H. John B. Birks

Modern diatom, cladocera, chironomid, and chrysophyte cyst assemblages as quantitative indicators for the reconstruction of past environmental conditions in the Alps. II. Nutrients

Diatom, chrysophyte cyst, benthic cladocera, planktonic cladocera, and chironomid assemblages were studied in the surface sediments of 68 small lakes along an altitudinal gradient from 300 to 2350 m in Switzerland. In addition, 43 environmental variables relating to the physical limnology, geography, catchment characteristics, climate, and water chemistry were recorded or measured for each lake. The explanatory power of each of these predictor variables for the different biological data-sets was estimated by a series of canonical correspondence analyses (CCA) and the statistical significance of each model was assessed by Monte Carlo permutation tests. A minimal set of environmental variables was found for each biological data-set by a forward-selection procedure within CCA. The unique, independent explanatory power of each set of environmental variables was estimated by a series of CCAs and partial CCAs. Inference models or transfer functions for mean summer (June, July, August) air temperature were developed for each biological data-set using weighted-averaging partial least squares or partial least squares. The final transfer functions, after data screening, have root mean squared errors of prediction, as assessed by leave-one-out cross-validation, of 1.37 °C (chironomids), 1.60 °C (benthic cladocera), 1.62 °C (diatoms), 1.77 °C (planktonic cladocera), and 2.23 °C (chrysophyte cysts).

Alpines, trees, and refugia in Europe

Refugia were critically important for species survival in both glacial and interglacial stages of the Quaternary. The classical view of glacial stages is that alpine and arctic plants were widespread in the lowlands of central Europe and around the margins of the continental and alpine ice-sheets, whereas trees were restricted to localised refugial areas in southern Europe and the Mediterranean basin. New palaeobotanical evidence in Europe suggests, however, that this classical view is incomplete and that tree distributional ranges during the glacial stages were more extensive and included many local areas of small populations in central and eastern Europe growing in so-called ‘cryptic’ refugia. We argue that this concept of ‘cryptic’ refugia is also applicable to arctic and alpine plants during temperate interglacial stages where small localised populations grow in naturally open habitats that are not beyond or above the forest limit. Determination of the whereabouts of these cold- and warm-stage ‘cryptic’ refugia is very important in our understanding of the spatial patterns of present day genetic diversity and the possible rates of spread of trees in response to future climate change.

Strengths and Weaknesses of Quantitative Climate Reconstructions Based on Late-Quaternary Biological Proxies

The importance of reconstructing past environments quantitatively in palaeoecology is reviewed by showing that many ecological questions asked of palaeoecological data commonly involve the reconstructions of past environment. Three basic approaches to reconstructing past climate from palaeoecological data are outlined and discussed in terms of their assumptions, strengths, and weaknesses. These approaches are the indicator-species approach involving bioclimateenvelope modelling; the assemblage approach involving modern analogue techniques and response surfaces; and the multivariate calibration-function approach. Topics common to all approaches are reviewed – presentation and interpretation, evaluation and validation, comparison, and general limitations of climate reconstructions. Challenges and possible future developments are presented and the potential future role of quantitative climate reconstructions in palaeoecology is summarised.

Quantitative Environmental Reconstructions from Biological Data

Quantitative reconstructions of past environmental conditions (e.g., pH) are an important part of palaeolimnology. Such reconstructions involve three steps: (1) the development of a representative modern organism-environment training-set, (2) the development and application of appropriate numerical techniques to model the relationship between modern occurrences and abundances of the organisms in the training-set and their contemporary environment, and (3) the application of this model to stratigraphical palaeolimnological data to infer past environmental conditions, and model selection, testing, and evaluation and assessment of the final reconstruction. These three stages are discussed. Problems of spatial autocorrelation are outlined. The general approach is illustrated by a case-study. The assumptions and limitations of the calibration-function approach are presented, and violations of these assumptions are discussed in relation to different environmental reconstructions. Appropriate computer software is outlined, and future research areas are presented. The chapter challenges palaeolimnologists to be more critical of their environmental-inference models and to be alert to the problems and dangers of confounding variables, and of violating the main assumptions of the approach.

