Development of a chironomid-based air temperature inference model for the central Canadian Arctic

Subfossil midge remains were identified in surface sediment recovered from 88 lakes in the central Canadian Arctic. These lakes spanned five vegetation zones, with the southern-most lakes located in boreal forest and the northern-most lakes located in mid-Arctic tundra. The lakes in the calibration are characterized by ranges in depth, summer surface-water temperature (SSWT), average July air temperature (AJAT) and pH of 15.5 m, 10.60°C, 8.40°C and 3.69, respectively. Redundancy analysis (RDA) indicated that maximum depth, pH, AJAT, total nitrogen-unfiltered (TN-UF), Cl and Al capture a large and statistically significant fraction of the overall variance in the midge data. Inference models relating midge abundances and AJAT were developed using different approaches including: weighted averaging (WA), weighted averaging-partial least squares (WA-PLS) and partial least squares (PLS). A chironomid-based inference model, based on a two-component WA-PLS approach, provided robust performance statistics with a high coefficient of determination (r ² = 0.77) and low root mean square error of prediction (RMSEP = 1.03°C) and low maximum bias. The use of a high-resolution gridded climate data set facilitated the development of the midge-based inference model for AJAT in a region with a paucity of meteorological stations and where previously only the development of a SSWT inference model was possible. David Porinchu and Nicolas Rolland contributed equally to the work.     

Modern influences on chironomid distribution in western Ireland: potential for palaeoenvironmental reconstruction

Ireland provides a unique setting for the study of past climates, as its climate is dominated by westerly airflow from the North Atlantic and readily responsive to changes in North Atlantic circulation patterns. Although there has been substantial research on Ireland’s past environments, quantitative palaeolimnological research, especially chironomid-based research, has been lacking. In order to further develop chironomid-based palaeolimnological investigations, a calibration set was constructed to determine the dominant environmental controls on modern chironomids in western Ireland. Chironomid subfossils were collected from surface sediments of 50 lakes. The lakes were characterised with 36 environmental variables, including physical attributes, lake water characteristics, lake sediment characteristics and land cover within each catchment. In this exploratory study, no specific environmental variable was targeted and lakes were chosen to span gradients of latitude, elevation, depth and trophic status. Redundancy analysis showed that six environmental variables—mean July air temperature, lake depth, dissolved organic carbon, and percentage catchment land cover of agriculture, peat bog and scrubland—captured a large and statistically significant portion of the variance in the chironomid data. July temperature and agricultural land cover were the most dominant environmental variables, with July temperature proving the most suitable for inference model development. A classical weighted-averaging model was developed to estimate July air temperature, with a coefficient of determination (r _jack ² ) of 0.60 and root mean square error of prediction (RMSEP) of 0.57 °C. Results suggest that summer temperature is the dominant influence on chironomid distribution across a wide variety of lake types, and the relatively small RMSEP should allow for more accurate reconstructions of Ireland’s relatively subdued Holocene temperature fluctuations.     

Chironomid-based water depth reconstructions: an independent evaluation of site-specific and local inference models

Water depth is an important environmental variable that explains a significant portion of the variation in the chironomid fauna of shallow lakes. We developed site-specific and local chironomid water-depth inference models using 26 and 104 surface-sediment samples, respectively, from seven kettlehole lakes in the Plymouth Aquifer, southeast Massachusetts, USA. Our site-specific model spans a depth gradient of 5.6?m, has an $ {\text{r}}_{\text{jack}}^{2} $ of 0.90, root mean square error of prediction (RMSEP) of 0.5?m and maximum bias of 0.7?m. Our local model has a depth gradient of 11.7?m, an $ {\text{r}}_{\text{jack}}^{2} $ of 0.71, RMSEP of 1.6?m and maximum bias of 2.9?m. Principal coordinates of neighbourhood matrices (PCNM) analysis showed that there is no influence of spatial autocorrelation on the site-specific model, but PCNM variables explained a significant amount of variance (4.8%) in the local model. This variance, however, is unique from the variance explained by water depth. We applied the inference models to a Holocene chironomid record from Crooked Pond, a site for which multiple, independent palaeohydrological reconstructions are available. The chironomid-based reconstructions are remarkably similar and show stable water depths of ~5?m, interrupted by a 2-m decrease between 4,200 and 3,200?cal a BP. Sedimentological evidence of water level fluctuations at Crooked Pond, obtained using the so-called Digerfeldt approach, also shows a drop in water depths around that time. The period of reconstructed lower water levels coincides with the abrupt decline in moisture-dependent hemlock in this region, providing further evidence for this major palaeohydrological event. The site-specific model has the best performance statistics, but the high percent abundance of fossil taxa from the long core that are absent or rare in the training set makes the site-specific reconstruction unreliable for the period before 4,400?cal a BP. The fossil taxa are well represented in the local model, making it the preferred inference model. The strong similarity between the chironomid-based reconstructions and the independent palaeohydrological records highlights the potential for using chironomid-based inference models to determine past lake depths at sites where temperature was not an influencing factor.     

