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.     

Diatom–environmental relationships and nutrient transfer functions from contrasting shallow and deep limestone lakes in Ontario, Canada

Diatom assemblages were analysed in the surface sediments of 44 alkaline lakes in south-western Ontario, Canada, and combined with a pre-existing 58 south-eastern Ontario lake set: (1) to determine if shallow, polymictic Ontario lakes contain different diatom assemblages from deeper, dimictic lakes, and if so, which environmental variables most influence assemblages; (2) to improve the existing transfer functions; (3) to construct and compare transfer functions separately for dimictic, deep lakes and for polymictic, shallow lakes. Polymictic and dimictic lakes covered a similar nutrient range (spring total phosphorus (TP)=4–54 g/l, spring total nitrogen (TN)=200–927 g/l; n=101) and spring pH levels (7.6–9; n=101). However, polymictic lakes were shallower (median mean depth = 2.9 m vs. 7.3 m in dimictic lakes). Benthic diatoms (average 60% relative abundance) dominated the polymictic lakes, whereas planktonic diatoms (average 60%) dominated dimictic lakes. A Canonical Correspondence Analyses with forward selection (p < 0.05, 999 Monte Carlo permutations) identified TP, alkalinity, watershed to volume ratios and lake depth as the most important measured environmental variables influencing diatom distribution in both polymictic and dimictic lakes. Additionally, pH was identified as an important variable in polymictic lakes, whereas TN was also forward selected in the dimictic lakes. Adding more lakes to the original southern Ontario calibration set improved the TN transfer function (r² _jack=0.42, root mean squared error of prediction (RMSEP)_jack=0.11 [log g TN/l]), although there was a high systematic error in the revised model (r² _residual = 0.48). However, the strongest TP model was derived from the polymictic lakes (r² _boot =0.44, RMSEP_boot=0.20 [log g TP/l]), which was the smallest lake set (n=30) with the lowest number of diatom species. The stronger TP model from the polymictic lakes may be partly due to the relatively low macrophyte cover in our polymictic lakes, which may lead to stronger benthic–pelagic coupling than in lakes with large macrophyte populations. Additionally, our study suggests that the Chrysophyceae cyst:diatom frustule ratio may be useful for indicating trends in TP levels of 35 g/l in alkaline lakes that are dimictic, but is not necessarily indicative of trophic state changes in shallow, polymictic lakes. Our study demonstrates that it may be important to construct separate diatom-based nutrient transfer functions for polymictic and dimictic lakes.     

Diatom species–environment relationships and inference models from Isachsen, Ellef Ringnes Island, Canadian High Arctic

Surface sediment diatom assemblages were examined from 26 freshwater sites near Isachsen (78°47N, 103°32W), Ellef Ringnes Island, a region of diverse and atypical water chemistry for high arctic sites. One hundred and sixty eight diatom taxa were identified from these samples, over 50% of which had not previously been recorded in the Canadian High Arctic. Variations in diatom assemblages were related to changes in measured environmental variables using multivariate techniques. Canonical correspondence analysis (CCA) indicated that five variables contributed significantly to explaining patterns of diatom variation (i.e., COND, DIC, Mn, TPF, TPU). The first CCA axis (=0.44) was primarily controlled by conductivity-related variables, while CCA axis 2 (=0.21) was related to particulate concentrations. Diatom-based inference models were generated for the reconstruction of conductivity (RMSEP_jack=0.32, r²_jack=0.76) and pH (RMSEP_jack=0.40, r²_jack=0.69). The strengths of these models indicate that it will be possible to reliably infer past trends in conductivity and pH from diatom assemblages preserved in dated sediment cores from the Isachsen region.     

