6 resultados para Threshold regression
em Publishing Network for Geoscientific
Resumo:
This study combined data on fin whale Balaenoptera physalus, humpback whale Megaptera novaeangliae, minke whale B. acutorostrata, and sei whale B. borealis sightings from large-scale visual aerial and ship-based surveys (248 and 157 sightings, respectively) with synoptic acoustic sampling of krill Meganyctiphanes norvegica and Thysanoessa sp. abundance in September 2005 in West Greenland to examine the relationships between whales and their prey. Krill densities were obtained by converting relationships of volume backscattering strengths at multiple frequencies to a numerical density using an estimate of krill target strength. Krill data were vertically integrated in 25 m depth bins between 0 and 300 m to obtain water column biomass (g/m**2) and translated to density surfaces using ordinary kriging. Standard regression models (Generalized Additive Modeling, GAM, and Generalized Linear Modeling, GLM) were developed to identify important explanatory variables relating the presence, absence, and density of large whales to the physical and biological environment and different survey platforms. Large baleen whales were concentrated in 3 focal areas: (1) the northern edge of Lille Hellefiske bank between 65 and 67°N, (2) north of Paamiut at 63°N, and (3) in South Greenland between 60 and 61° N. There was a bimodal pattern of mean krill density between depths, with one peak between 50 and 75 m (mean 0.75 g/m**2, SD 2.74) and another between 225 and 275 m (mean 1.2 to 1.3 g/m**2, SD 23 to 19). Water column krill biomass was 3 times higher in South Greenland than at any other site along the coast. Total depth-integrated krill biomass was 1.3 x 10**9 (CV 0.11). Models indicated the most important parameter in predicting large baleen whale presence was integrated krill abundance, although this relationship was only significant for sightings obtained on the ship survey. This suggests that a high degree of spatio-temporal synchrony in observations is necessary for quantifying predator-prey relationships. Krill biomass was most predictive of whale presence at depths >150 m, suggesting a threshold depth below which it is energetically optimal for baleen whales to forage on krill in West Greenland.
Resumo:
Lake Baikal, the world's most voluminous freshwater lake, has experienced unprecedented warming during the last decades. A uniquely diverse amphipod fauna inhabits the littoral zone and can serve as a model system to identify the role of thermal tolerance under climate change. This study aimed to identify sublethal thermal constraints in two of the most abundant endemic Baikal amphipods, Eulimnogammarus verrucosus and Eulimnogammarus cyaneus, and Gammarus lacustris, a ubiquitous gammarid of the Holarctic. As the latter is only found in some shallow isolated bays of the lake, we further addressed the question whether rising temperatures could promote the widespread invasion of this non-endemic species into the littoral zone. Animals were exposed to gradual temperature increases (4 week, 0.8 °C/d; 24 h, 1 °C/h) starting from the reported annual mean temperature of the Baikal littoral (6 °C). Within the framework of oxygen- and capacity-limited thermal tolerance (OCLTT), we used a nonlinear regression approach to determine the points at which the changing temperature-dependence of relevant physiological processes indicates the onset of limitation. Limitations in ventilation representing the first limits of thermal tolerance (pejus (= "getting worse") temperatures (Tp)) were recorded at 10.6 (95% confidence interval; 9.5, 11.7), 19.1 (17.9, 20.2), and 21.1 (19.8, 22.4) °C in E. verrucosus, E. cyaneus, and G. lacustris, respectively. Field observations revealed that E. verrucosus retreated from the upper littoral to deeper and cooler waters once its Tp was surpassed, identifying Tp as the ecological thermal boundary. Constraints in oxygen consumption at higher than critical temperatures (Tc) led to an exponential increase in mortality in all species. Exposure to short-term warming resulted in higher threshold values, consistent with a time dependence of thermal tolerance. In conclusion, species-specific limits to oxygen supply capacity are likely key in the onset of constraining (beyond pejus) and then life-threatening (beyond critical) conditions. Ecological consequences of these limits are mediated through behavioral plasticity in E. verrucosus. However, similar upper thermal limits in E. cyaneus (endemic, Baikal) and G. lacustris (ubiquitous, Holarctic) indicate that the potential invader G. lacustris would not necessarily benefit from rising temperatures. Secondary effects of increasing temperatures remain to be investigated.
Resumo:
Extinction is a remarkably difficult phenomenon to study under natural conditions. This is because the outcome of stress exposure and associated fitness reduction is not known until the extinction occurs and it remains unclear whether there is any phenotypic reaction of the exposed population that can be used to predict its fate. Here we take advantage of the fossil record, where the ecological outcome of stress exposure is known. Specifically, we analyze shell morphology of planktonic Foraminifera in sediment samples from the Mediterranean, during an interval preceding local extinctions. In two species representing different plankton habitats, we observe shifts in trait state and decrease in variance in association with non-terminal stress, indicating stabilizing selection. At terminal stress levels, immediately before extinction, we observe increased growth asymmetry and trait variance, indicating disruptive selection and bet-hedging. The pre-extinction populations of both species show a combination of trait states and trait variance distinct from all populations exposed to non-terminal levels of stress. This finding indicates that the phenotypic history of a population may allow the detection of threshold levels of stress, likely to lead to extinction. It is thus an alternative to population dynamics in studying and monitoring natural population ecology.