Looking forward through the past : identification of 50 priority research questions in palaeoecology

Summary 1. Priority question exercises are becoming an increasingly common tool to frame future agendas in conservation and ecological science. They are an effective way to identify research foci that advance the field and that also have high policy and conservation relevance. 2. To date there has been no coherent synthesis of key questions and priority research areas for palaeoecology, which combines biological, geochemical and molecular techniques in order to reconstruct past ecological and environmental systems on timescales from decades to millions of years. 3. We adapted a well-established methodology to identify 50 priority research questions in palaeoecology. Using a set of criteria designed to identify realistic and achievable research goals, we selected questions from a pool submitted by the international palaeoecology research community and relevant policy practitioners. This article is protected by copyright. All rights reserved. Accepted Article 4. The integration of online participation, both before and during the workshop, increased international engagement in question selection. 5. The questions selected are structured around six themes: human–environment interactions in the Anthropocene; biodiversity, conservation, and novel ecosystems; biodiversity over long timescales; ecosystem processes and biogeochemical cycling; comparing, combining and synthesizing information from multiple records; and new developments in palaeoecology. 6. Future opportunities in palaeoecology are related to improved incorporation of uncertainty into reconstructions, an enhanced understanding of ecological and evolutionary dynamics and processes, and the continued application of long-term data for better-informed landscape management. 7. Synthesis Palaeoecology is a vibrant and thriving discipline and these 50 priority questions highlight its potential for addressing both pure (e.g. ecological and evolutionary, methodological) and applied (e.g. environmental and conservation) issues related to ecological science and global change.

Local temperatures inferred from plant communities suggest strong spatial buffering of climate warming across Northern Europe

Recent studies from mountainous areas of small spatial extent (<2500 km(2) ) suggest that fine-grained thermal variability over tens or hundreds of metres exceeds much of the climate warming expected for the coming decades. Such variability in temperature provides buffering to mitigate climate-change impacts. Is this local spatial buffering restricted to topographically complex terrains? To answer this, we here study fine-grained thermal variability across a 2500-km wide latitudinal gradient in Northern Europe encompassing a large array of topographic complexities. We first combined plant community data, Ellenberg temperature indicator values, locally measured temperatures (LmT) and globally interpolated temperatures (GiT) in a modelling framework to infer biologically relevant temperature conditions from plant assemblages within <1000-m(2) units (community-inferred temperatures: CiT). We then assessed: (1) CiT range (thermal variability) within 1-km(2) units; (2) the relationship between CiT range and topographically and geographically derived predictors at 1-km resolution; and (3) whether spatial turnover in CiT is greater than spatial turnover in GiT within 100-km(2) units. Ellenberg temperature indicator values in combination with plant assemblages explained 46-72% of variation in LmT and 92-96% of variation in GiT during the growing season (June, July, August). Growing-season CiT range within 1-km(2) units peaked at 60-65°N and increased with terrain roughness, averaging 1.97 °C (SD = 0.84 °C) and 2.68 °C (SD = 1.26 °C) within the flattest and roughest units respectively. Complex interactions between topography-related variables and latitude explained 35% of variation in growing-season CiT range when accounting for sampling effort and residual spatial autocorrelation. Spatial turnover in growing-season CiT within 100-km(2) units was, on average, 1.8 times greater (0.32 °C km(-1) ) than spatial turnover in growing-season GiT (0.18 °C km(-1) ). We conclude that thermal variability within 1-km(2) units strongly increases local spatial buffering of future climate warming across Northern Europe, even in the flattest terrains.

From Classical to Canonical Ordination

The simple or classical ordination methods mostly used by palaeoecologists and palaeolimnologists are principal component analysis (PCA) and correspondence analysis (CA), and, more rarely, principal coordinate analysis (PCoA) and non-metric multidimensional scaling (NMDS). These methods are reviewed in a geometric framework. They mostly differ by the types of distances among objects that they allow users to preserve during ordination. Canonical ordination methods are generalisations of the simple ordination techniques; the ordination is constrained to represent the part of the variation of a table of response variables (e.g., species abundances) that is maximally related to a set of explanatory variables (e.g., environmental variables). Canonical redundancy analysis (RDA) is the constrained form of PCA whereas canonical correspondence analysis (CCA) is the constrained form of CA. Canonical ordination methods have also been proposed that look for linear and polynomial relationships between the dependent and explanatory variables. Tests of statistical significance using permutation tests can be obtained in canonical ordination, just as in multiple regression. Canonical ordination serves as the basis for variation partitioning, an analytical procedure widely used by palaeolimnologists.

Quantifying recent ecological changes in remote lakes of North America and greenland using sediment diatom assemblages.

