Non-climatic Effects Research Articles

Deriving a high-quality daily dataset of large-pan evaporation over China using a hybrid model

Global warming is expected to increase the atmospheric evaporative demand and make more surface water for evapotranspiration, aggerating water sources' social and ecological shortage. Pan evaporation, as a routine observation worldwide, is an excellent metric to indicate the response of terrestrial evaporation to global warming. However, several non-climatic effects, such as instrument upgrades, have destroyed the homogenization of pan evaporation and limited its applications. In China, 2400s meteorological stations have observed daily pan evaporation since 1951. The observed records became discontinuous and inconsistent due to the instrument upgrade from micro-pan D20 to large-pan E601. Here, combining the Penpan model (PM) and random forest model (RFM), we developed a hybrid model to assimilate different types of pan evaporation into a consistent dataset. Based on the cross-validation test, on a daily scale, the hybrid model has a lower bias (RMSE=0.41 mm day−1) and better stability (NSE=0.94) than the two sub-models and the conversion coefficient method. Finally, we produced a homogenized daily dataset of E601 across China from 1961 to 2018. Based on this dataset, we analyzed the long-term trend of pan evaporation. Pan evaporation showed a -1.23±0.57 mm a−2 downward trend from 1961-1993, primarily caused by decreased pan evaporation in warm seasons over North China. After 1993, the pan evaporation in South China increased significantly, resulting in a 1.83±0.87 mm a−2 upward trend across China. With better homogeneity and higher temporal resolution, the new dataset is expected to promote drought monitoring, hydrological modeling, and water resources management. Free access to the dataset can be found at https://figshare.com/s/0cdbd6b1dbf1e22d757e.

A research agenda for nonvascular photoautotrophs under climate change.

Nonvascular photoautotrophs (NVP), including bryophytes, lichens, terrestrial algae, and cyanobacteria, are increasingly recognized as being essential to ecosystem functioning in many regions of the world. Current research suggests that climate change may pose a substantial threat to NVP, but the extent to which this will affect the associated ecosystem functions and services is highly uncertain. Here, we propose a research agenda to address this urgent question, focusing on physiological and ecological processes that link NVP to ecosystem functions while also taking into account the substantial taxonomic diversity across multiple ecosystem types. Accordingly, we developed a new categorization scheme, based on microclimatic gradients, which simplifies the high physiological and morphological diversity of NVP and world-wide distribution with respect to several broad habitat types. We found that habitat-specific ecosystem functions of NVP will likely be substantially affected by climate change, and more quantitative process understanding is required on (1) potential for acclimation, (2) response to elevated CO2 , (3) role of the microbiome, and (4) feedback to (micro)climate. We suggest an integrative approach of innovative, multimethod laboratory and field experiments and ecophysiological modelling, for which sustained scientific collaboration on NVP research will be essential.