Tracing lake trophic history with a chironomid–total phosphorus inference model

1. In the absence of historical water chemistry data, predictive biological indicator groups preserved in lake sediments can be employed to reconstruct the history of lake eutrophication. Diatoms are well established in this role, but to augment diatom‐based inferences of nutrient status we investigate the potential use of chironomid midges (Insecta: Chironomidae). 2. Canonical correspondence analysis (CCA) of modern chironomid assemblages in surface sediments from 44 lakes in the English Midlands and Wales, U.K., shows that five environmental variables (total phosphorus (TP), bottom dissolved oxygen, maximum lake depth, Secchi depth and surface water temperature) make a statistically significant (P < 0.05) contribution to explaining the variance in the chironomid data, of which TP makes the largest contribution (29%). 3. The relationship is used to develop a series of weighted averaging (WA) and partial least squares (PLS), (WA‐PLS) models to infer log₁₀TP. The models are evaluated by leave‐one‐out (jack‐knifing) cross‐validation. The simplest minimal adequate model is provided by WA with unweighted inverse deshrinking of root mean square error of prediction (RMSEP_jack=0.34 and r²_jack=0.60). 4. Using this model, the trophic history of Betton Pool, Shropshire, U.K., is reconstructed from the mid‐19th century to the present day and the results from the chironomid‐TP model are compared with inferences from a diatom‐TP model ( 13 ). Both reconstructions suggest that there was a gradual rise in TP since 1850 AD until about 1974, followed by a more pronounced and rapid increase that has continued until the present. Inferred TP values from the WA chironomid inference model agree with diatom‐inferred values. 5. The study demonstrates that fossil chironomid assemblages can be used to investigate quantitatively the trophic history of lakes.     

BENTHIC DIATOM AUTECOLOGY AND INFERENCE MODEL DEVELOPMENT FROM THE CANADIAN HIGH ARCTIC ARCHIPELAGO1

Diatom assemblages were analyzed from 64 lakes and ponds from Alert, Ellesmere Island and Mould Bay, Prince Patrick Island in the Canadian High Arctic Archipelago. Diverse water chemistry conditions and diatom communities were present in these sites. Small benthic taxa typically dominated diatom communities; however, assemblages were markedly different between Alert and Mould Bay sites in response to disparate water chemistry characteristics in the two regions. The most abundant taxa belonged to the genera Navicula, Cymbella, Achnanthes, Nitzschia, and Pinnularia. Canonical correspondence analysis indicated that pH, specific conductivity, dissolved organic carbon, and total phosphorus were the most important limnological variables in determining species composition. Diatom inference models were developed for pH, specific conductivity, and dissolved organic carbon using weighted averaging and weighted averaging partial least squares techniques; these had root mean square error of prediction/r²_boot values of 0.40/0.77, 0.28/0.70, and 0.24/0.55, respectively. These models are applicable to sites with large ranges of taxonomic and limnological variation and will allow the reconstruction of past changes of climate‐related limnological parameters from biostratigraphic records in future paleolimnological studies.     

Validation of a diatom–phosphorus calibration set for Sweden

1. A weighted averaging (WA) regression and calibration model for diatoms and total phosphorus (TP) was developed from a dataset of 45 surface‐sediment samples from Swedish lakes. Jack‐knifed error statistics were comparable with those for similar diatom–TP datasets: r²_jack=0.47, root mean squared error of prediction (RMSEP)=0.24 log₁₀μg TP L^–1 and mean bias=–0.002 log₁₀ μg TP L^–1 for the simple WA model; r²_jack=0.36, RMSEP=0.27 log₁₀ μg TP L^–1 and mean bias=0.017 log₁₀ μg TP L^–1 for WA with tolerance downweighting. 2. The model was used to estimate TP concentrations for the Ekoln basin of Lake Mälaren using a ²¹⁰Pb‐dated sediment core record. Highly eutrophic conditions developed in the basin in the 1960s as a result of nutrient inputs from cultivated land and the city of Uppsala. A reduction in the supply of phosphorus from sewage outlets in the late 1960s resulted in less eutrophic conditions. 3. The model results indicated levels of 50–60 μg TP L^–1 prior to 1900. The rapid eutrophication of the lake basin after the 1950s and the subsequent recovery were evident from the diatom data. 4. Diatom‐inferred TP (DI–TP) values were validated by comparison with monitored data for the period 1966–95. The diatom model tended to underestimate TP at high levels (> 80 μg L^–1) but overestimate at lower concentrations. 5. A good agreement was observed between the trends in TP concentration and the DI–TP concentration and the timing of the maximum was well reflected by the diatom‐based reconstruction. A significant correlation (r²=0.69, P < 0.01) was found between DI–TP and measured TP at this site.     

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.     

