in Insect Science, University of Ghana, Accra, Ghana  

April 21, 2021

doi:10.21083/ibol.v11i1.6619 

This research is part of a larger effort by Target Malaria in Ghana to understand the role of the An. gambiae mosquito in the broader ecosystem.

For more information see:

The important interactions behind the itch

References:

  1. Service MW (1971) Studies on sampling larval populations of the Anopheles gambiae Bulletin of the World Health Organization 45:169–180.
  2. Service MW (1973) Mortalities of the larvae of the Anopheles gambiae Giles complex and detection of predators by the precipitin test. Bulletin of Entomological Research 62:359– 369.
  3. Service MW (1977) Mortalities of the immature stages of species of the Anopheles gambiae complex in Kenya: comparison between rice fields and temporary pools, identification of predators, and effects of insecticidal spraying. Journal of Medical Entomology 13:535–545.
  4. Ho BC, Ewert A, Chew LM (1989) Interspecific competition among Aedes Aegypti, albopictus and Ae. triseriatus (Diptera: Culicidae). Journal of Medical Entomology. 26:615–623.
  5. Barrera L (1996) Competition and resistance to starvation in larvae of container-inhabiting Aedes mosquitos. Ecological Entomology 21:117–127.
  6. Juliano SA, Lounibos LP and O’Meara GF (2004) A field test for competitive effects of Aedes albopictus on aegypti in south Florida: differences between sites and co-existence and exclusion? Oecologia. 139:583–593.
  7. Braks MAH, Honόrio NA, Lounibos LP, Lourenςo-de-Oliveira R, Juliano SA (2004) Interspecific competition between two invasive species of container mosquitos, Aedes aegypti and Aedes albopictus (Diptera: Culicidae), in Brazil. Annual Entomological Society of America 97:130–139.
  8. Li L, Bian L, Yakob L, Zhou U, Yan G (2009) Temporal and spatial stability of Anopheles gambiaelarval habitat distribution in western Kenya highlands. International Journal of Health Geographics. 8(70). doi:10.1186/1476-072X-8-70
  9. Fath BD, Patten BC (1998) Network synergism: emergence of positive relations in ecological systems. Ecological Modelling 107:127–143.
  10. Clements AN (1992) The Biology of Mosquitoes (Vol 1) Development, Nutrition and Reproduction. Chapman and Hall, London.
  11. Paajimans KP, Huijben S, Githeko AK, Takken W (2009) Competitive interactions between larvae of the malaria mosquitos, Anopheles arabiensis and Anopheles gambiae under semi-field conditions in western Kenya. Acta Tropica. 109:124–
  12. Koella JC, Lyimo EO (1996) Variability in the relationship between weight and wing length of Anopheles gambiae (Diptera: Culicidae). Journal of Medical Entomology 33: 261–264.
  13. Stephens DW, Brown JS, Ydenberg RC (2007) Foraging: Behavior and Ecology. University of Chicago Press, Chicago, IL.
  14. Findley JS, Black H (1983) Morphological and dietary structuring of a Zambian insectivorous bat community. Ecology 64:625–630.

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Discovering a resilient and hyperdiverse midge fly fauna in a Singaporean swamp forest

Discovering a resilient and hyperdiverse midge fly fauna in a Singaporean swamp forest

Discovering a resilient and hyperdiverse midge fly fauna in a Singaporean swamp forest

Researchers uncover a highly unique and diverse chironomid community in a Singaporean swamp forest highlighting the importance of these ecosystems and the power of Next-Generation Sequencing for biomonitoring efforts.

Nee Soon Swamp Forest, Singapore

PHOTO CREDIT: Wang Luan Keng

Benthic macroinvertebrates – those animals that live at the bottoms of water bodies – are abundant, diverse, relatively immobile, and responsive to environmental stresses, and these traits make them ideal indicators of the quality of aquatic ecosystems. Our study demonstrates the utility of Next-Generation Sequencing (NGS) platforms as an efficient and rapid tool for monitoring efforts.

