The burning of fossil fuels, such as coal, oil, and gas, releases greenhouse gases into the atmosphere, which trap heat and cause the planet to warm.

Climate change is causing more frequent and severe droughts and wildfires, which can damage or destroy forests.

Climate change-induced biodiversity loss refers to the loss of biodiversity that is directly caused by climate change.

The decline of coral reefs due to ocean acidification is an example of a climate change-induced biodiversity loss because ocean acidification is caused by the absorption of carbon dioxide from the atmosphere, which is a result of climate change.

Forest environmental impact monitoring is primarily aimed at monitoring the health and condition of forests, including their biodiversity, productivity, and resilience.

Remote sensing is a common method used for forest environmental impact monitoring because it allows for the collection of data over large areas in a cost-effective and timely manner.

Remote sensing is primarily used for forest environmental impact monitoring to map forest cover and deforestation, as it allows for the detection of changes in forest cover over time.

Optical imagery is a type of remote sensing data that is commonly used for forest environmental impact monitoring because it provides information about the visible and near-infrared spectrum, which can be used to identify and classify different types of vegetation.

The primary advantage of using radar imagery for forest environmental impact monitoring is that it can penetrate clouds and vegetation, which makes it useful for monitoring forests in areas with frequent cloud cover or dense vegetation.

Transect surveys are a common method used for field surveys in forest environmental impact monitoring because they allow for the collection of data along a linear path, which can be used to assess changes in forest structure and composition over time.

Plot surveys are used in forest environmental impact monitoring to assess forest health and condition by collecting data on tree species composition, tree density, and other forest attributes within a defined area.

Soil analysis is a common method used for laboratory analysis in forest environmental impact monitoring because it can provide information about soil nutrients, pH, and other soil properties that can influence forest health and productivity.

Modeling and simulation are used in forest environmental impact monitoring to predict the impacts of climate change on forests by simulating different climate scenarios and assessing their potential effects on forest ecosystems.

Dynamic global vegetation models are a common type of model used for predicting the impacts of climate change on forests because they simulate the interactions between vegetation and the climate system, allowing for the assessment of how forests will respond to changes in climate.

The primary goal of forest environmental impact monitoring in relation to climate change is to assess the vulnerability of forests to climate change and to identify areas that are most at risk.