Inferring a single variable from an assemblage with multiple controls: getting into deep water with cladoceran lake-depth transfer functions

Transfer functions have proved very useful for quantitative reconstruction of past environments. Inferring values of a single parameter based on changes in a community with multiple controls may result in unreliable inferences. To assess this unreliability cladoceran surface sediment assemblages from 53 lakes in Greenland, which have substantial variations in lake depth and fish abundance, both of which shape cladoceran communities, were analysed in this study. Redundancy analysis (RDA) revealed that maximum lake depth and either fish abundance or fish presence/absence exerted substantial and significant control on the cladoceran assemblage. Partial RDA showed that maximum lake depth and fish abundance uniquely explained 7.9 and 5.1%, respectively, with 5.3% variance being shared. A transfer function to infer lake depth from cladoceran sub-fossils was constructed and performed moderately well [coefficient of determination (r ²) = 0.65; root mean square error of prediction (RMSEP) = 0.32 log maximum depth] on the full dataset. When outliers, defined by a bootstrapped prediction error greater than 25% of the total depth gradient, were excluded, the model performed well (r ² = 0.74, RMSEP = 0.25 log maximum depth). The improved transfer function was then applied to sedimentary assemblage from a sediment core from Lake Bores?, in North-eastern Greenland, covering 9,000 years. A large increase in lake depth was inferred around 6250 bp. Whilst the climate was wetter at that time, the inferred changes in depth likely reflect the alteration of the food web, which resulted from the arrival of fish in the lake. This highlights the risks of using single-variable inference models for hindcasting change in lake physical and/or food web structure when there are other important co-variables.     

Surface sediment diatom assemblages and epilimnetic total phosphorus in large, shallow lakes of the Yangtze floodplain: their relationships and implications for assessing long-term eutrophication

1. The Yangtze floodplain (SE China) is characterized by a number of large shallow lakes, many of which have undergone eutrophication due to the intensification of agriculture and urban growth over recent decades. As monitoring data are limited and in order to determine lake baseline nutrient concentrations, 49 lakes were sampled, covering a total phosphorus (TP) gradient (c. 30–550 μg L⁻¹) to develop a diatom-based inference model. 2. There are three dominant diatom assemblages in these shallow lakes with a marked change in assemblage structure near the boundary between eutrophic and hypereutrophic nutrient levels (as indicated by their TP value). Canonical correspondence analysis indicated that TP was the most important and significant variable in explaining the diatom distributions, independently accounting for 9.5% variance of diatoms. 3. Forty-three lakes were used to generate a transfer function using weighted averaging (WA) with inverse deshrinking. This model had low predictive error (root mean squared error of prediction; RMSEP_jack = 0.12) and a high coefficient of prediction (R²_jack = 0.82), comparable with regional TP models elsewhere. The good performance of this TP model may reflect the low abundance of benthic diatom species which are commonly regarded as the main error source in European shallow lake WA models. 4. The WA model was used to reconstruct the past-TP concentrations for Taibai Lake, a shallow hypereutrophic lake in Hubei province. The results showed that TP concentration varied slightly (43–62 μg L⁻¹) prior to the 1920s, indicating an eutrophic state since the 1800s. A period of sustained eutrophication occurred after 1950, because of the development of agriculture, reflecting by maximum values of Aulacoseira alpigena and increased abundance of Cyclotella meneghiniana, C. atomus and Cyclostephanos dubius. The steep increase in nutrient concentration after 1970 was related to the overuse of chemical fertilizer and fish farming in the catchment. 5. The shift in fossil diatoms from epiphytic to planktonic forms in the lake sediment core during 1950–70 provides useful information on the transformation from macrophyte-dominated to alga-dominated states. It is plausible that the TP concentration of 80–110 μg L⁻¹ observed in this study is the critical range for switching between the two stable states in the lake. 6. The regional diatom-TP model developed in this study allows, therefore, the possibility of reconstructing historical background nutrient concentrations in lakes. It will provide an indication of the onset and development of eutrophication at any site. This is particularly important for the many lakes in the Yangtze floodplain where information about historical changes in water quality is lacking.     

Chrysophyte cyst biogeographical and ecological distributions: a synthesis

The distributions of chrysophyte stomatocysts in the sediments of 221 lakes from four study areas located in British Columbia, Canada (two datasets), New York, U.S.A., and south central Siberia were examined. The combined lake set spanned a wide range of chemical and morphometric variables. Approximately 400 cyst morphotypes were identified, from which we selected sixty-three common types for further analysis. Canonical ordination (detrended canonical correspondence analysis (DCCA) and constrained DCCA) showed that four environmental variables (pH, conductivity, depth and total phosphorus (TP) ) were significant (Monte Carlo permutation test, P =0.01 for all four variables) and independent determinants of the cyst distributions. Weighted averaging (WA) inference models were developed for each variable. The best models, in terms of their r ², were developed for pH and conductivity ( r ²=0.78 and 0.73, respectively). The models for depth and TP were less robust ( r ²=0.47 and 0.46, respectively). We discuss the relative importance of conductivity and salinity, lakewater acidity and metal concentrations, lake morphometry and trophic status as determinants of chrysophyte population distributions, and possible causal mechanisms for each variable. We identify assemblages of cysts that appear to be associated with six different groups of lakes: (1) very acidic (pH <6.5) lakes; (2) acidic (pH <7.0), softwater lakes; (3) circumneutral (pH 7–8), oligo- to mesotrophic lakes; (4) alkaline, hardwater, meso- to eutrophic lakes; (5) shallow, alkaline (pH 8–8.5), meso- to eutrophic lakes; and (6) shallow, very alkaline (pH >8.5) lakes, including sub- and hyposaline lakes. Finally, we suggest further possible avenues for research that will improve the usefulness of chrysophyte stomatocysts as paleolimnological indicators.     