Influence of industrial activity and pollution on the paleoclimate reconstruction from a eutrophic lake in lowland England,UK

Reliable estimates of Holocene temperatures are important for understanding past climate dynamics, the response of biota to climate change, and validating climate models. Chironomids in lake sediment cores are used widely to quantify past summer temperatures, for which high-latitude and/or high-altitude lakes, remote from human influence, are usually considered appropriate. Temperature inferences from lowland lakes are likely influenced by other variables, specifically eutrophication and industrial pollution, but their reliability has never been tested. We used a Norwegian chironomid-based transfer function (r ² = 0.91; RMSEP = 1.01 °C) to infer mean July air temperature over the last 200 years, using chironomid assemblages in a core collected from a polluted, nutrient-enriched lake at Speke Hall, Liverpool, England. The chironomid-inferred temperatures correlate significantly with the local instrumental temperature record and follow long-term national temperature trends. These results show that chironomids can be used to produce reliable estimates of past mean July air temperature, even when other variables have also influenced the composition of the chironomid community. These findings underline the value of chironomids as sensitive and reliable quantitative proxies for summer temperature.     

How does taxonomic resolution affect chironomid-based temperature reconstruction?

The resolution achievable for chironomid identifications has increased in recent years because of significant improvements in taxonomic literature. However, high taxonomic resolution requires more training for analysts. Furthermore, with greater taxonomic resolution, misidentifications and the number of rare, poorly represented taxa in chironomid calibration datasets may increase. We assessed the effects of various levels of taxonomic resolution on the performance of chironomid-based temperature inference models (transfer functions) and temperature reconstruction. A calibration dataset consisting of chironomid assemblage and temperature data from 100 lakes was examined at four levels of taxonomic detail. The coarsest taxonomic resolution primarily represented identifications to genus or suprageneric level. At the highest level of taxonomic resolution, identification to genus level was possible for 37% of taxa, and identification below genus was possible for 60% of taxa. Transfer functions were obtained using Weighted Averaging (WA) and Weighted Averaging-Partial Least Squares (WA-PLS) regression. Cross-validated performance statistics, such as the root mean square error of prediction (RMSEP) and the coefficient of determination (r ²) between inferred and observed values improved considerably from the lowest taxonomic resolution level (WA: RMSEP 1.91°C, r ² 0.78; WA-PLS: RMSEP 1.59°C, r ² 0.86) to the highest taxonomic resolution level (WA: RMSEP 1.66°C, r ² 0.84; WA-PLS: RMSEP 1.41°C, r ² 0.89). Reconstructed July air temperatures during the Lateglacial period based on fossil chironomid assemblages from Hijkermeer (The Netherlands) were similar for all levels of taxonomic resolution, except the coarsest level. At the coarsest taxonomic level, reconstruction failed to infer one of the known Lateglacial cold episodes in the record. Also, the difference in reconstructed values based on lowest and highest taxonomic resolutions exceeded sample-specific estimated standard errors of prediction in several instances. Our results suggest that chironomid-based transfer functions at the highest taxonomic resolution outperform models based on lower-resolution calibration data. However, transfer functions of intermediate taxonomic resolution produced results very similar to models based on high-resolution taxonomic data. In studies that include analysts with different levels of expertise, inference models based on intermediate taxonomic resolution, therefore, might provide an alternative to transfer functions of maximum taxonomic detail in order to ensure taxonomic consistency between calibration datasets and down-core records produced by different analysts.     

