Ecological Restoration and Species Recovery in Aquatic Habitats
DOI:
https://doi.org/10.70102/AEEF/V4I2/AF260214Keywords:
Aquatic Habitat Restoration; Species Recovery; Freshwater Biodiversity; Edna Monitoring; Adaptive Management; Riparian Ecology; Water Quality.Abstract
Aquatic ecosystems are considered among the most ecologically valuable habitats on Earth that occupy only 1% of the land area, but support about 10% of global biodiversity. Nonetheless, anthropogenic activities like pollution by industries and agriculture, hydrological modification, invasive alien species, and climatic changes causing thermal stress pose a serious threat to the biodiversity in fresh, brackish, and salt-water environments. For this reason, ecological restoration and recovery programs play an important role in recovering lost biodiversity in such habitats. In this regard, this study evaluates the success of ecological restoration in different aquatic ecosystems through multiple case studies carried out at seven different types of habitats spread across Asia, Africa, North America, Europe, and Australia. The approach taken involved assessment of habitat condition, targeted ecological actions, and continuous biomonitoring of the sites for a period of 24-54 months. Environmental DNA sequencing and acoustic telemetry were used as advanced biomonitoring tools for accurate monitoring of biodiversity and recovery trends. The findings from the study shown remarkable improvements in all the study habitats after intervention. On average, fish richness has been seen to increase by 72%, while macroinvertebrate diversity was noted to improve by 67%, which demonstrates the improvement in both trophic levels and the suitability of the habitat. Significant improvements were also made in the parameters used to measure water quality, with the dissolved oxygen concentration increasing from 42 to 85%. Moreover, a reduction in pollutant concentrations as well as stress on the entire ecosystem has been observed. Overall, the results illustrate how effective data-driven and adaptive approaches to restoration coupled with feedback sy