Quantitative relationships of invertebrates to pH in Norwegian river systems

The invertebrate fauna has been surveyed for twenty one unlimed generally acidic river systems in Norway. The data consist of 180 samples and 127 invertebrate taxa and associated water chemistry data (pH, calcium, acid neutralizing capacity, total aluminium, and conductivity). Multivariate numerical methods are used to quantify the relationships between aquatic invertebrates and water chemistry. Detrended canonical correspondence analysis (DCCA) shows one dominant axis of variation with high correlations for pH and aluminium. DCCA axis 2 is significantly correlated with calcium. The predictive abilities of invertebrates to pH are explored by means of weighted averaging (WA) regression and calibration and weighted averaging partial-least-squares regression (WA-PLS). The performance of the methods is reported in terms of the root mean square error of prediction (RMSEP) of (observed pH-inferred pH). Bootstrapping and leave-one-out jackknifing are used as cross-validation procedures. The predictive abilities of invertebrates are good (RMSEP_boot for WA = 0.309 pH units). Comparison of the invertebrates with diatom studies shows that invertebrates are as good predictors of modern pH as diatoms are. RMSEP_jack shows that WA-PLS improves the predictive abilities. Indicator taxa for pH are found by Gaussian regression. Anisoptera, Agrypnia obsoleta, Leptophlebia marginata, Sialis lutaria, and Zygoptera have significant sigmoidal curves where abundances increase with decreasing pH. Cyrnus flavidus shows a significant unimodal response and has an estimated optimum in the acid part of the gradient. Isoperla spp. and Ostracoda show significant sigmoidal responses where abundances increase with increasing pH. Amphinemura borealis, Diura nanseni, Isoperla grammatica, I. obscura, and Siphonoperla burmeisteri show significant unimodal responses and have high pH optima. Many taxa do not have statistically significant unimodal or sigmoidal curves, but are found by WA to be characteristic of either high pH or low pH. These results suggest that a combined use of Gaussian regression and direct gradient analysis is needed to get a full overview of potential indicator taxa.     

Limnology of two lake systems of Katmai National Park and Preserve, Alaska: Part II. Light penetration and Secchi depth

Seven large lakes in the Naknek River drainage and four in the Alagnak River drainage within the Katmai National Park and Preserve, Alaska, were surveyed once a summer during the period 1990–92 to determine baseline limnological conditions. All of the lakes are oligotrophic based on Secchi depth (SD) transparency and light penetration. Overall, SD transparency varied from 4.4 m to 17 m, the vertical light extinction coefficient (K _d) ranged from 0.411 m^-1 to 0.070 m^-1 and the depth of 1% light penetration (I_1%) varied from 11 m to 67 m. However, because of greater light scattering, the percent of photosynthetic radiation (PAR) at SD was nearly twice as much in Battle Lake (30.4%) and Naknek Lake (32.8%), compared with the other nine lakes (mean 16%). Consequently, the ratio of I_1% to SD was about 4 in these two lakes compared to a mean value of 2.6 for the other lakes. However, Battle Lake is a deep blue calcium sulfate lake with little phytoplankton, whereas Naknek Lake contains some inorganic glacial flour and volcanic ash, as well as planktonic algae, but where sampled exhibits minimal turbidity. Biomass of planktonic algae (indexed by total chlorophyll concentration) explained most of the variation in SD (r ²=0.66), K _d (r ²=0.75), and I _1% (r ²=0.85). In contrast, neither color nor turbidity were significant predictors of any optical variable. Considering all 11 lakes, there was a significant linear relationship between SD and both K _d (r ²=0.80) and I _1% (r ²=0.72); however, most of the unaccounted for variation was attributed to Battle Lake and Naknek Lake. Although changes in water transparency are often linked to changes in algal biomass (chlorophyll), simple measures of SD transparency alone may not be appropriate for assessing whole-scale watershed or regional changes toward oligotrophication or eutrophication in lakes of the remote and pristine Katmai National Park and Preserve.     