Paleotemperature reconstruction in tropical Africa using fossil Chironomidae (Insecta: Diptera)

Fossil assemblages of chironomid larvae (non-biting midges) preserved in lake sediments are well-established paleothermometers in north-temperate and boreal regions, but their potential for temperature reconstruction in tropical regions has never before been assessed. In this study, we surveyed sub-fossil chironomid assemblages in the surface sediments of 65 lakes and permanent pools in southwestern Uganda (including the Rwenzori Mountains) and central and southern Kenya (including Mount Kenya) to document the modern distribution of African chironomid communities along the regional temperature gradient covered by lakes situated between 489 and 4,575 m above sea level (a.s.l). We then combined these faunal data with linked Surface-Water Temperature (SWTemp: range 2.1–28.1°C) and Mean Annual Air Temperature (MATemp: range 1.1–24.9°C) data to develop inference models for quantitative paleotemperature reconstruction. Here we compare and discuss the performance of models based on different numerical techniques [weighted-averaging (WA), weighted-averaging partial-least-squares (WA-PLS) and a weighted modern analogue technique (WMAT)], and on subsets of lakes with varying gradient lengths of temperature and other environmental variables. All inference models calibrated against MATemp have a high coefficient of determination ( r_\textjack² r_{\text{jack}}^{2}  = 0.81–0.97), low maximum bias (0.84–2.59°C), and low root-mean-squared error of prediction (RMSEP = 0.61–1.50°C). The statistical power of SWTemp models is generally weaker ( r_\textjack² r_{\text{jack}}^{2}  = 0.77–0.95; maximum bias 1.55–3.73°C; RMSEP = 1.39–1.98°C), likely because the surface-water temperature data are spot measurements failing to catch significant daily and seasonal variation. Models based on calibration over the full temperature gradient suffer slightly from the limited number of study sites at intermediate elevation (2,000–3,000 m), and from the presence of morphologically indistinguishable but ecologically distinct taxa. Calibration confined to high-elevation sites (>3,000 m) has poorer error statistics, but is less susceptible to biogeographical and taxonomic complexities. Our results compare favourably with chironomid-based temperature inferences in temperate regions, indicating that chironomid-based temperature reconstruction in tropical Africa can be achieved.     

Diatom-inference models for surface-water temperature and salinity developed from a 57-lake calibration set from the Sierra Nevada, California, USA

Physical, chemical, and biological data were collected from a suite of 57 lakes that span an elevational gradient of 1360 m (2115 to 3475 m a.s.l.) in the eastern Sierra Nevada, California, USA as part of a multiproxy study aimed at developing transfer functions from which to infer past drought events. Multivariate statistical techniques, including canonical correspondence analysis (CCA), were used to determine the main environmental variables influencing diatom distributions in the study lakes. Lakewater depth, surface-water temperature, salinity, total Kjeldahl nitrogen, and total phosphorus were important variables in explaining variance in the diatom distributions. Weighted-averaging (WA) and weighted-averaging partial least squares (WA-PLS) were used to develop diatom-based surface-water temperature and salinity inference models. The two best diatom-inference models for surface-water temperature were developed using simple WA and inverse deshrinking. One model covered a larger surface-water temperature gradient (13.7 °C) and performed slightly poorer (r² = 0.72, RMSE = 1.4 °C, RMSEP_jack = 2.1 °C) than a second model, which covered a smaller gradient (9.5 °C) and performed slightly better (r² = 0.89, RMSE = 0.7 °C, RMSEP_jack = 1.5 °C). The best diatom-inference model for salinity was developed using WA-PLS with three components (r² = 0.96, RMSE = 4.06 mg L^–1, RMSEP_jack = 11.13 mg L^–1). These are presently the only diatom-based inference models for surface-water temperature and salinity developed for the southwestern United States. Application of these models to fossil-diatom assemblages preserved in Sierra Nevada lake sediments offers great potential for reconstructing a high-resolution time-series of Holocene and late Pleistocene climate and drought for California.     

