A modern pollen–climate calibration set based on lake sediments from the Tibetan Plateau and its application to a Late Quaternary pollen record from the Qilian Mountains

Aim Fossil pollen spectra from lake sediments on the Tibetan Plateau have been used for qualitative climate reconstruction, but no modern pollen–climate calibration set based on lake sediments is available to infer past climate quantitatively. This study aims to develop such a dataset and apply it to fossil data. Location The Tibetan Plateau, between 30 and 40° N and 87 and 103° E. Methods We collected surface sediments from 112 lakes and analysed them palynologically. The lakes span a wide range of mean annual precipitation (P_ann; 31–1022 mm), mean annual temperature (T_ann; −6.5 to 1 °C), and mean July temperature (T_July; 2.6–19.7 °C). Redundancy analysis showed that the modern pollen spectra are characteristic of their respective vegetation types and local climate. Transfer functions for P_ann, T_ann and T_July were developed with weighted averaging partial least squares. Model performance was assessed by leave-one-out cross-validation. Results The root mean square errors of prediction (RMSEP) were 104 mm (P_ann), 1.18 °C (T_ann) and 1.17 °C (T_July). The RMSEPs, when expressed as percentages of the gradient sampled, were 10.6% (P_ann), 15.7% (T_ann) and 11.9% (T_July). These low values indicate the good performance of our models. An application of the models to fossil pollen spectra covering the last c. 50 kyr yielded realistic results for Luanhaizi Lake in the Qilian Mountains on the north-eastern Tibetan Plateau (modern P_ann 480 mm; T_ann−1 °C). T_ann and P_ann values similar to present ones were reconstructed for late Marine Isotope Stage 3, with minimum values for the Last Glacial Maximum (c. 300 mm and 2 °C below present), and maximum values for the early Holocene (c. 70 mm and 0.5 °C greater than present). Main conclusions The modern pollen–climate calibration set will potentially be useful for quantitative climate reconstructions from lake-sediment pollen spectra from the Tibetan Plateau, an area of considerable climatic and biogeographical importance.     

Modern pollen assemblages as climate indicators in southern Europe

Aim and Location Our aim is to develop pollen–climate inference models for southern Europe and to test their performance and inference power by cross‐validation with modern climate data. Surface sediments collected from lakes along a climate gradient from the winter‐cold/summer‐wet Alps to winter‐wet/summer‐dry Sicily were analysed for modern pollen assemblages. Methods For each lake, mean monthly temperatures, seasonal precipitation and site‐specific climate uncertainties have been estimated. Pollen–climate relationships were studied using numerical analyses, and inference models were derived by partial least squares (PLS) and weighted‐averaging PLS (WA‐PLS) regressions for January and July temperatures (T), and for winter, spring and summer precipitation (P). In order to assess whether these variables are also of ecological importance for vegetation in the subregions, we split the data set into an Alpine and a Mediterranean subset. Results Low bootstrap cross‐validated root mean square errors of prediction (RMSEP) for January T (1.7 °C), July T (2.1 °C) and summer P (38 mm), as well as low RMSEPs expressed as a percentage of the gradient length (8–9%), indicate a good inference power. Models revealed excellent to good performance statistics for January T, July T and summer P (r²= 0.8), and for winter and spring P (r²=c. 0.5). We show that the variables with the highest explanatory power differ between the two subregions. These are summer T and P for the Alpine set, and January T, winter P and July T for the Mediterranean set. Main conclusions The study reveals the influence of climatic conditions during the growing season on modern pollen assemblages and indicates the potential of pollen data for long‐term climate reconstructions of parameters such as winter precipitation and temperature, which seem to be the main factors having an influence on the variability of Mediterranean climate. These models may therefore provide important information on past regional climate variability in southern Europe.     