Salt tolerance of eggplant

Summary No quantitative information is available regarding the salt tolerance of eggplant (Solanum melongena L.). The present study was conducted over a two-year period in small field plots irrigated by drip, where irrigation frequency was also a variable. The salt tolerance function may be described by the equation Y_r=100–6.9 (EC_e−1.1), where Y_r=relative yield of fruit, EC_e=the mean integrated electrical conductivity at the soil saturation extract, 1.1 dS/m=threshold salinity. Salt was distributed reasonably uniformly within the root zone.     

A landscape approach to examining spatial patterns of limnological variables and long-term environmental change in a southern Canadian lake district

1. We explored patterns of limnological variables (physical, chemical and biological) with relation to landscape position (expressed as lake order) in 86 study lakes located on shield bedrock in south‐central Ontario, Canada. 2. Using anova s with lake order as the categorical variable, landscape position explained significant amounts of variation in major ion chemistry, physical and catchment characteristics, hypolimnetic oxygen, and community composition in algal (diatom, chrysophyte) and invertebrate (chironomid) assemblages preserved in surficial sediments. Several nutrient variables (TP, total phosphorus and TN, total nitrogen) and dissolved organic carbon did not have significant relationships with lake order. 3. The strongest relationships with lake order (as a fraction of variation explained in anova s) included silica concentrations (r² = 0.40) and SO₄ (r² = 0.29) concentrations, surface area (r² = 0.50) and hypolimnetic oxygen (r² = 0.29). 4. Bedrock geology (carbonate metasedimentary versus non‐carbonate bedrock) had strong influences on spatial gradients of pH and major ion chemistry. It was difficult to separate geological influences from spatial influences on limnological variables in this study, as drainage patterns in the region are highly influenced by surface features of underlying geological formations because of the very thin glacial till or exposed bedrock that exists in most catchments. 5. Patterns of limnological variables indicated that low‐order, headwater lakes had the lowest concentrations of major ions, and, from algal inferences of pH change, had been most susceptible to acidic deposition. High‐order, downstream lakes were larger and deeper, and had higher concentrations of hypolimnetic oxygen, indicating that optimal lake trout habitat was primarily located in high‐order lakes. 6. Variance partitioning analyses indicated that lake order as a metric of landscape position explained comparable portions of community variation in algal and invertebrate assemblages compared with geographic position (latitude, longitude) and Cartesian coordinate position (e.g. x, y, x², y², etc.) metrics. Lake order explained more community variation in chironomid assemblages compared with other landscape metrics, possibly because of the strong relationships between lake order and lake morphometry variables.     

基于MODIS的中国草地NPP综合估算模型

草地生态系统是陆地生态系统分布最广的生态系统类型之一,其碳储量的估算在全球变化中的作用越来越受到重视。为了快速、便捷地实现中国草地净初级生产力(NPP)的估算,在获取野外调查资料与同期遥感影像数据的基础上,利用归一化植被指数(NDVI)以及气候数据,构建了草地NPP综合估算模型。模型包括叶面积指数(LAI)和光合累积量(PA)两个子模型,其中LAI子模型利用了遥感数据NDVI,PA子模型利用了温度、降水和辐射等气候数据。通过建模以外独立的实测数据的验证,模拟值与实测值之间有很好的相关性,R2为0.8519,相关性达到极显著水平。RMSE和RRMSE均较小,表明模型的模拟结果比较可靠。同时模拟值与实测值之间的平均相对误差仅为1.97%,模拟结果的准确度较高,因此利用上述模型估算中国草地NPP是可行的。以上结果为中国草地NPP估算提供了新的方法。     

