PALOMA · A Palaeoenvironmental Investigation of Amazonian Lowland Sensitivity to Climatic Drivers Using Pollen-based Modelling Approaches

A Palaeoenvironmental Investigation of Amazonian Lowland Sensitivity to Climatic Drivers Using Pollen-based Modelling Approaches

This MSCA project was entitled “A Palaeoenvironmental Investigation of Amazonian Lowland Sensitivity to Climatic Drivers Using Pollen-Based Modelling Approaches”, hereafter Project PALOMA (European Fellowship, Grant ID 101105420), and it was hosted at Geosciences Barcelona (GEO3BCN-CSIC). Its overarching aim was to initiate the first steps towards reconstructing past environmental and climatic changes in Amazonia, more specifically the lowlands of north-western Amazonia, using quantitative pollen-based climatic modelling, in order to understand the sensitivity of this biome to climatic drivers during the Holocene (last 11,700 years). Being able to accurately reconstruct past climatic changes in the Amazon, and use these findings as past analogues of what we could face in the ongoing global change scenario to inform conservation initiatives and relevant stakeholders, is an increasingly urgent matter. Considering the current rate of CO2 emissions, the ‘safe’ limit of 2°C warming will likely be exceeded by 2100. Projected disruptions to the balance of hydrological and evapotranspiration cycles may lead to forest dieback and in turn trigger changes in rainfall and increased fire events and send Amazonia down an irreversible path. As such, protecting and conserving globally-important carbon sinks like the Amazon represents the strongest approach for defence against climate change. Within the last region, the lowlands of NW Amazonia are particularly crucial in the regulation of Amazonia’s hydrological cycles as this region receives most of the water input from the Andes and delivers it into the Amazon River, meaning than any changes here will likely affect the rest of the Basin and ultimately the rest of the world. Therefore, reconstructing past changes in climate and environment in Amazonia can help us evaluate the response and sensitivity of these ecosystems to external drivers, including climatic variability. We can use this information to forecast the potential shifts the vegetation may undergo in the ongoing climatic change, and even anticipate undesirable scenarios. Fossil pollen grains, preserved in sedimentary deposits such as lakes or peatlands, enable the reconstruction of past vegetation composition through time and the drivers that led to changes in assemblages, such as climatic variability and human impact. While some long-term (1000+ years) records of climate have been recovered from the Amazonian region in the past, these rely on interpretations of several proxies (like pollen) or indicators of climate that are often hard to disentangle from other processes, limiting our ability to compare past changes to present-day climatic observations or future projections. In this context, project PALOMA sought to attempt the development and application of quantitative pollen-based climate reconstructions using modern pollen datasets to calibrate statistical relationships between vegetation and climate. This approach is based on the principle that plant taxa occupy specific climatic ranges, and that pollen assemblages reflect the composition of surrounding vegetation. By compiling modern pollen data across climatic and environmental gradients and linking these to observed climatic variables, it is possible to establish the relationship between pollen and climatic parameters such as temperature and precipitation. These relationships can then be used to calibrate fossil pollen records using transfer function models and reconstruct past climate variables. The overall objectives of the project were: 1) Enhance the modern pollen dataset for Amazonian lowlands and improve the representation of different taphonomic sources; and 2) Apply quantitative methods for pollen-based climate reconstruction to fossil records from NW Amazonia.

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