Reliability of pollen ratios for environmental reconstructions on the Tibetan Plateau

Aim Pollen ratios are widely used to gain palaeovegetation and palaeoclimatic information from fossil pollen spectra, although their applicability has seldom been tested with modern pollen data. I used a data set of 113 lake‐surface sediments from the eastern Tibetan Plateau to test the reliability of several pollen ratios. Location The lake‐surface pollen spectra cover a wide range of vegetation types (temperate desert, temperate steppe, alpine desert, alpine steppe, high‐alpine meadow, sub‐alpine shrub, coniferous and mixed forest) and climatic conditions (mean July temperature, T_July: 4.0–17.4°C; mean annual precipitation, P_ann: 104–670 mm). Methods Lake‐surface sediments were analysed palynologically, and several pollen ratios were calculated. These ratios were interpreted with respect to vegetation and climatic conditions. Results The arboreal pollen sum (AP) was highest in samples from forested areas and was significantly correlated with P_ann (r² = 0.44). In non‐forested areas, samples from large lakes and from lakes surrounded by sparse vegetation had increased AP values, suggesting that AP is a useful vegetation density indicator. Artemisia/Chenopodiaceae (A/C) ratios were lowest in desert areas and were positively correlated with P_ann (r² = 0.25). The aridity pollen index was inappropriate for inferring (palaeo‐)climatic information from samples on the eastern Tibetan Plateau as it had no significant correlation with the environmental factors. Artemisia/Cyperaceae (A/Cy) ratios had a significant correlation with T_July (r² = 0.23), but only a weak correlation with P_ann, which indicates that the A/Cy ratio is applicable as a temperature indicator. Furthermore, it is a valuable tool for the differentiation of high‐alpine meadow from steppe vegetation. Main conclusions AP sum, A/C ratio and A/Cy ratio are useful tools for qualitative and semi‐quantitative palaeoenvironmental reconstruction on the Tibetan Plateau; however, the results obtained should not be interpreted quantitatively.     

Three‐dimensional change in temperature sensitivity of northern vegetation phenology

Understanding how the temperature sensitivity of phenology changes with three spatial dimensions (altitude, latitude, and longitude) is critical for the prediction of future phenological synchronization. Here we investigate the spatial pattern of temperature sensitivity of spring and autumn phenology with altitude, latitude, and longitude during 1982–2016 across mid‐ and high‐latitude Northern Hemisphere (north of 30°N). We find distinct spatial patterns of temperature sensitivity of spring phenology (hereafter “spring S_T”) among altitudinal, latitudinal, and longitudinal gradient. Spring S_T decreased with altitude mostly over eastern Europe, whereas the opposite occurs in eastern North America and the north China plain. Spring S_T decreased with latitude mainly in the boreal regions of North America, temperate Eurasia, and the arid/semi‐arid regions of Central Asia. This distribution may be related to the increased temperature variance, decreased precipitation, and radiation with latitude. Compared to spring S_T, the spatial pattern of temperature sensitivity of autumn phenology (hereafter “autumn S_T”) is more heterogeneous, only showing a clear spatial pattern of autumn S_T along the latitudinal gradient. Our results highlight the three‐dimensional view to understand the phenological response to climate change and provide new metrics for evaluating phenological models. Accordingly, establishing a dense, high‐quality three‐dimensional observation system of phenology data is necessary for enhancing our ability to both predict phenological changes under changing climatic conditions and to facilitate sustainable management of ecosystems.     

Does climate directly influence NPP globally?

The need for rigorous analyses of climate impacts has never been more crucial. Current textbooks state that climate directly influences ecosystem annual net primary productivity (NPP), emphasizing the urgent need to monitor the impacts of climate change. A recent paper challenged this consensus, arguing, based on an analysis of NPP for 1247 woody plant communities across global climate gradients, that temperature and precipitation have negligible direct effects on NPP and only perhaps have indirect effects by constraining total stand biomass (M_tot) and stand age (a). The authors of that study concluded that the length of the growing season (l_gs) might have a minor influence on NPP, an effect they considered not to be directly related to climate. In this article, we describe flaws that affected that study's conclusions and present novel analyses to disentangle the effects of stand variables and climate in determining NPP. We re‐analyzed the same database to partition the direct and indirect effects of climate on NPP, using three approaches: maximum‐likelihood model selection, independent‐effects analysis, and structural equation modeling. These new analyses showed that about half of the global variation in NPP could be explained by M_tot combined with climate variables and supported strong and direct influences of climate independently of M_tot, both for NPP and for net biomass change averaged across the known lifetime of the stands (ABC = average biomass change). We show that l_gs is an important climate variable, intrinsically correlated with, and contributing to mean annual temperature and precipitation (T_ann and P_ann), all important climatic drivers of NPP. Our analyses provide guidance for statistical and mechanistic analyses of climate drivers of ecosystem processes for predictive modeling and provide novel evidence supporting the strong, direct role of climate in determining vegetation productivity at the global scale.     