A HIGH-RESOLUTION, GRIDDED DATASET FOR MONTHLY TEMPERATURE NORMALS (1971-2000) IN SWEDEN

A baseline climatology is required in evaluating climate variability and changes on regional and local scales. Gridded climate normals, i.e. averages over a 30‐year period, are of special interest since they can be readily used for validation of climate models. This study is aimed at creating an updated gridded dataset for Swedish monthly temperature normals over the period 1971–2000, based on standard 2‐m air temperature records at 510 stations in mainland Sweden. Spatial trends of the normal temperatures were modelled as functions of latitude, longitude and elevation by multiple linear regression. The study shows that the temperature normals are strongly correlated with latitude throughout the year and especially in cold months, while elevation was a more important factor in June and July. Longitude played a minor role and was only significant in April and May. Regression equations linking temperature to latitude, longitude and elevation were set up for each month. Monthly temperature normals were detrended by subtracting spatial trends given by the regressions. Ordinary kriging was then applied to both original data (simple method) and de‐trended data (composite method) to model the spatial variability and to perform spatial gridding. The multiple regressions showed that between 82% (summer) and 96% (winter) of the variance in monthly temperature normals could be explained by latitude and elevation. Unexplained variances, i.e. the residuals, were modelled with ordinary kriging with exponential semivariograms. The composite grid estimates were calculated by adding the multiple linear trends back to the interpolated residuals at each grid point. Kriged original temperature normals provided a performance benchmark. The cross–validation shows that the interpolation errors of the normals are significantly reduced if the composite method rather than the simple one was used. A gridded monthly dataset with 30‐arcsecond spacing was created using the established trends, the kriging model and a digital topographic dataset.     

气候变化下的祁连山地区近40 年多年冻土分布变化模拟

冻土是一种对气候变化极为敏感的土体介质,故气候的变化过程能反映和模拟冻土的分布及变化趋势。基于高程-响应模型,运用高分辨率的高程数据（DEM）、经度数据（Longitude）、纬度数据（Latitude）、年平均气温数据（MAAT）和气温垂直递减率数据（VLRT）对祁连山地区近40 年的多年冻土分布状况进行了数值模拟。分析表明：① 该高程-响应模型模拟的冻土范围和变化趋势与相关研究所引入逻辑回归模型的模拟结果基本一致。② 该模型模拟的1970s、1980s、1990s,2000s 的祁连山地区冻土分布面积分别为9.75×10⁴ km²、9.35×10⁴ km²、8.85×10⁴ km²、7.66×10⁴ km²。在这40 年中,冻土的分布范围呈现出明显减少的趋势。③ 从1970s 到1980s、1980s 到1990s、1990s 到2000s 三个时间段内,冻土分布范围的退缩速率分别为4.1%、5.3%、13.4%,其呈现逐渐增速的趋势,1990s 到2000s 出现了跳跃式增长。本研究可为分析长时间序列祁连山地区的多年冻土变化提供科学参考依据。     

A comparison of three Eurasian chironomid–climate calibration datasets on a W–E continentality gradient and the implications for quantitative temperature reconstructions

Multiple regional chironomid–climate calibration datasets are available to reconstruct quantitatively July air temperatures from fossil chironomid assemblages. We examined the relationship between July air temperature and the 40 most common chironomid taxa in three independent Eurasian calibration (training) sets. The estimated temperature optimum of each chironomid taxon is systematically lower (by ~1–2 °C) in a Norwegian calibration set compared to Finnish and Russian calibration sets. This result might partly be explained by the fact that the Norwegian calibration set extends further at the cold end of the temperature gradient. A difference in continentality between the Russian sites and the European sites might also contribute to this pattern. The number of taxa that show a statistically significant unimodal response to temperature is higher in the Norwegian calibration set (34 out of 40 taxa) compared to the modern Finnish (11 of 37 taxa; 3 common taxa absent) and the Russian calibration set (20 of 40 taxa), probably due to the longer temperature gradient incorporated in the Norwegian calibration set. We applied all three calibration sets to fossil chironomid assemblages from the high-latitude study site of Sokli (northeast Finland), a site with a unique series of lacustrine deposits covering (amongst others) the Holocene, part of early MIS 3 (at ~53 ka) and MIS 5d–c (at ~110–95 ka) and with independent proxy-records for comparison. In the early Holocene and during MIS 5c, the chironomid-based temperature inferences from all three inference models had similar values. Temperature reconstructions based on the Norwegian calibration set are 2–4 °C lower for the late Holocene, early MIS 3 and MIS 5d than the inferred temperatures based on the other calibration sets. Although the lakes included in the Finnish calibration set are located closest to the site of Sokli, evaluation tests and a comparison with independent proxy data suggests that the Norwegian calibration set provides the most suitable analogues for reconstruction purposes for most of the fossil assemblages. Our results imply that when choosing a calibration set for quantitative climate reconstructions on glacial timescales, regional proximity of the fossil site may not be a sufficient basis, and the length of the temperature gradient of the calibration dataset and factors such as the continentality gradient covered by the calibration set must also be considered.     

