introduction forest ecosystems have continuously downgraded due to every environmental pressure including climate change, aerosols deposits, industrial pollutions and other degradation factors. the output soon or late would be a different forest. forest monitoring is a well-regulated and usually long running procedure, which has the ability to detect these phenomena and reactions based on aims ...

There is converging evidence that physical activity influences affective states. It has been found that aerobic exercise programs can significantly diminish negative affect. Moreover, among healthy individuals, moderate levels of physical activity seem to increase energetic arousal and positive affect. However, the predictive utility of affective states for bodily movement has rarely been inves...

OBJECTIVE We employed Ecological Momentary Assessment (EMA) real-time recording in the natural setting to determine whether spousal interaction frequency predicts 3-year progression of carotid artery intima medial thickening (IMT). METHODS Participants were 250 healthy, older adults (M age = 61, 48% female) who, at baseline, underwent 6 days of ambulatory monitoring using electronic diaries t...

In summary, LTER systems can provide a standardized infrastructure to collect comparable data to answer the questions of today, and a rigorous scientific basis to address future challenges. We invite scientists to integrate stand-alone studies within innovative LTER approaches to provide future generations with the management tools to move beyond the confines of our current limited biodiversity...

We describe and label four types of monitoring—surveillance, implementation, effectiveness, and ecological effects—that are designed to answer very different questions and achieve very different goals. Surveillance monitoring is designed to uncover change in target variables over space and time; implementation monitoring is designed to record whether management actions were applied as prescribe...

Phytoplankton biomass within the Saginaw Bay ecosystem (Lake Huron, Michigan, USA) was characterized as a function of select physical/chemical indicators. The complexity and variability of ecological systems typically make it difficult to model the influences of anthropogenic stressors and/or natural disturbances. Here, Artificial Neural Networks (ANNs) were developed to model chlorophyll a con...