Climate‐driven changes to the spatio‐temporal distribution of the parasitic nematode,Haemonchus contortus,in sheep in Europe

Recent climate change has resulted in changes to the phenology and distribution of invertebrates worldwide. Where invertebrates are associated with disease, climate variability and changes in climate may also affect the spatio‐temporal dynamics of disease. Due to its significant impact on sheep production and welfare, the recent increase in diagnoses of ovine haemonchosis caused by the nematode Haemonchus contortus in some temperate regions is particularly concerning. This study is the first to evaluate the impact of climate change on H. contortus at a continental scale. A model of the basic reproductive quotient of macroparasites, Q₀, adapted to H. contortus and extended to incorporate environmental stochasticity and parasite behaviour, was used to simulate Pan‐European spatio‐temporal changes in H. contortus infection pressure under scenarios of climate change. Baseline Q₀ simulations, using historic climate observations, reflected the current distribution of H. contortus in Europe. In northern Europe, the distribution of H. contortus is currently limited by temperatures falling below the development threshold during the winter months and within‐host arrested development is necessary for population persistence over winter. In southern Europe, H. contortus infection pressure is limited during the summer months by increased temperature and decreased moisture. Compared with this baseline, Q₀ simulations driven by a climate model ensemble predicted an increase in H. contortus infection pressure by the 2080s. In northern Europe, a temporal range expansion was predicted as the mean period of transmission increased by 2–3 months. A bimodal seasonal pattern of infection pressure, similar to that currently observed in southern Europe, emerges in northern Europe due to increasing summer temperatures and decreasing moisture. The predicted patterns of change could alter the epidemiology of H. contortus in Europe, affect the future sustainability of contemporary control strategies, and potentially drive local adaptation to climate change in parasite populations.     

A new methodology for reconstructing climate and vegetation from modern pollen assemblages: an example from British Columbia

Aim We used modern pollen assemblages to develop a method for climate reconstruction that reduces the spatial autocorrelation of residuals and accounts for the strong topographic and climatic variation that occurs in British Columbia, Canada. Location British Columbia, Canada, including sites both on the mainland and on adjacent islands (Queen Charlotte Islands and Vancouver Island). Methods New pollen assemblages from surface‐sediment samples collected in British Columbia were combined with other published and unpublished samples (n = 284). Multivariate rank‐distances between sample sites and a randomized set of sites within the province were calculated for climate parameters to determine whether gaps in the current network of present‐day pollen sample sites exist. Lacustrine surface‐sediment pollen assemblages (n = 145) were ordinated using non‐metric multidimensional scaling (NMDS), and a generalized additive model (GAM) was used to reconstruct modern mean warmest month temperature (MWMT) and mean annual precipitation (MAP) from the NMDS ordination. The results were compared with standard climate reconstruction techniques, including the modern analogue technique, partial least squares, weighted averaging, weighted averaging–partial least squares and factor analysis. Results Reconstructions of MWMT and MAP using NMDS and GAM were comparable to those of existing models. When reconstructing MWMT, the NMDS/GAM method had a lower root‐mean‐squared error of prediction (RMSEP), lower spatial autocorrelation and higher correlation with observed temperature values than the other methods tested. When reconstructing MAP, the partial least squares method performed better than the NMDS/GAM method for RMSEP and correlation with observed values; however, the NMDS/GAM method had a lower spatial autocorrelation of residuals. Main conclusions NMDS reveals strong relationships among modern pollen assemblages, vegetation and climate parameters. Climate models using NMDS and GAM are comparable to other palaeoecological reconstruction models, but provide lower spatial autocorrelation of residuals for both parameters tested. An inverse distance‐weighted surface of multivariate rank‐climate distances generated from the network of pollen sample sites indicates that greater sampling intensity in north‐western and central‐interior British Columbia is required in order to obtain an accurate representation of climatic and vegetation diversity in the province.     

