Glacial and interglacial refugia within a long-term rainforest refugium: The Wet Tropics Bioregion of NE Queensland, Australia

An artificial neural network is used to classify environments, including climate, terrain and soil variables, according to their suitability for fifteen structural/environmental forest classes in the Wet Tropics Bioregion of north-east Queensland. We map the environments characteristic of these forest classes in four climate regimes (the present and three past climate scenarios), quantify the changes in area of these environments in response to past regional changes in climate and identify areas that would have been environmentally suitable for rainforests at last glacial maximum (glacial refugia). We also identify areas that would have been suitable for upland and highland rainforest classes during the warmest parts of the interglacial (interglacial refugia) and map locations that consistently remain favourable to specific forest classes despite large changes in climate.In the climate of the last glacial maximum (LGM), rainforest environments are predicted in three relatively distinct refugia in the northern, central and southern Wet Tropics. Only three percent of the total area contains lowland, Mesophyll Vine Forest and the majority of the area of the rainforest refugia supports upland rainforest classes. In the cool, wet climate of the Pleistocene/Holocene transition (PHT), rainforest environments expand to form a more or less continuous block from the northern limits of the region to the Walter Hill Range, except for discontinuous patches extending through the Seaview and Paluma Ranges in the south. During the Holocene climatic optimum (HCO), rainforest environments become more fragmented, especially in the south. Lowland rainforest environments are very extensive in this climate while upland rainforest classes are restricted to what we term “interglacial refugia”.Estimated distributions and stable locations (consistently predicted in all four climate scenarios) for the various rainforest environment classes are our main, novel contribution. Each forest environment responds individualistically to climate change. Our results confirm the highly dynamic nature of the Wet Tropics landscape and present a much more detailed picture of landscape change since the late Pleistocene than previously has been available. This mapping exercise should be useful in the future for analyses of present-day biogeographic patterns. We argue that empirical modelling approaches have an important role in palaeoecology and global change research that is complementary to the developing mechanistic methods.     

Expected trends and surprises in the Lateglacial and Holocene vegetation history of the Iberian Peninsula and Balearic Islands

Recent, high-resolution palaeoecological records are changing the traditional picture of post-glacial vegetation succession in the Iberian Peninsula. In addition to the influence of Lateglacial and Early Holocene climatic changes, other factors are critical in the course of vegetation development and we observe strong regional differences. The floristic composition, location and structure of glacial tree populations and communities may have been primary causes of vegetation development. Refugial populations in the Baetic cordilleras would have been a source, but not the only one, for the early Lateglacial oak expansions. From Mid to Late Holocene, inertial, resilient, and rapid responses of vegetation to climatic change are described, and regional differences in the response are stressed. The role of fire, pastoralism, agriculture, and other anthropogenic disturbances (such as mining), during the Copper, Bronze, Iberian, and Roman times, is analysed. The implications of ecological transitions in cultural changes, especially when they occur as societal collapses, are discussed.     

Controlled comparison of species- and community-level models across novel climates and communities

Species distribution models (SDMs) assume species exist in isolation and do not influence one another''s distributions, thus potentially limiting their ability to predict biodiversity patterns. Community-level models (CLMs) capitalize on species co-occurrences to fit shared environmental responses of species and communities, and therefore may result in more robust and transferable models. Here, we conduct a controlled comparison of five paired SDMs and CLMs across changing climates, using palaeoclimatic simulations and fossil-pollen records of eastern North America for the past 21 000 years. Both SDMs and CLMs performed poorly when projected to time periods that are temporally distant and climatically dissimilar from those in which they were fit; however, CLMs generally outperformed SDMs in these instances, especially when models were fit with sparse calibration datasets. Additionally, CLMs did not over-fit training data, unlike SDMs. The expected emergence of novel climates presents a major forecasting challenge for all models, but CLMs may better rise to this challenge by borrowing information from co-occurring taxa.