This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry... Show moreThis paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. The chain first uses random forests regression with surrogates to fill gaps in the database (> 45% of missing entries) and maximizes the global representativeness of the trait dataset. Plant species are then aggregated to Plant Functional Types (PFTs). Next, the spatial abundance of PFTs at MODIS resolution (500 m) is calculated using Landsat data (30 m). Based on these PFT abundances, representative trait values are calculated for MODIS pixels with nearby trait data. Finally, different regression algorithms are applied to globally predict trait estimates from these MODIS pixels using remote sensing and climate data. The methods were compared in terms of precision, robustness and efficiency. The best model (random forests regression) shows good precision (normalized RMSE≤ 20%) and goodness of fit (averaged Pearson's correlation R = 0.78) in any considered trait. Along with the estimated global maps of leaf traits, we provide associated uncertainty estimates derived from the regression models. The process chain is modular, and can easily accommodate new traits, data streams (traits databases and remote sensing data), and methods. The machine learning techniques applied allow attribution of information gain to data input and thus provide the opportunity to understand trait-environment relationships at the plant and ecosystem scales. The new data products – the gap-filled trait matrix, a global map of PFT abundance per MODIS gridcells and the high-resolution global leaf trait maps – are complementary to existing large-scale observations of the land surface and we therefore anticipate substantial contributions to advances in quantifying, understanding and prediction of the Earth system. Show less
This thesis examines the challenges and human responses to changes in climate and environment in occupying north-west Europe from MIS 11 to MIS 5e (c. 420__125 ka). The first part studies human... Show moreThis thesis examines the challenges and human responses to changes in climate and environment in occupying north-west Europe from MIS 11 to MIS 5e (c. 420__125 ka). The first part studies human habitats and environments in Britain during MIS 11 and concludes that humans were attracted to the more dynamic, open river valleys in temperate climates, which provided a greater variety of resources. Part 2 examines population change in Britain from MIS 13 __ MIS 5e using the archaeology from the different terraces of the Thames and Solent rivers. Using artefacts as a proxy for population, both river systems suggest peak populations in MIS 13 and 11, with low populations or human absence from MIS 6 to MIS 4. Part 3 examines the reasons for this probable absence of humans. The major differences between the archaeological records from Britain and continental Europe suggests that it was the island status of Britain that controlled population, largely governed by the progressive subsidence of the floor of the North Sea Basin Show less
In this thesis I studied the relationships between parasitoids, hosts and climate from an evolutionary point of view by using hymenopteran parasitoids as a model system. A comparative approach was... Show moreIn this thesis I studied the relationships between parasitoids, hosts and climate from an evolutionary point of view by using hymenopteran parasitoids as a model system. A comparative approach was used to study the variation in life-history traits of species or populations from different habitats. I showed that closely related species manipulate their host behaviour differently and allocate their essential resources to different life-history traits during development. Metabolic rate and energy reserves varied strongly between species. At the population level, energy reserves were found differ substantially between different climate zones. A molecular study revealed clear genetic divergence of these populations, which partially reflected the pattern in life-history variation. To conclude, I suggest that life-history traits of parasitoids are subject to natural selection pressures from both host and cli mate. Resource allocation and host manipulation in parasitoids is species specific and highly diverged among populations to fit habitat requirements. Show less