A pre-European settlement pollen–climate calibration set for Minnesota, USA: developing tools for palaeoclimatic reconstructions

Aim The bias in modern North American pollen assemblages by landscape disturbance from Euro‐American settlement has long been overlooked in the construction of pollen–climate transfer functions. Our aim is to examine this problem and to develop an unbiased pre‐settlement pollen–climate transfer function, and to test its performance and inference power in comparison with commonly used techniques. Location Minnesota, USA, is of palaeoclimatic interest because within the state are located two continental‐scale ecotones, controlled by temperature and available moisture. Shifts of these ecotones can be tracked using palaeoecological techniques. Methods Using a data set of pre‐settlement pollen assemblages from 133 lakes, which were coupled to climate data from the earliest instrumental records (i.e. 1895–1924), a pre‐settlement pollen–climate data set was developed that lacked the influence of anthropogenic landscape disturbance. A corresponding modern pollen data set (from lake sediment core tops) and a modern climate (i.e. 1961–90) data set were also developed. The two pollen sets were compared to demonstrate the effects of landscape disturbance from human activities. Ordination (redundancy analysis with Monte Carlo permutation tests) and regression techniques (generalized linear modelling) were used to establish the relationships between the early instrumental climate variables and pre‐settlement pollen assemblages and individual taxa, respectively. Transfer functions for the most suitable climate variables (i.e. those forming a minimal set of non‐collinear climate variables that explained the greatest amount of pollen variance) were developed from the pre‐settlement data set using bootstrapping. Results Comparison of pre‐settlement pollen and modern pollen showed an over‐representation of Ambrosia, Chenopodiaceae and Poaceae, and an under‐representation of arboreal taxa (e.g. Pinus, Quercus, Ostrya) in the modern assemblages. Not surprisingly, ordination and regression techniques showed a strong relationship between the early instrumental climate variables and pre‐settlement pollen assemblages and taxa. Transfer functions were developed for May and February mean temperature and available moisture. Pre‐settlement transfer functions substantially improved the root mean squared error by 37–72% in comparison with modern transfer functions inferring pre‐settlement conditions, suggesting that the modern transfer functions have poorer predictive abilities. Main conclusions For climatic reconstructions, there can be a serious distortion of inferences based solely on modern pollen–climate data sets in regions where anthropogenic landscape disturbance has occurred. By using historical climate data, coupled with pre‐disturbance pollen assemblages, robust transfer functions for temperature and effective moisture were developed.     

Orange, yellow and white-cream: inheritance of carotenoid-based colour in sunflower pollen

Inheritance of pollen colour was studied in sunflower (Helianthus annuus L.) using three distinct pollen colour morphs: orange, yellow and white‐cream. Orange is the most common colour of sunflower pollen, while the yellow morph is less frequent. These two types were observed in the inbred lines F11 and EF2L, respectively. White‐cream pollen is a rare phenotype in nature, and was identified in a mutant, named white‐cream pollen, recovered in the R₂ generation of an in vitro regenerated plant. The F11 inbred line was used as starting material for in vitro regeneration. The carotenoid content of these three pollen morphs differed, and was extremely reduced in white‐cream pollen. The phenotype of F₁ populations obtained by reciprocal crosses revealed that the orange trait was dominant over both white‐cream and yellow. Segregation of F₂ populations of both crosses, orange × yellow and orange × white‐cream, approached a 3:1 ratio, indicating the possibility of simple genetic control. By contrast, a complementation cross between the two lines with white‐cream and yellow pollen produced F₁ plants with orange pollen. The F₂ populations of this cross‐segregated as nine orange: four white‐cream: four yellow. A model conforming to the involvement of two unlinked genes, here designated Y and O, can explain these results. Accessions with yellow pollen would have the genotype YYoo, the white‐cream pollen mutant would have yyOO and the accession with orange pollen would have YYOO. Within F₂ populations of the cross white‐cream × yellow a new genotype, yyoo, with white‐cream pollen was scored. The results of the cross yyoo × YYoo produced only F₁ plants with yellow pollen, supporting a recessive epistatic model of inheritance between two loci. In this model, yy is epistatic on O and o. In F₂ populations, the distributions of phenotypic classes suggested that the genetic control of carotenoid content is governed by major genes, with large effects segregating in a background of polygenic variation. These three pollen morphs can provide insight into the sequence in which genes act, as well into the biochemical pathway controlling carotenoid biosynthesis in anthers and the transfer of these different pigments into pollenkitt.     

Are pollen-based climate models improved by combining surface samples from soil and lacustrine substrates?