In freshwater ecosystems, non-biting midges (Diptera: Chironomidae) often constitute the majority of diversity and biomass with different chironomid species varying in their sensitivity to environmental changes. But, when monitoring these habitats, chironomids are either ignored entirely or not studied at a species-level because morphological assessments are expensive and laborious, and the identification literature is based on adults while larvae are most often collected.

Chironomid adults collected from Nee Soon Swamp Forest. Different chironomid species vary in their sensitivity to environmental parameters. PHOTO CREDIT: Bilgenur Baloglu
The solution? NGS platforms. They allow for fast and effective species-level assessments of large-scale samples at low cost (less than $0.40 USD/specimen). Moreover, there is a high congruence between molecular and morphological identification, enabling a detailed examination of the composition of taxonomically complex communities1,2. Freshwater swamp forests – the forested wetlands occurring along rivers and lakes – are home to various endemic and endangered species with 33% of birds and 45% of mammals either threatened or endangered on the IUCN Red List3, and with most of the insect fauna unknown. These ecosystems are under threat worldwide from habitat destruction, pollution, and climate crisis. Most of the world’s tropical swamp forests are found in Southeast Asia’s Indo-Malayan region collectively occupying more than 13 million ha4 among many geographically separated peninsulas and islands. Nee Soon swamp forest is the largest remnant (90 ha) of its kind in Singapore and thus of high national conservation value.

Bilge Baloglu sampling water DNA from Singapore’s largest swamp forest remnant.
PHOTO CREDIT: Dickson Ng

We generated DNA barcodes using NGS to study chironomids among the natural swamp forest Nee Soon and three adjacent man-made reservoirs. We wanted to understand the effects of urbanization and to know whether the chironomid fauna of Nee Soon is resistant to, that is, minimally impacted by, the adjacent reservoirs. We sampled >14,000 chironomid specimens (both adults and larvae) as part of a freshwater quality monitoring program, and quantified species richness and compositional changes using NGS and DNA barcoding.

Our study showed that Singapore’s biggest swamp forest remnant maintains a rich and largely unique fauna of about 350 species. The minimal species overlap between sites indicated that the Nee Soon swamp forest is resistant against the invasion of species from surrounding artificial reservoirs. 

These findings suggest that even small or fragmented swamp forests can be suitable habitats for chironomids, shedding light on many other swamp forests in Southeast Asia that collectively occupy a much larger area and that are threatened by destruction for oil palm plantations and paper pulp production. Overall, our study exposes the enormous power of NGS and DNA barcoding in ecological research to study ecosystem health, biological diversity, and habitat conservation.

References:

1. Brodin Y, Ejdung G, Strandberg J, Lyrholm T (2013) Improving environmental and biodiversity monitoring in the Baltic Sea using DNA barcoding of Chironomidae (Diptera). Molecular Ecology Resources 13:996–1004.

2. Montagna M, Mereghetti V, Lencioni V, Rossaro B (2016) Integrated taxonomy and DNA barcoding of alpine midges (Diptera: Chironomidae). PLoS One 11:e0149673

3. Posa MR (2011) Peat swamp forest avifauna of Central Kalimantan, Indonesia: Effects of habitat loss and degradation. Biological Conservation 144(10):2548-2556.

4. Hooijer A, Page S, Canadell JG, Silvius M, Kwadijk J, Wösten H, Jauhiainen J (2010) Current and future CO2 emissions from drained peatlands in Southeast Asia. Biogeosciences 7:1505–1514

For full details, please refer to the publication in Frontiers in Zoology.

Written by

Bilgenur Baloğlu

Bilgenur Baloğlu

Centre for Biodiversity Genomics, Guelph, ON, Canada

September 6, 2019
doi: 10.21083/ibol.v9i1.5525

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