Comparing palaeolimnological and instrumental evidence of climate change for remote mountain lakes over the last 200 years

This paper compares the palaeolimnological evidence for climate change over the last 200 years with instrumental climate data for the same period at seven European remote mountain lakes. The sites are Øvre Neådalsvatn (Norway), Saanajärvi (Finland), Gossenköllesee (Austria), Hagelseewli (Switzerland), Jezero v Ledvici (Slovenia), Estany Redó (Spain, Pyrenees), and Niné Terianske Pleso (Slovakia). We used multiple regression analysis to transfer homogenised lowland air temperature records to each of the sites, and these reconstructions were validated using data from on-site automatic weather stations. These data showed that mean annual temperature has varied over the last 200 years at each site by between 1 and 2 °C, typical of the high frequency variability found throughout the Holocene, and appropriate, therefore, to test the sensitivity of the various proxy methods used. Sediment cores from each site were radiometrically dated using ²¹⁰Pb, ¹³⁷Cs and ²⁴¹Am and analysed for loss-on-ignition, C, N, S, pigments, diatoms, chrysophytes, Cladocera and chironomids. Comparisons between the proxy data and the instrumental data were based on linear regression analysis with the proxy data treated as response variables and the instrumental data (after smoothing using LOESS regressions) as predictor variables. The results showed few clear or consistent patterns with generally low or very low r² values. Highest values were found when the data were compared after smoothing using a broad span, indicating that some of the proxy data were capturing climate variability but only at a relatively coarse time resolution. Probable reasons for the weak performance of the methods used include inaccurate dating, especially for earlier time periods, the influence of confounding forcing factors at some sites e.g., air pollution, earthquakes, and the insensitivity of some methods to low amplitude climate forcing. Nevertheless, there were trends in some proxy records at a number of sites that had a relatively unambiguous correspondence with the instrumental climate records. These included organic matter and associated variables (C and N) and planktonic diatom assemblages at the majority of sites and chrysophytes and chironomids at a few sites. Overall for longer term studies of the Holocene, these results indicate the need to be cautious in the interpretation of proxy records, the importance of proxy method validation, the continuing need to use reinforcing multi-proxy approaches, and the need for careful site and method selection.     

Diatom transfer-functions for quantifying past air temperature, pH and total organic carbon concentration from lakes in northern Sweden

The relationships between diatoms (Bacillariophyceae) in surface sediments of lakes and summer air temperature, pH and total organic carbon concentration (TOC) were explored along a steep climatic gradient in northern Sweden to provide a tool to infer past climate conditions from sediment cores. The study sites are in an area with low human impact and range from boreal forest to alpine tundra. Canonical correspondence analysis (CCA) constrained to mean July air temperature and pH clearly showed that diatom community composition was different between lakes situated in conifer-, mountain birch- and alpine-vegetation zones. As a consequence, diatoms and multivariate ordination methods can be used to infer past changes in treeline position and dominant forest type. Quantitative inference models were developed to estimate mean July air temperature, pH and TOC from sedimentary diatom assemblages using weighted averaging (WA) and weighted averaging partial least squares (WA-PLS) regression. Relationships between diatoms and mean July air temperature were independent of lake-water pH, TOC, alkalinity and maximum depth. The results demonstrated that diatoms in lake sediments can provide useful and independent quantitative information for estimating past changes in mean July air temperature (R² _jack = 0.62, RMSEP = 0.86 °C; R² and root mean squared error of prediction (RMSEP) based on jack-knifing), pH (R² _jack = 0.61, RMSEP = 0.30) and TOC (R² _jack = 0.49, RMSEP = 1.33 mg l^-1). The paper focuses mainly on the relationship between diatom community composition and mean July air temperature, but the relationships to pH and TOC are also discussed.     

