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Karisa, J.

Publications and source records attributed to Karisa, J..

2 recordsLinked to original sources

Leveraging the Red List of Ecosystems for national action on coral reefs through the Kunming-Montreal Global Biodiversity Framework

Countries have committed to conserving and restoring ecosystems after signing the Kunming-Montreal Global Biodiversity Framework (GBF). The IUCN Red List of Ecosystems (RLE) will serve as a headline indicator to track progress of countries towards achieving this goal, and to guide action across the GBFs targets. Using Kenyan coral reefs, we demonstrate how nations implementing the GBF, can use standardised estimates of ecosystem degradation from RLE assessments to support site-specific management decisions. We undertook a reef-by-reef analysis to evaluate the relative severity of decline of four key ecosystem components over the past 50-years: hard corals, macroalgae, parrotfish and groupers. Using the two benthic indicators, we also calculated standardised estimates of state to identify reef sites which maintain a better condition through time relative to adjacent sites. Over the past 50 years, Kenyas coral reefs have degraded across all four ecosystem components. At more than half the monitored sites both parrotfish and grouper abundance declined by more than 50%, while coral cover and macroalgae-coral ratio declined by at least 30%. This resulted in a Vulnerable threat status for coral reefs in Kenya based on degradation (under criterion D of the RLE). The temporal trends in coral cover revealed four sites which maintained an above average condition over their monitoring history (15-25 years). The results can guide management actions to contribute to at least nine of the 23 GBF targets. For example, we identified several sites with relatively healthy benthic and fish communities as candidate areas for protection measures under Target 3. We also found that Marine Protected Areas and Locally Managed Marine Areas, which restrict fishing and control gears, had lower declines in groupers compared to unmanaged areas, providing further evidence for their expansion. The RLE has a key role to play in monitoring and meeting the goals and targets of the Global Biodiversity Framework, and our work demonstrates how using the wealth of data within these assessments can inform local-scale ecosystem management and amplify the GBFs impact.

ecology↗

Evaluation of near infrared spectroscopy for sporozoite detection in mosquitoes infected with wild-strain parasites from asymptomatic gametocyte carriers in Kilifi Kenya

BackgroundScreening for Plasmodium spp. sporozoite infection in mosquitoes is routinely done using ELISA (enzyme-linked immunosorbent assay). Near infrared spectroscopy (NIRS), a fast and non-destructive method, has recently been shown to distinguish, with 95% accuracy, between uninfected and sporozoite-infected mosquitoes using laboratory strains of Plasmodium falciparum (PfN54). The aim of this present study was to further investigate the reproducibility of NIRS to identify sporozoite infection in mosquitoes infected using field isolates of P. falciparum gametocytes from asymptomatic carriers. MethodsHealthy individuals (aged 5 years and above) were screened for gametocytaemia by thick-smear microscopy in an area of moderate transmission along the Coast of Kenya between May and September 2018. Asymptomatic gametocyte carriers were recruited for mosquito feeding assays, direct membrane feeding (DMFA) and direct skin feeding (DFA), using insectary-reared Anopheles gambiae s.s (Kilifi strain). Mosquitoes were kept for 14-days post feeding after which they were scanned using NIRS and subsequently analysed for sporozoite infection using circumsporozoite-ELISA. Predictive models were explored using partial least square regressions (PLS). ResultsTwo hundred and ninety-nine (299) individuals were screened for malaria parasites, 74 (24.8%) were found with circulating asexual parasites, and 16 (5.4%) with P. falciparum gametocyte stages. Fourteen (14) asymptomatic gametocyte carriers were recruited to the study for mosquito feeding assays. A total of 134 (7%, 134/1881) sporozoite-infected mosquitoes were obtained from 9 successful experiments. Three different training datasets composed of infected and uninfected mosquitoes were analysed. The PLS models were unable to distinguish between sporozoite-infected and uninfected mosquitoes. A predictive model could not be generated. ConclusionsThe results of this study were not consistent with previous published research on NIRS for detection of sporozoite infection in the same mosquito species and may reflect differences between laboratory and field conditions. The current findings indicate that methods for sporozoite detection should be tested on field isolates at an early stage in their development and are informative for future research seeking novel high-throughput methods for parasite detection in mosquitoes.

zoology↗