ADVERTISEMENT

How To Classify Tropical Forests In Brazil In Terms Of Carbon Stock

Recently many countries have committed to emissions reports to climate accords informing their greenhouse gas (GHG) annual emissions, including carbon dioxide. Forest ecosystems are huge carbon sinks and with this, they substantially contribute to intensifying the greenhouse effect. Thus, there is an increasing need for quantifying carbon in forests.

The paper proposes a statistical method for classifying natural forests into four classes of carbon stock, ranging from low to very-high stock. Such classification method employs overall climate and physical (stand) variables; mean annual temperature (MAT), and mean annual precipitation (MAP) were included as climatic variables, whereas tree dimensions and density were considered as the standard ones. The paper assessed three sets of variables: i) with all variables, ii) with all variables, except mean height, and iii) with all variables, except mean height, mean square diameter of trees, and basal area (this last reflects the degree of ground occupation of trees per unit area).

ADVERTISEMENT

These sets of variables were tested with i) MAT and MAP together, ii) MAT only, iii) MAP only, and neither. The procedure was performed in two Brazilian forest types: Atlantic Forest (similar to evergreen tropical forests) and Savanna, which is in a drier and hotter region than Atlantic Forest. As results, the best case reached nearly 100% of correct classification. Stand variables contributed significantly to successful classification. The variable mean height exerted a greater effect in Savanna forests than those in Atlantic Forest, however, basal area and mean square diameter were the most important in both biomes.

Climate variables were most helpful when stand variables were not included in the analysis; this is an expected behavior because stand variables are directly related to tree dimensions and density, which are, in turn, directly related to carbon stored on stems, branches, and crowns of trees. The climate variables attained a maximum contribution of 9.2% for the classification, a value significant at 95% probability level. In relation to the response of forests to climate variables, forests from Atlantic Forest tended to be more sensitive to both MAT and MAP, whereas forests from Savanna had no significant climatic dependence in the classification.

As shown in other research that relates forest carbon and weather, the findings suggest that highly stocked forests are negatively correlated with MAT and positively correlated with MAP, i.e., hotter and drier regions shelter forests with the lower carbon stocks. As many other researchers have found, the study points out climate warming and drier seasons as threats to forest carbon loss in the tropical biomes.

The method could be expanded to other variables besides tree carbon, such as live or dead biomass and carbon of any tree/forest component. The validation proved that the method is efficient, reaching a high degree of correct classifications even for validation data. The method is useful in the forest management by allowing to estimate carbon stocks at local and regional scales over large areas.

ADVERTISEMENT

This study, Carbon stock classification for tropical forests in Brazil: Understanding the effect of stand and climate variables was recently published by Hassan Camil David et al., in the journal Forest Ecology and Management.

Comments

READ THIS NEXT

Feeding Electricity To Bacteria

Can electricity serve as an alternative electron supplier for bacterial growth? And can we enhance the electron uptake capacity of […]

How Many Liters In Are In 1 Gallon?

How many liters are in a gallon? While you may think the answer to this question should be a straightforward […]

Yellowstone Supervolcano May Blow Faster Than Thought

Yellowstone National Park is one of the first national parks in the United States. It is home to numerous ecosystems, […]

Biased And Crossmap Dropout Strategies For Convolutional Neural Networks

Over the last decade, deep learning models, particularly Convolutional Neural Networks (CNN), have shown outstanding results in various fields, including […]

College Drinking Culture In Spain, Argentina, And The USA: An Examination Of Impulsivity, College Alcohol Beliefs, And Alcohol Outcomes

Across many countries and cultures, college students drink heavily. Students who drink heavily are at risk for a wide range […]

Function Of The Nucleus

The function of the nucleus is to store a cell’s hereditary material, or DNA, which helps with and controls a […]

Inhibiting Prostaglandin E2 Receptor EP3 May Reduce Brain Injury After Hemorrhagic Stroke

Intracerebral hemorrhage (ICH), otherwise known as hemorrhagic stroke, accounts for approximately 15% of all strokes. In this type of stroke, […]

Science Trends is a popular source of science news and education around the world. We cover everything from solar power cell technology to climate change to cancer research. We help hundreds of thousands of people every month learn about the world we live in and the latest scientific breakthroughs. Want to know more?