Seasonal Dynamics of CO2 Flux Across the Surface of Shallow Temperate Lakes

We used data collected from 1989 to 2009 from 151 shallow (mean depth < 3 m) temperate lakes in Denmark to explore the influence of lake trophic status, surface area and catchment size on the seasonal dynamics of the air–water flux of CO₂. Monthly CO₂ fluxes were derived from measurements of acid neutralizing capacity (ANC), pH, ionic strength, temperature, and wind speed. CO₂ fluxes exhibited large seasonal variability, in particular in oligo-mesotrophic lakes. Most of the lakes emitted CO₂ during winter (median rates ranging 300–1,900 mg C m⁻² day⁻¹), and less CO₂ during summer or, in the case of some of the highly eutrophic lakes, retained CO₂ during summer. We found that seasonal CO₂ fluxes were strongly negatively correlated with pH (r = −0.65, P < 0.01), which in turn was correlated with chlorophyll a concentrations (r = 0.48, P < 0.01). Our analysis suggests that lake trophic status (a proxy for pelagic production) interacts with the lake ANC to drive the seasonal dynamics of CO₂ fluxes, largely by changing pH and thereby the equilibrium of the free CO₂ and bicarbonate relation. Long-term observations from four lakes, which have all undergone a period of oligotrophication during the past two decades, provide further evidence that CO₂ efflux generally increases as trophic status decreases, as a consequence of decreased pH. Across these four lakes, the annual average CO₂ emission has increased by 32% during the past two decades, thus, demonstrating the strong link between lake trophic status and CO₂ flux.     

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.     

The simultaneous inference of zooplanktivorous fish and macrophyte density from sub‐fossil cladoceran assemblages: a multivariate regression tree approach

1. Quantitative palaeolimnology has traditionally sought to quantify species‐environment relationships to use alterations in biological assemblages to reflect past environmental change. Transfer functions have used regression techniques, such as weighted averaging, to define taxon optima and tolerance for a single chemical or biological variable. 2. Cladoceran assemblages and their sub‐fossil remains in shallow lakes are shaped by a combination of interacting factors. Partial constrained ordination of sub‐fossil cladoceran assemblages from 39 shallow lakes (29 in Norfolk, U.K. and 10 in Denmark) indicated that both zooplanktivorous fish (ZF) density and submerged macrophyte abundance significantly influenced community composition. These dual structuring forces precluded the use of a transfer function as one of the key assumptions of this approach was not met, namely that environmental variables apart from the variable being modelled have negligible influence on species distribution or that there is a linear relationship between the two. Separate transfer functions for ZF and macrophyte abundance were developed but had poor performance diagnostics with low bootstrapped r², high root mean square error of prediction (RMSEP) and large bias. 3. To obviate the problem of multiple structuring forces a multivariate regression tree (MRT) was employed, which allows for more than one explanatory variable within a model. The MRT analysis defined six groups with discrete ranges of ZF and macrophyte densities. The technique identified critical values or ‘break points’ in ZF and macrophyte abundances which result in significant alterations in the sub‐fossil cladoceran assemblage. In addition, the MRT groups had different summer mean values for chlorophyll‐a, Secchi depth, total phosphorus and nitrate‐nitrogen. 4. The predictive abilities of the model were assessed by comparing the observed versus predicted MRT group membership. In general group membership was reliably predicted, suggesting sub‐fossil cladoceran assemblages reliably reflect ZF and macrophyte density in shallow lakes. For a relatively small number of sites there were differences between the observed and predicted MRT group membership. These failures of prediction may result, at least in part, from the disparity of the time period represented by the environmental data and the surface sediment cladoceran assemblage.     

Predicting tropical plant physiology from leaf and canopy spectroscopy

A broad regional understanding of tropical forest leaf photosynthesis has long been a goal for tropical forest ecologists, but it has remained elusive due to difficult canopy access and high species diversity. Here we develop an empirical model to predict sunlit, light-saturated, tropical leaf photosynthesis using leaf and simulated canopy spectra. To develop this model, we used partial least squares (PLS) analysis on three tropical forest datasets (159 species), two in Hawaii and one at the biosphere 2 laboratory (B2L). For each species, we measured light-saturated photosynthesis (A), light and CO₂ saturated photosynthesis (A _max), respiration (R), leaf transmittance and reflectance spectra (400–2,500 nm), leaf nitrogen, chlorophyll a and b, carotenoids, and leaf mass per area (LMA). The model best predicted A [r ²  = 0.74, root mean square error (RMSE) = 2.9 μmol m⁻² s⁻¹)] followed by R (r ²  = 0.48), and A _max (r ²  = 0.47). We combined leaf reflectance and transmittance with a canopy radiative transfer model to simulate top-of-canopy reflectance and found that canopy spectra are a better predictor of A (RMSE = 2.5 ± 0.07 μmol m⁻² s⁻¹) than are leaf spectra. The results indicate the potential for this technique to be used with high-fidelity imaging spectrometers to remotely sense tropical forest canopy photosynthesis.