Palynological perspectives on vegetation survey: a critical step for model-based reconstruction of Quaternary land cover

1. Quantitative reconstruction of past vegetation distribution and abundance from sedimentary pollen records provides an important baseline for understanding long term ecosystem dynamics and for the calibration of earth system process models such as regional-scale climate models, widely used to predict future environmental change. Most current approaches assume that the amount of pollen produced by each vegetation type, usually expressed as a relative pollen productivity term, is constant in space and time.
2. Estimates of relative pollen productivity can be extracted from extended R-value analysis (Parsons and Prentice, 1981) using comparisons between pollen assemblages deposited into sedimentary contexts, such as moss polsters, and measurements of the present day vegetation cover around the sampled location. Vegetation survey method has been shown to have a profound effect on estimates of model parameters (Bunting and Hjelle, 2010), therefore a standard method is an essential pre-requisite for testing some of the key assumptions of pollen-based reconstruction of past vegetation; such as the assumption that relative pollen productivity is effectively constant in space and time within a region or biome.
3. This paper systematically reviews the assumptions and methodology underlying current models of pollen dispersal and deposition, and thereby identifies the key characteristics of an effective vegetation survey method for estimating relative pollen productivity in a range of landscape contexts.
4. It then presents the methodology used in a current research project, developed during a practitioner workshop. The method selected is pragmatic, designed to be replicable by different research groups, usable in a wide range of habitats, and requiring minimum effort to collect adequate data for model calibration rather than representing some ideal or required approach. Using this common methodology will allow project members to collect multiple measurements of relative pollen productivity for major plant taxa from several northern European locations in order to test the assumption of uniformity of these values within the climatic range of the main taxa recorded in pollen records from the region.

Climate change-linked range expansion of Nathusius' pipistrelle bat, Pipistrellus nathusii (Keyserling & Blasius, 1839)

Aim To examine the effect of climate change on the occurrence and distribution of Pipistrellus nathusii (Nathusius' pipistrelle) in the United Kingdom (UK).Location We modelled habitat and climatic associations of P. nathusii in the UK and applied this model to the species' historical range in continental Europe.Methods A binomial logistic regression model was constructed relating the occurrence of P. nathusii to climate and habitat characteristics using historical species occurrence records (1940-2006) and CORINE land cover data. This model was applied to historical and projected climate data to examine changes in suitable range (1940-2080) of this species. We tested the predictive ability of the model with known records in the UK after 2006 and applied the model to the species' known range in Europe.Results The distribution of P. nathusii was related positively to the area of water bodies, woodland and small areas of urbanization, and negatively related to the area of peat/heathland. Species records were associated with higher minimum temperatures, low seasonal variation in temperature and intermediate rainfall. We found that suitable areas have existed in the UK since the 1940s and that these have expanded. The model had high predictive power when applied to new records after 2006, with a correct classification rate of 70%, estimated by receiver operating characteristic analysis. Based on climate projections, our model suggests a potential twofold increase in the area suitable for P. nathusii in the UK by 2050. The single most influential climate variable contributing to range increase was the projected increase in minimum temperature. When applied to Europe, the model predictions had best predictive capability of known records in western areas of the species' range, where P. nathusii is present during the winter.Main conclusions We show that a mobile, migratory species has adapted its range in response to recent climate change on a continental scale. We believe this may be the first study to demonstrate a case of range change linked to contemporary climate change in a mammal species in Europe.

Behavioural context of multi-scale species distribution models assessed by radio-tracking

Incorporating ecological processes and animal behaviour into Species Distribution Models (SDMs) is difficult. In species with a central resting or breeding place, there can be conflict between the environmental requirements of the 'central place' and foraging habitat. We apply a multi-scale SDM to examine habitat trade-offs between the central place, roost sites, and foraging habitat in . Myotis nattereri. We validate these derived associations using habitat selection from behavioural observations of radio-tracked bats. A Generalised Linear Model (GLM) of roost occurrence using land cover variables with mixed spatial scales indicated roost occurrence was positively associated with woodland on a fine scale and pasture on a broad scale. Habitat selection of radio-tracked bats mirrored the SDM with bats selecting for woodland in the immediate vicinity of individual roosts but avoiding this habitat in foraging areas, whilst pasture was significantly positively selected for in foraging areas. Using habitat selection derived from radio-tracking enables a multi-scale SDM to be interpreted in a behavioural context. We suggest that the multi-scale SDM of . M. nattereri describes a trade-off between the central place and foraging habitat. Multi-scale methods provide a greater understanding of the ecological processes which determine where species occur and allow integration of behavioural processes into SDMs. The findings have implications when assessing the resource use of a species at a single point in time. Doing so could lead to misinterpretation of habitat requirements as these can change within a short time period depending on specific behaviour, particularly if detectability changes depending on behaviour. © 2011 Gesellschaft für ökologie.

Range expansion and comparative habitat use of insular, congeneric lagomorphs: invasive European hares Lepus europaeus and endemic Irish hares Lepus timidus hibernicus

The European hare (Lepus europaeus) has declined throughout its native range but invaded numerous regions where it has negatively impacted native wildlife. In southern Sweden, it replaces the native mountain hare (L. timidus) through competition and hybridisation. We investigated temporal change in the invasive range of the European hare in Ireland, and compared its habitat use with the endemic Irish hare (L. timidus hibernicus). The range of the European hare was three times larger and its core range twice as large in 2012–2013 than in 2005. Its rate of radial range expansion was 0.73 km year−1 with its introduction estimated to have occurred ca. 1970. Both species utilised improved and rough grasslands and exhibited markedly similar regression coefficients with almost every land cover variable examined. Irish hares were associated with low fibre and high sugar content grass (good quality grazing) whilst the invader had a greater tolerance for low quality forage. European hares were associated with habitat patch edge density, suggesting it may be more suited to using hedgerows as diurnal resting sites than the Irish hare. Consequently, the invader had a wider niche breadth than the native but their niche overlap was virtually complete. Given the impact of the European hare on native species elsewhere, and its apparent pre-adaption for improved grasslands interspersed with arable land (a habitat that covers 70 % of Ireland), its establishment and range expansion poses a significant threat to the ecological security of the endemic Irish hare, particularly given their ecological similarities.