Differences between pollen assemblages obtained from lacustrine and terrestrial surface sediments may affect the ability to obtain reliable pollen-based climate reconstructions. We test the effect of combining modern pollen samples from multiple depositional environments on various pollen-based climate reconstruction methods using modern pollen samples from British Columbia, Canada and adjacent Washington, Montana, Idaho and Oregon states. This dataset includes samples from a number of depositional environments including soil and lacustrine sediments.Combining lacustrine and terrestrial (soil) samples increases root mean squared error of prediction (RMSEP) for reconstructions of summer growing degree days when weighted-averaging partial-least-squares (WAPLS), weighted-averaging (WA) and the non-metric-multidimensional-scaling/generalized-additive-models (NMDS/GAM) are used but reduces RMSEP for randomForest, the modern analogue technique (MAT) and the Mixed method, although a slight increase occurs for MAT at the highest sample size. Summer precipitation reconstructions using MAT, randomForest and NMDS/GAM suffer from increased RMSEP when both lacustrine and terrestrial samples are used, but WA, WAPLS and the Mixed method show declines in RMSEP.These results indicate that researchers interested in using pollen databases to reconstruct climate variables need to consider the depositional environments of samples within the analytical dataset since pooled datasets can increase model error for some climate variables. However, since the effects of the pooled datasets will vary between climate variables and between pollen-based climate reconstruction methods we do not reject the use of mixed samples altogether. We finish by proposing steps to test whether significant reductions in model error can be obtained by splitting or combining samples from multiple substrates.     

Modelling late Quaternary changes in plant distribution, vegetation and climate using pollen data from Georgia, Caucasus

Aim To use pollen data, numerical analysis and modelling to reconstruct late Quaternary vegetation and climate in a complex, mountainous environment. Location Georgia (Caucasus region). Methods Pollen data were assembled from various sources and used to map: (1) changing frequencies of individual taxa; (2) vegetation changes; and (3) reconstructed climatic parameters for the past 14,000 years. Numerical analyses were performed using two‐way indicator species analysis (twinspan ), detrended correspondence analysis (DCA), the modern analogue technique (MAT) and weighted averaging (WA). Results Mapping of pollen taxa showed that Chenopodiaceae, Artemisia and Ephedra were most abundant in the study area during the late‐glacial. Betula and Corylus expanded during the early Holocene, yielding to Abies, Carpinus, Fagus, Quercus and Castanea. Picea, Pinus, Juglans and Ostrya‐type expanded during the late Holocene. Mixed forests grew in the moist, Black Sea refugium throughout the late Quaternary. Elsewhere in Georgia, the Pleistocene–Holocene transition is recorded as a shift from desert‐steppes to oak‐xerophyte communities and mixed forests. This kind of vegetation remained relatively stable until the mid–late Holocene, when coniferous forests and mountain grasslands advanced. DCA showed that rainfall was most strongly correlated with pollen composition in the study area (r² = 0.55). No temperature signal was detected. A weighted‐averaging transfer function linking pollen percentages to annual precipitation was selected over a MAT model as it performed better when applied to a validation data set. Rainfall reconstructions indicate widespread aridity at the terminal Pleistocene, followed by a gradual increase in precipitation, peaking during the mid Holocene (7000–4000 cal. yr bp ) and generally decreasing thereafter. Main conclusions On a regional scale, the results confirm those from previous studies of palaeovegetation and palaeoclimate in Western Asia. On a local scale, reconstructions from individual sites often diverge from the regional trend because of edaphic changes, ecological succession, human impacts and other disturbances. Some of these factors are probably responsible for the increasing heterogeneity of Georgia’s vegetation in the latter half of the Holocene.     

Climatic connectivity between Africa and Europe may serve as a basis for phenotypic adjustment of migration schedules of trans-Saharan migratory birds