Background Although arctic lakes have responded sensitively to 20th-century climate change, it remains uncertain how these ecological transformations compare with alpine and montane-boreal counterparts over the same interval. Furthermore, it is unclear to what degree other forcings, including atmospheric deposition of anthropogenic reactive nitrogen (Nr), have participated in recent regime shifts. Diatom-based paleolimnological syntheses offer an effective tool for retrospective assessments of past and ongoing changes in remote lake ecosystems. Methodology/Principal Findings We synthesized 52 dated sediment diatom records from lakes in western North America and west Greenland, spanning broad latitudinal and altitudinal gradients, and representing alpine (n = 15), arctic (n = 20), and forested boreal-montane (n = 17) ecosystems. Diatom compositional turnover (β-diversity) during the 20th century was estimated using Detrended Canonical Correspondence Analysis (DCCA) for each site and compared, for cores with sufficiently robust chronologies, to both the 19th century and the prior ∼250 years (Little Ice Age). For both arctic and alpine lakes, β-diversity during the 20th century is significantly greater than the previous 350 years, and increases with both latitude and altitude. Because no correlation is apparent between 20th-century diatom β-diversity and any single physical or limnological parameter (including lake and catchment area, maximum depth, pH, conductivity, [NO3 −], modeled Nr deposition, ambient summer and winter air temperatures, and modeled temperature trends 1948–2008), we used Principal Components Analysis (PCA) to summarize the amplitude of recent changes in relationship to lake pH, lake:catchment area ratio, modeled Nr deposition, and recent temperature trends. Conclusions/Significance The ecological responses of remote lakes to post-industrial environmental changes are complex. However, two regions reveal concentrations of sites with elevated 20th-century diatom β-diversity: the Arctic where temperatures are increasing most rapidly, and mid-latitude alpine lakes impacted by high Nr deposition rates. We predict that remote lakes will continue to shift towards new ecological states in the Anthropocene, particularly in regions where these two forcings begin to intersect geographically.

SCALED CHRYSOPHYTES (CHRYSOPHYCEAE AND SYNUROPHYCEAE) FROM ADIRONDACK DRAINAGE LAKES AND THEIR RELATIONSHIP TO ENVIRONMENTAL VARIABLES1

The relationships between 23 scaled chrysophyte taxa (Chrysophyceae and Synurophyceae) and measured limnological variables in 62 Adirondack, New York, drainage lakes were examined by canonical correspondence analysis (CCA). The major proportion of variation in chrysophyte species distributions was strongly related to total monomeric Al (Alm) and Mg concentrations, and their close correlates pH, Na, Ca, and acid‐neutralizing capacity (ANC). Total monomeric Al concentrations explain a greater proportion of species variation than pH, suggesting that Alm concentrations may be more important in governing the distribution of chrysophyte taxa in these lakes. Gaussian logit (GL) and linear logit (LL) regressions of the relative percentages of individual chrysophyte taxa to lakewater pH and Alm concentrations and the examination of pH–Alm response surfaces show that many chrysophyte taxa exhibit unique responses to these environmental gradients; taxa can be characterized as alkaline, circumneutral, acidic, and pH indifferent. Within each of these groups, taxa can be characterized further based upon their optima and tolerances to Alm concentrations. Chrysophyte indicator species (i.e. a taxon with a strong statistical relationship to the environmental variable of interest, a well‐defined optimum, and a narrow tolerance to the variable of interest) for pH include Mallomonas hindonii, M. crassisquama, M. pseudocoronata, and Synura uvella; M. hindonii, M. crassisquama, M. pseudocoronata, S. petersenii, and S. spinosa are good indicators of Alm concentrations. Highly significant predictive models were developed to infer lakewater pH and Alm concentrations from the relative percentages of chrysophyte scales in the study lakes. Model evaluation was based on their correlation coefficients and the root‐mean‐squared error of prediction (RMSE) derived from bootstrapping. Weighted averaging regression and calibration with tolerance down‐weighting (i.e. weighting taxa inversely to their variance) produced superior results when compared to the computationally and data‐demanding maximum likelihood methods and to simple weighted averaging regression and calibration.

Partitioning floristic variance in Norwegian upland grasslands into within-site and between-site components: are the patterns determined by environment or by land-use?

This study presents a quantitative partitioning of the variance infloristic data from grazed semi-natural vegetation of summer farms inRøldal, western Norway. The data consist of 189 taxa recorded in 1074-m2 sample plots within 10 summer farms with differentland-use histories. Thirty-five environmental variables were recorded,includingaltitude, slope, radiation, geology, soil chemistry, and past and presentland-use. A series of (partial) canonical correspondence analyses (CCAs) wereused to partition the total variation into within-farm and between-farmcomponents, and to investigate the explanatory power of different groups ofenvironmental and land-use variables at the two scales. The results show that:(1) although local gradients are of overriding importance for floristiccomposition, landscape-scale processes also contribute significantly to theobserved patterns; (2) the measured land-use and environmental factors accountfor comparable amounts of compositional variance at the two scales; and (3)evenif the relative contributions of the two classes of explanatory variables arecomparable, details differ, showing that broad-scale environmental and land-usepatterns are not just scaled-up versions of the fine-scale patterns or viceversa. These results support a multi-process view of vegetation patterns.