Efstadalsvatn – a multi-proxy study of a Holocene lacustrine sequence from NW Iceland

Multi-proxy data, both lithostratigraphic and biostratigraphic, are presented from Efstadalsvatn, a lake in NW Iceland. The sequence covers the period 10,000 to 3500 ¹⁴C yr B.P. The biostratgraphic data include the first Icelandic chironomid-based reconstruction of Holocene mean July air temperatures, using a Norwegian training set in the absence of modern Icelandic data. The results show that deglaciation and ecosystem development probably began before 10,000 ¹⁴C yr B.P. and that July temperatures were around 4°C at ca. 9500 ¹⁴C yr B.P. Temperatures then rose to ca. 8°C at the time of the deposition of the Saksunarvatn tephra (9100 ¹⁴C yr B.P.), reaching ca. 10°C by 8500 ¹⁴C yr B.P., high enough for the growth of tree birch, although successful birch colonisation did not take place until 6750 ¹⁴C yr B.P. There is some evidence for cooling immediately preceding 9100 ¹⁴C yr B.P. There is little firm biostratigraphic evidence for the 8200 cal. B.P. event, although this may be due to a relatively low resolution pollen sampling interval, but there are changes at this time in the total carbon (TC) and mass susceptibility (MS) data. Optimal temperatures and relative vegetation stability may have occurred between 8000–6100 ¹⁴C yr B.P. but the chironomid assemblages indicate higher temperatures after 5000 ¹⁴C yr B.P. This latter interpretation may, however, reflect delayed colonisation of thermophilous taxa and requires further investigation. There is evidence in the lithostratigraphy for greater local terrestrial instability after 6100 ¹⁴C yr B.P. but it seems unlikely that this led to the redevelopment of ice in the catchment. The biostratigraphic records appear to show a degree of resistence to climate forcing throughout the early and middle Holocene. The new chironomid-based temperature reconstruction needs to be refined by further studies in Iceland, particularly the development of an Icelandic training set, but has already demonstrated the problems of paleoclimatic interpretations based on pollen and/or macrofossil evidence alone.     

Empirical models for describing recent sedimentation rates in lakes distributed across broad spatial scales

Over the last 20 years there has been a surge of interest in paleolimnology and as a result a large accumulation of lake sedimentation records. This emerging archive has allowed us to develop empirical models to describe which variables explain significant variation in sedimentation rates over the past ∼150 years across large spatial scales. We hypothesized that latitude would be a significant explanatory variable of profundal zone lake sedimentation rates across a temperate to polar gradient. We further hypothesized that along a more longitudinally-constrained dataset (i.e. east coast of North America), latitude would explain a greater proportion of the variance. To test these hypotheses, we collated data from 125 natural, average-sized lakes (with surface area <500 km²) by recording authors’ estimates of sedimentation rates (measured as mm/year) or by digitizing recent sediment profiles and calculating sedimentation rates over the past ∼150 years. We found that, at both scales, latitude was the strongest predictor of lake sedimentation rates (full dataset: r ² = 0.28, P = 0.001, n = 125; east coast dataset: r ² = 0.58, P < 0.001, n = 43). By conducting a multiple linear regression analysis, we found that 70% of the variance in sedimentation rates from the east coast transect was explained by latitude and elevation alone. This latter model is of sufficient strength that it is a robust predictive tool. Given that climate and land-use strongly co-vary with latitude and that both of these factors have previously been shown to influence lake sedimentation rates, it appears that latitude is a surrogate measure for climate and land-use changes. We also show support for land-use as an important variable influencing sedimentation rates by demonstrating large increases in recent versus Holocene accumulation rates. These results indicate that it is possible to make generalizations about sedimentation rates across broad spatial scales with even limited geographic data.     