Most European migratory birds wintering in sub‐Saharan Africa have anticipated arrival to the breeding areas over the past decades. This phenological change may be ultimately caused by warming of the Northern Hemisphere via evolutionary changes or phenotypic plasticity in migration behavior. First arrival dates are negatively predicted by temperatures upon arrival to the breeding grounds. This seems puzzling, because migrants should be unable to predict weather conditions at long range. Migrants can enjoy diverse fitness benefits from early arriving. However, if weather conditions at destination cannot be predicted, early arrival can also entail severe costs. If meteorological conditions in Europe during breeding covary with those in sub‐Saharan Africa during late winter, long‐distance migrants may have a clue to predict meteorological conditions in their breeding areas while they are still in Africa and adjust their migration schedule consequently, an idea that has never been tested. We analyzed the correlation between March–April temperature anomalies (T_an) in Europe and February T_an in the Sahel and sub‐Sahel, where long‐distance migrants winter or stop‐over. T_an in Africa negatively predicted T_an in Europe, the association being particularly strong (unsigned effect size, z_r>0.35) for eastern Sahel and northern and eastern Europe, where the risks of early arrival may be larger. However, the strength of the correlations between T_an in the two continents has declined during the last 25 years; thus, possibly, partly compromising adaptive mechanisms of adjustment of migration. The existence of such climatic connectivity leads to several predictions, including that positive T_an in Africa should delay arrival. Consistent with this prediction, we found that first arrival dates of seven long‐distance migratory species positively covaried with February T_an in Africa. Thus, while wintering, migrants might be able to predict meteorological conditions at the beginning of the breeding season, and phenotypically adjust migration schedules to optimally tune arrival date.     

Resilience of rice (Oryza spp.) pollen germination and tube growth to temperature stress

Resilience of rice cropping systems to potential global climate change will partly depend on the temperature tolerance of pollen germination (PG) and tube growth (PTG). Pollen germination of high temperature‐susceptible Oryza glaberrima Steud. (cv. CG14) and Oryza sativa L. ssp. indica (cv. IR64) and high temperature‐tolerant O. sativa ssp. aus (cv. N22), was assessed on a 5.6–45.4 °C temperature gradient system. Mean maximum PG was 85% at 27 °C with 1488 μm PTG at 25 °C. The hypothesis that in each pollen grain, the minimum temperature requirements (T_n) and maximum temperature limits (T_x) for germination operate independently was accepted by comparing multiplicative and subtractive probability models. The maximum temperature limit for PG in 50% of grains (T_x(50)) was the lowest (29.8 °C) in IR64 compared with CG14 (34.3 °C) and N22 (35.6 °C). Standard deviation (s_x) of T_x was also low in IR64 (2.3 °C) suggesting that the mechanism of IR64's susceptibility to high temperatures may relate to PG. Optimum germination temperatures and thermal times for 1 mm PTG were not linked to tolerating high temperatures at anthesis. However, the parameters T_x(50) and s_x in the germination model define new pragmatic criteria for successful and resilient PG, preferable to the more traditional cardinal (maximum and minimum) temperatures.     

Development and evaluation of a diatom-conductivity model from lakes in West Greenland

1. The area around Kangerlussuaq (Søndre Strømfjord; West Greenland, 67°N 51°W) contains thousands of lakes ranging from coastal, dilute (conductivity < 30 μS cm^–1) oligotrophic systems to subsaline (～4000 μS cm^–1), closed basin lakes close to the ice sheet margin. In closed basins, salinity (or conductivity) is often a proxy for effective moisture, and thus palaeorecords of lake conductivity can provide valuable palaeoclimatic data. Little or nothing is known about the recent history of these lakes and hence it is difficult to evaluate how they will respond to effects of future changes. 2. Over 100 lakes have been sampled (1996–2000) between the ice sheet and the outer coast for a variety of water chemical and limnological variables. Surface sediments were taken from a subset of 40 lakes and analysed for diatoms. Diatom responses to 28 environmental variables were analysed by multivariate ordination techniques and indicate that the main gradient is highly correlated to conductivity (explaining ～12% of species variance). Despite the relatively short gradient (24–4072 μS cm^–1), diatom assemblages exhibit a clear response to conductivity. The most saline lakes do not contain a true saline flora. 3. We developed a range of weighted averaging (WA) and weighted‐averaging partial least squares (WA‐PLS) models from this training data set and found two component WA‐PLS models performed best. The effects of data transformation and omission of dissolution susceptible species (Diatoma spp.) on model performance were also examined. The error statistics for the preferred WA‐PLS (2) model (r²_jack=0.88, root mean square error of prediction (RMSEP)=0.217 log μS cm^–1) compare well with other published models. 4. A ²¹⁰Pb‐dated short core from a meromictic, subsaline lake (Braya Sø; location 67°N, 51°W, max. depth 23 m; conductivity 2600 μS cm^–1) was analysed for diatoms. Diatom preservation is poor and some taxa (e.g. Diatoma spp.) are badly corroded. Lake water conductivity was reconstructed using WA‐PLS models. Diatom‐inferred conductivity ranges from 1800 to 4400 μS cm^–1 over the last 600 years (extrapolated ²¹⁰Pb chronology). 5. The Kangerlussuaq area of West Greenland is an important area for palaeoclimatic research, located as it is between the Greenland ice sheet (ice core records) and the Davis Straits to the west. The development of a statistically robust transfer function for diatoms and conductivity will enable the reconstruction of conductivity from the many subsaline lakes around the head of the fjord and, hence, regional estimates of changing palaeoprecipitation.     

