Response of benthic cave invertebrates to organic pollution events

1.Even though the fragility and vulnerability of subterranean ecosystems (caves, groundwater and hyporheic habitats) is widely acknowledged, the impacts of anthropogenic disturbances have been poorly quantified when compared to surface waters. In particular, limited data exist regarding the impact of organic pollution upon aquatic cave invertebrate communities. 2.The Peak-Speedwell Cavern system (Derbyshire, UK) was affected by two organic pollution events, during a 7–year study (1997-2003), originating from the same source in the surface catchment but resulting in markedly different ecological responses. The first event led to the elimination of most taxa from affected sites while the second resulted in an increase in abundance of organisms within the cave associated with the increased availability of trophic resources. The second event also coincided with the invasion of the stygophilic amphipod, Gammarus pulex, at a site where it had not previously been recorded. 3.Recovery of the invertebrate community following both organic pollution events occurred within 12-months. Recolonisation of the affected sites was facilitated by annual flooding of the cave and by the presence of refugia on unaffected subterranean tributaries. 4.The data highlight the problems associated with the conservation and management of subterranean ecosystems where impacts in distant surface catchments may have unseen repercussions for the subterranean environment. Aquatic subterranean habitats are not widely monitored and the impacts of pollution/disturbance may not be detected in surface waters for some time, if at all, due to dilution effects. Caves supporting obligate subterreanean organisms (stygobites) are particularly vulnerable to these pressures and require clear management strategies to protect both the subterranean and surface catchments which support them

Scientific and ecological value of seasonal aquatic systems with particular reference to the Pantyllyn turlough - Dyfed

SIGLEAvailable from British Library Document Supply Centre- DSC:GPC-03551 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

The Mixed Meal Model: quantifying the contribution of 1 triglycerides to metabolic resilience.

Despite the pivotal role played by elevated circulating triglyceride levels in the pathophysiology of cardio-metabolic diseases many of the indices used to quantify metabolic health focus on deviations in glucose and insulin alone. We present the Mixed Meal Model, a computational model describing the systemic interplay between triglycerides, free fatty acids, glucose, and insulin. We show that the Mixed Meal Model can capture deviations in the post-meal excursions of plasma glucose, insulin, and triglyceride that are indicative of features of metabolic resilience; quantifying insulin resistance and liver fat; validated by comparison to gold-standard measures. We also demonstrate that the Mixed Meal Model is generalisable, applying it to meals with diverse macro-nutrient composition. In this way, by coupling triglycerides to the glucose-insulin system the Mixed Meal Model provides a more holistic assessment of metabolic resilience from meal response data, quantifying pre-clinical metabolic deteriorations that drive disease development in overweight and obesity

Quantifying the contribution of triglycerides to metabolic resilience through the mixed meal model

Despite the pivotal role played by elevated circulating triglyceride levels in the pathophysiology of cardio-metabolic diseases many of the indices used to quantify metabolic health focus on deviations in glucose and insulin alone. We present the Mixed Meal Model, a computational model describing the systemic interplay between triglycerides, free fatty acids, glucose, and insulin. We show that the Mixed Meal Model can capture deviations in the post-meal excursions of plasma glucose, insulin, and triglyceride that are indicative of features of metabolic resilience; quantifying insulin resistance and liver fat; validated by comparison to gold-standard measures. We also demonstrate that the Mixed Meal Model is generalizable, applying it to meals with diverse macro-nutrient compositions. In this way, by coupling triglycerides to the glucose-insulin system the Mixed Meal Model provides a more holistic assessment of metabolic resilience from meal response data, quantifying pre-clinical metabolic deteriorations that drive disease development in overweight and obesity