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

Surface sediments from 68 small lakes in the Alps and 9 well-dated sediment core samples that cover a gradient of total phosphorus (TP) concentrations of 6 to 520 g TP l^-1 were studied for diatom, chrysophyte cyst, cladocera, and chironomid assemblages. Inference models for mean circulation log₁₀ TP were developed for diatoms, chironomids, and benthic cladocera using weighted-averaging partial least squares. After screening for outliers, the final transfer functions have coefficients of determination (r², as assessed by cross-validation, of 0.79 (diatoms), 0.68 (chironomids), and 0.49 (benthic cladocera). Planktonic cladocera and chrysophytes show very weak relationships to TP and no TP inference models were developed for these biota. Diatoms showed the best relationship with TP, whereas the other biota all have large secondary gradients, suggesting that variables other than TP have a strong influence on their composition and abundance. Comparison with other diatom – TP inference models shows that our model has high predictive power and a low root mean squared error of prediction, as assessed by cross-validation.     

Lacustrine oxygen isotope record of 20th-century climate change in central EuropeL evaluation of climatic controls on oxygen isotopes in precipitation

We report oxygen isotope data from a 108-yr (1885–1993) sequence with annual laminae of bio-induced authigenic calcite in a frozen core from Baldeggersee, a small lake in Central Switzerland. These isotope results provide proxy data on the isotopic composition of past precipitation in the Baldeggersee catchment region and are quantitatively compared with instrumental climate data (i.e. mean annual air temperature and atmospheric circulation pattern indices) to evaluate climatic controls on oxygen isotopes in precipitation.Monitoring the isotope hydrology of Baldeggersee demonstrates that the oxygen isotopic composition of the lake water is controlled by the isotopic composition of local atmospheric precipitation (¹⁸O_p) and that the isotopic signal of precipitation is preserved, albeit damped, in the lake calcite oxygen isotope record (¹⁸O_c). Comparison of the calcite oxygen isotope proxy for ¹⁸O_p in the catchment with historical mean annual air temperature measurements from Bern, Switzerland confirms that authigenic calcite reliably records past annual air temperature in the region. This ¹⁸O_c/temperature relationship is calculated to be 0.39/°C for the period 1900–1960, based on an isotope mass-balance model for Baldeggersee. An exception is a 0.8 anomalous negative shift in calcite ¹⁸O values since the 1960s. Possible explanations for this recent ¹⁸O_c shift, as it is not related to mean annual air temperature, include changes in ¹⁸O_p due to synoptic circulation patterns. In particular, the 0.8 negative shift coincides with a trend towards a more dominant North Atlantic Oscillation (NAO) index. This circulation pattern would tend to bring more isotopically more negative winter precipitation to the region and could account for the 0.8 offset in ¹⁸O_c data.     

Relationships between environmental variables and zooplankton subfossils in the surface sediments of 36 shallow coastal brackish lakes with special emphasis on the role of fish

Subfossil zooplankton assemblages (Cladocera 22 taxa, Rotifera 1 taxon) were identified from the surface sediments of 36 shallow (median depth = 0.7 m) Danish coastal brackish lakes differing in epilimnic salinity (SAL, range 0.2–17.4), summer-mean total phosphorus (TP, 27–327 g l^–1) and total nitrogen (TN, 0.850–2.629 mg l^–1), as well as in submerged macrophyte coverage and planktivorous fish density (PL-CPUE). Cladoceran species richness declined significantly with increasing SAL, TP and TN, while no significant correlation was found to either PL-CPUE, macrophyte coverage or lake surface area. Bonferroni-adjusted forward selection within canonical correspondence analysis (CCA) showed that 22.1% of the variation in zooplankton data was explained by PL-CPUE, SAL and TP uniquely; each variable explaining an almost equally significant amount of variation in the zooplankton data. Predictive models to infer PL-CPUE, SAL and TP were developed using variance weighted-averaging (WA) procedures. Almost similar values of boot-strapped coefficient of determination (r²_{boot-strapped} 0.22–0.38) were produced by the WA inference models of PL-CPUE, SAL and TP, while the inference models of TP produced the lowest boot-strapped root-mean-squared-error of prediction (RMSEP_{boot-strapped} 0.29–0.36 log(TP + 1), g l^–1). Yet, zooplankton TP and SAL optima (WA) were strongly correlated (r² = 0.46), while PL-CPUE optima (WA) were independent of both TP and SAL optima, indicating that only the PL-CPUE inference models are suitable for making reconstructions.     