Modelling exposure to selected temperature during pregnancy: the limitations of squamate viviparity in a cool-climate environment

Behavioural thermoregulation is important for the success of cool‐climate lizards, and a basis of the cold‐climate hypothesis for the evolution of viviparity in squamate reptiles. The temperature (T_sel) selected by pregnant females in a thermal gradient is considered to be optimal for embryonic development; however, exposure to T_sel throughout pregnancy has been difficult to estimate in small‐bodied lizards as temperature‐sensitive telemetry is impractical. In addition, the value of maternal thermophily during pregnancy is controversial: some studies have shown elevated T_sel, whereas others have found lowered T_sel or no change during pregnancy. We estimated indirectly the overall exposure to T_sel during the 4–5 months of pregnancy of the cool‐climate, sub‐alpine species Oligosoma maccanni (McCann's skink, 3–6 g) from southern New Zealand. The thermal environment available to skinks was modelled using temperature loggers inside validated copper models in basking and retreat sites. Pregnant skinks were able to achieve mean T_sel (28.9 °C) in the field very infrequently (4–15% of each month during the final 4 months of pregnancy). In field thermoregulatory studies, pregnant females did not bask more frequently and did not show altered field body temperature compared with non‐pregnant adults, suggesting that all skinks (whether pregnant or not) thermoregulate maximally whenever conditions allow. Further research on cool‐climate lizards should address the significance for offspring phenotypes of low and variable exposure to T_sel during pregnancy, as well as the significance of temperatures for embryos in maternal bodies (viviparity) versus nest sites (oviparity) arising from differences in maternal body size. © 2009 The Linnean Society of London, Biological Journal of the Linnean Society, 2009, 96 , 541–552.     

Chironomid-based inference models for estimating end-of-summer hypolimnetic oxygen from south-central Ontario shield lakes

1. Subfossil chironomid head capsules were sampled from surficial sediments from 86 boreal shield lakes in south‐central Ontario, Canada. Lake characteristics ranged from shallow to very deep (> 80 m), ultraoligotrophic to mesotrophic, and with end‐of‐summer hypolimnetic oxygen conditions ranging from near‐saturation to anoxic. 2. Subfossil chironomid assemblages, comprising 44 taxa from 59 lakes, were analysed using multivariate ordination techniques such as redundancy analysis (RDA) and canonical correspondence analysis (CCA). Forward selection in RDA and CCA both showed that measures of oxygen, such as end‐of‐summer volume‐weighted hypolimnetic oxygen concentration (VWHO) and bottom oxygen concentration (botO₂), were the strongest explanatory variables for the chironomid data. Maximum depth and major ion chemistry were also important explanatory variables. 3. Oxygen inference models were developed using partial‐least‐squares regression (PLS), weighted‐averaging partial‐least‐squares regression (WA‐PLS), and weighted averaging regression (WA). Models were developed using both the full 44 taxa assemblage (which included littoral taxa) and using only 15 profundal‐type taxa. 4. Cross‐validated models (jackknifing) using full‐assemblage or profundal‐only taxa had similar statistical power (similar root mean squared error of prediction, RMSEP). The best models had moderate predictive power, with an r²_jack as high as 0.56, and an RMSEP as low as 2.15 mg L^–1 for [VWHO], and an r²_jack of 0.49 and an RMSEP of 0.24 for log([botO₂] + 1). 5. Reconstruction of [VWHO] and [botO₂] using a previously published chironomid profile that showed strong lake response to land‐clearance and logging suggests that oxygen inference models are reliable and accurate, reflecting the qualitative changes occurring in subfossil assemblages. However, the profundal‐only models may be misleading in situations where the ratio of littoral‐to‐profundal subfossils changes drastically in response to lake disturbance.     