Predicting forest attributes In southeast Alaska using artificial neural networks

Artificial neural network (ANN) methods are used to predict forest characteristics. The data source is the Southeast Alaska (SEAK) Grid Inventory, a ground survey compiled by the USDA Forest Service at several thousand sites. The main objective of this article is to predict characteristics at unsurveyed locations between grid sites. A secondary objective is to evaluate the relative performance of different ANNs. Data from the grid sites are used to train six ANNs: multilayer perceptron, fuzzy ARTMAP, probabilistic, generalized regression, radial basis function, and learning vector quantization. A classification and regression tree method is used for comparison. Topographic variables are used to construct models: latitude and longitude coordinates, elevation, slope, and aspect. The models classify three forest characteristics: crown closure, species land cover, and tree size/structure. Models are constructed using n-fold cross-validation. Predictive accuracy is calculated using a method that accounts for the influence of misclassification as well as measuring correct classifications. The probabilistic and generalized regression networks are found to be the most accurate. The predictions of the ANN models are compared with a classification of the Tongass national forest in southeast Alaska based on the interpretation of satellite imagery and are found to be of similar accuracy.

Nong Thale Pron - a key site from southern Thailand for studying monsoon variability during the past 15000 years

Studies of marine sediments, cave speleothemes, annually laminated corals, and tree rings from Asian monsoon regions have added knowledge to our understanding of the factors that control inter-annual to millennial monsoon variability in the past and have provided important constraints for climate modeling scenarios. In contrast, the spatial and temporal pattern of sub-millennial scale monsoon variability and its impact on land cover in SE Asia are still unresolved. This shortcoming stems from the fact that temporally well-resolved paleo-environmental studies are missing from large parts of SE Asia, especially from Thailand. Given that global and regional climate models are increasingly using terrestrial paleo- data to test their performance, past changes in land cover are therefore important variables to better understand feedbacks between different Earth systems. We obtained sediments from Lake Nong Thale Pron, in southern Thailand (8º 10`N, 99 º23`E; 380 m.asl). The aim of our study is to reconstruct lake status changes and to evaluate whether the extent of these changes are linked to known shifts in monsoon intensity and variability. Preliminary results show that lake infilling started more than 15,000 years ago and that the sediments cover the last deglaciation and the Holocene. Current analyses include Itrax XRF core scanning, loss-on-ignition (LOI at 950 and 550ºC), CN elemental and isotopic composition. We expect that our results will be able to give a picture of how the lake's status has changed over time and whether the extent of these changes is linked to known shifts in monsoon intensity and variability.

Exploiting Human Resource Requirements to Infer Human Movement Patterns for Use in Modelling Disease Transmission Systems: An Example from Eastern Province, Zambia

In this research, an agent-based model (ABM) was developed to generate human movement routes between homes and water resources in a rural setting, given commonly available geospatial datasets on population distribution, land cover and landscape resources. ABMs are an object-oriented computational approach to modelling a system, focusing on the interactions of autonomous agents, and aiming to assess the impact of these agents and their interactions on the system as a whole. An A* pathfinding algorithm was implemented to produce walking routes, given data on the terrain in the area. A* is an extension of Dijkstra's algorithm with an enhanced time performance through the use of heuristics. In this example, it was possible to impute daily activity movement patterns to the water resource for all villages in a 75 km long study transect across the Luangwa Valley, Zambia, and the simulated human movements were statistically similar to empirical observations on travel times to the water resource (Chi-squared, 95% confidence interval). This indicates that it is possible to produce realistic data regarding human movements without costly measurement as is commonly achieved, for example, through GPS, or retrospective or real-time diaries. The approach is transferable between different geographical locations, and the product can be useful in providing an insight into human movement patterns, and therefore has use in many human exposure-related applications, specifically epidemiological research in rural areas, where spatial heterogeneity in the disease landscape, and space-time proximity of individuals, can play a crucial role in disease spread.

Temporal variation in the water chemistry of northern Victoria Land lakes (Antarctica)

Concentrations of major ions, silicate and nutrients (total N and P) were measured in samples of surface water from 28 lakes in ice-free areas of northern Victoria Land (East Antarctica). Sixteen lakes were sampled during austral summers 2001/02, 2003/04, 2004/05 and 2005/06 to assess temporal variation in water chemistry. Although samples showed a wide range in ion concentrations, their composition mainly reflected that of seawater. In general, as the distance from the sea increased, the input of elements from the marine environment (through aerosols and seabirds) decreased and there was an increase in nitrate and sulfate concentrations. Antarctic lakes lack outflows and during the austral summer the melting and/or ablation of ice cover, water evaporation and leaching processes in dry soils determine a progressive increase in water ion concentrations. During the five-year monitoring survey, no statistically significant variation in the water chemistry were detected, except for a slight (hardly significant) increase in TN concentrations. However, Canonical Correspondence Analysis (CCA) indicated that other factors besides distance from the sea, the presence of nesting seabirds, the sampling time and percentage of ice cover affect the composition of water in Antarctic cold desert environments.