Precise descriptions of forest productivity, biomass, and structure are essential for understanding ecosystem responses to climatic and anthropogenic changes. However, relations between these components are complex, in particular for tropical forests. We developed an approach to simulate carbon dynamics in the Amazon rainforest including around 410 billion individual trees within 7.8 million km.

Understanding how anthropogenic CO2 emissions will influence future precipitation is critical for sustainably managing ecosystems, particularly for drought-sensitive tropical forests. Although tropical precipitation change remains uncertain, nearly all models from the Coupled Model Intercomparison Project Phase 5 predict a strengthening zonal precipitation asymmetry by 2100, with relative increases over Asian and African tropical forests and decreases over South American forests.

The present study documents the wood-boring trace fossil Asthenopodichnium from the Palaeocene sediments of the Barmer Hill Formation (BHF) in the Barmer Basin, Western Rajasthan, India. The Asthenopodichnium trace fossils are loosely to tightly packed, pouch-like burrows or almond-shaped structures identified as Asthenopodichnium lignorum, whereas lozenge and J-shaped structures are designated as Asthenopodichnium lithuanicum.

Original Source

Non-native plants invade some tropical forests but there are few long-term studies of these invasions, and the consequences for plant richness and diversity are unclear. Repeated measurements of permanent plots in tropical montane rain forests in the Blue and John Crow Mountains National Park in Jamaica over 24 to 40 years coincided with invasion by a non-native tree, Pittosporum undulatum.

Limited data exists on emissions from agriculture-driven deforestation, and available data are typically uncertain. In this paper, we provide comparable estimates of emissions from both all deforestation and agriculture-driven deforestation, with uncertainties for 91 countries across the tropics between 1990 and 2015. Uncertainties associated with input datasets (activity data and emissions factors) were used to combine the datasets, where most certain datasets contribute the most. This method utilizes all the input data, while minimizing the uncertainty of the emissions estimate.