Response of in vitro pollen germination and pollen tube growth of groundnut (Arachis hypogaea L.) genotypes to temperature

Air temperatures of greater than 35 °C are frequently encountered in groundnut‐growing regions, especially in the semi‐arid tropics. Such extreme temperatures are likely to increase in frequency under future predicted climates. High air temperatures result in failure of peg and pod set due to lower pollen viability. The response of pollen germination and pollen tube growth to temperature was quantified in order to identify differences in pollen tolerance to temperature among 21 groundnut genotypes. Plants were grown from sowing to harvest in a poly‐tunnel under an optimum temperature of 28/22 °C (day/night). Pollen was collected at anther dehiscence and was exposed to temperatures from 10° to 47·5 °C at 2·5 °C intervals. The results showed that a modified bilinear model most accurately described the response to temperature of percentage pollen germination and maximum pollen tube length. Genotypes were found to range from most tolerant to most susceptible based on both pollen characters and membrane thermostability. Mean cardinal temperatures (T_min, T_opt and T_max) averaged over 21 genotypes were 14·1, 30·1 and 43·0 °C for percentage pollen germination and 14·6, 34·4 and 43·4 °C for maximum pollen tube length. The genotypes 55‐437, ICG 1236, TMV 2 and ICGS 11 can be grouped as tolerant to high temperature and genotypes Kadiri 3, ICGV 92116 and ICGV 92118 as susceptible genotypes, based on the cardinal temperatures. The principal component analysis identified maximum percentage pollen germination and pollen tube length of the genotypes, and T_max for the two processes as the most important pollen parameters in describing a genotypic tolerance to high temperature. The T_min and T_opt for pollen germination and tube growth, rate of pollen tube growth were less predictive in discriminating genotypes for high temperature tolerance. Genotypic differences in heat tolerance‐based on pollen response were poorly related (R² = 0·334, P = 0·006) to relative injury as determined by membrane thermostability.     

Representation of tundra vegetation by pollen in lake sediments of northern Alaska

Aim To understand better the representation of arctic tundra vegetation by pollen data, we analysed pollen assemblages and pollen accumulation rates (PARs) in the surface sediments of lakes. Location Modern sediment samples were collected from seventy‐eight lakes located in the Arctic Foothills and Arctic Coastal Plain regions of northern Alaska. Methods For seventy of the lakes, we analysed pollen and spores in the upper 2 cm of the sediment and calculated the relative abundance of each taxon (pollen percentages). For eleven of the lakes, we used ²¹⁰Pb analysis to determine sediment accumulation rates, and analysed pollen in the upper 10–15 cm of the sediment to estimate modern PARs. Using a detailed land‐cover map of northern Alaska, we assigned each study site to one of five tundra types: moist dwarf‐shrub tussock‐graminoid tundra (DST), moist graminoid prostrate‐shrub tundra (PST) (coastal and inland types), low‐shrub tundra (LST) and wet graminoid tundra (WGT). Results Mapped pollen percentages and multivariate comparison of the pollen data using discriminant analysis show that pollen assemblages vary along the main north–south vegetational and climatic gradients. On the Arctic Coastal Plain where climate is cold and dry, graminoid‐dominated PST and WGT sites were characterized by high percentages of Cyperaceae and Poaceae pollen. In the Arctic Foothills where climate is warmer and wetter, shrub‐dominated DST, PST and LST were characterized by high percentages of Alnus and Betula pollen. Small‐scale variations in tundra vegetation related to edaphic variability are also represented by the pollen data. Discriminant analysis demonstrated that DST sites could be distinguished from foothills PST sites based on their higher percentages of Ericales and Rubus chamaemorus pollen, and coastal PST sites could be distinguished from WGT sites based on their higher percentages of Artemisia. PARs appear to reflect variations in overall vegetation cover, although the small number of samples limits our understanding of these patterns. For coastal sites, PARs were higher for PST than WGT, whereas in the Arctic Foothills, PARs were highest in LST, intermediate in DST, and lowest in PST. Main conclusion Modern pollen data from northern Alaska reflect patterns of tundra vegetation related to both regional‐scale climatic gradients and landscape‐scale edaphic heterogeneity.