Local level rainfall and temperature variability in drought-prone districts of rural Sidama,central rift valley region of Ethiopia

ABSTRACT

The purpose of this study is to examine local level spatiotemporal rainfall and temperature variability in drought-prone districts of rural Sidama, Central Rift Valley region of Ethiopia. The study used 129 gridded monthly rainfall and temperature data of 32 years (1983–2014). The gridded rainfall and temperature records were encoded into GIS software and evaluated through different statistical and geospatial techniques. Mann-Kendal rank test and F distribution tests were used to test temporal and spatial statistical significance, respectively, of the data. The analysis revealed that Belg and Kiremt are the main rainfall seasons, constituting 81% of the annual rainfall. Although annual, Kiremt, and Belg rainfall amounts appear to have decreased over time, the decreasing trend is statistically significant only for Belg rainfall records. On the other hand, rainfall standard anomaly results indicated seven droughts of different magnitudes: one extreme, two severe, and four moderate. The study also revealed increasing temperature trends over the years under consideration that are statistically significant. The findings of this study on rainfall contradict other findings obtained around the study area. Thus, climate change adaptations need to focus on location-specific climate data analysis so that the intended adaptive interventions can be successful.     

三个全球气候模式对中国气温季节变化模拟能力的空间差异特征分析

针对第五次国际耦合模式比较计划（CMIP5）中3个全球气候模式对中国气温季节变化模拟能力的空间差异特征进行具体分析。结果表明：BCC-CSM1.1（m）模式和GFDL-CM3模式能够再现中国气温的季节性变化,在中国东部地区模拟能力较强,平均绝对误差和均方根误差均较小,在中国西部地区模拟能力较弱,平均绝对误差和均方根误差较大。与BCC-CSM1.1（m）和GFDL-CM3模式相比,HADGEM2-ES模式再现中国地区气温季节变化的能力最弱,平均绝对误差和均方根误差在西部部分地区、内蒙古地区和东北地区较大,在华南地区南部较小。在相同模式下,日平均气温模拟效果最好,其次是日最低气温,日最高气温模拟效果最差。纬度、经度、海拔和坡度对气候模式模拟效果的影响存在模式间的差异,而坡向和地形遮蔽度对模式的模拟效果无明显影响。     

Diatom and chrysophyte functions and inferences of post-industrial acidification and recent recovery trends in Killarney lakes (Ontario, Canada)

The surface sediment diatom and chrysophyte assemblages from 33 Sudbury lakes were added to our published 72 lake data set to expand and refine the diatom and chrysophyte-based inference models that we had earlier developed for this region. Our calibration data set now includes 105 lakes, representing gradients for multiple environmental variables (e.g., lakewater pH, metals, and transparency). The revised models are based on the weighted averaging calibration and regression approach and include bootstrap error estimates. The pH model was the strongest (r² _boot = 0.75, RMSE _boot = 0.50). The chrysophyte-inferred pH model (r² _boot = 0.79, RMSE _boot = 0.48) that we developed was as robust as the diatom pH model. Diatom and chrysophyte inferred pH models were then applied to top (surface sediments representing current conditions) and bottom (generally from > 30 cm deep representing pre-industrial conditions) sediment diatom and chrysophyte assemblages of 19 Killarney area lakes near Sudbury. The top and bottom inferred pH results were compared to early-1970s measured pH data. These data suggest that, although many of the poorly buffered Killarney lakes had experienced acidification, marked pH recovery has occurred in many lakes within the last 25 years. Despite the stunning pH recovery, the present-day diatom and chrysophyte assemblages are significantly different from assemblages present during pre-industrial times. Our results suggest that biological recovery may require more time than chemical recovery. It is also likely that these lakes may never recover biologically because other anthropogenic stressors (e.g., climate warming and increased exposure to UV-B radiation) may now have greater influence on biological communities in Killarney/Sudbury area lakes than acidification.