气候变化和人为活动在宁夏草地变化中的相对作用

PDF HTML阅读 XML下载 导出引用 引用提醒 气候变化和人为活动在宁夏草地变化中的相对作用 DOI: 10.5846/stxb202105191307 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 宁夏自然科学基金项目（2018AAC03277）；宁夏农业高质量发展和生态保护科技创新示范项目（NGSB-2021-14-03，NGSB-2021-15-01）；陕西省教育厅项目（20JK0760） Assessment of relative effects of climate change and human activities on grassland dynamic in Ningxia Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:气候变化和人为活动是草地生态系统退化或恢复过程中的两大驱动因素。选取植被净初级生产力（NPP）为衡量指标，利用改进的Carnegie-Ames-Stanford Approach （CASA）模型、Thornthwaite Memorial模型以及残差趋势法分别计算了宁夏草地实际净初级生产力（ANPP）、潜在净初级生产力（PNPP）和人为活动影响的生产力（HNPP）及其变化趋势，定量评估了2001-2019年气候变化和人为活动在宁夏4种类型草地（温性草甸、温性草原、温性荒漠草原和温性草原化荒漠）动态变化中的相对作用。结果表明，2001-2019年宁夏草地实际净初级生产力增加的面积占宁夏草地总面积的97.84%；全区草地潜在净初级生产力均表现为增加趋势，表明气候变化有利于植被恢复。草地恢复过程中，气候变化引起的草地恢复面积占草地恢复总面积的61.68%，气候变化和人为活动共同作用引起的草地恢复面积占38.32%；人为活动是导致草地退化的绝对主导因素。4种类型草地动态变化的驱动因素存在差异，气候变化是促进温性草甸（68.94%）和温性草原化荒漠（70.51%）恢复的主导因素，气候变化和人为活动共同作用是促进温性草原恢复的主导因素（62.30%），温性荒漠草原的恢复是气候变化和人为活动共同作用的结果（97.93%）。水热条件好转，尤其是降水增加是宁夏草地恢复的主导气候因子，生态保护政策的实施是促进草地恢复的主要人为因素，对草地的不合理利用是导致草地退化的主要人为因素。 Abstract:Climate change and human activity are two main factors driving vegetation dynamics during grassland recovery or degradation. In this study, the net primary productivity (NPP) was selected as the index, the improved Carnegie-Ames-Stanford Approach (CASA) model and Thornthwaite Memorial model were used to estimate actual net primary productivity (ANPP) and potential net primary productivity (PNPP) determined by climatic conditions, respectively. The residual trend analysis (RESTREND) method was applied to analyze the residuals of potential and actual net primary productivity and further identify non-climatic effects on vegetation dynamics in four types of natural grassland, including meadow steppe, warm steppe, desert steppe and warm steppe desert of Ningxia. Results showed that the ANPP in 97.84% of the grassland increased from 2001 to 2019 generally. The PNPP of the whole region presented an increasing trend, revealing that climate change had a positive effect on vegetation recovery across the study area. During the grassland restoration, 61.68% of the recovered grassland resulted from climate change, while 38.32% of the recovered grassland from the combined effects of climate change and human activity. Anthropogenic activities were considered as the absolutely dominant influencing factor for vegetation degradation. The driving factors of vegetation dynamic showed differences in the four types of grassland. Climate change was the dominant factor for the recovery of warm meadow (68.94%) and warm steppe desert (70.51%). The combined effects of climate change and human activities were the main factors for the recovery of warm steppe (62.30%). The recovery of warm desert steppe resulted from the combined effects of climate change and human activities (97.93%). The improvement of hydrothermal conditions, especially the increases in precipitation, was the main influencing factor for grassland restoration in Ningxia. The implementation of ecological protection policies produced significantly positive effects on the restoration of grassland, and the unreasonable occupation of grassland was the main anthropogenic factor leading to grassland degradation. 参考文献 相似文献 引证文献

Cirques of the central Tibetan Plateau: Morphology and controlling factors

Cirque morphology represents the characteristics of palaeoglaciations and palaeoclimate. This study mapped and analysed 70 cirques in the central Tibetan Plateau (TP) with dominant continental climate. The results show that from northwest to southeast, cirque dimensions (i.e., length, width, and area) increase, while cirque floor altitudes decrease. A likely reason is the high precipitation rate caused by the Indian summer monsoon in the southeastern part. The diversity of cirque aspect values indicates weak or inconsistent prevailing winds during cirque development. Cirques enlarge with altitude, which might imply that cirques at high altitudes developed early and thus increased in size. Cirque aspect diversity increases with altitude from 5100 to 5600 m above sea level (asl), which indicates the capacity of high altitudes to support cirques at less favourable slopes. If altitude increases above 5600 m asl, the diversity of cirque aspect first increases and then decreases, which may be because of local topography. Mountain orientation and lithology had an effect on cirque aspect/size. Cirque numbers and sizes were compared between western, central, and eastern sectors of the Gangdise Mountains in the southern TP with those in the central TP. This comparison showed that a strengthening Indian summer monsoon can raise the value of ‘cirque density’ (i.e., cirque number per unit area), promote glacier development into valley-type, and limit cirque enlargement. • Cirques of a climatic transitional zone of the central Tibetan Plateau were studied. • Climatic and non-climatic effects were analysed. • A comparison with cirques in the Gangdise Mountains is presented.

Efficiency of Time Series Homogenization: Method Comparison with 12 Monthly Temperature Test Datasets

AbstractThe aim of time series homogenization is to remove nonclimatic effects, such as changes in station location, instrumentation, observation practices, and so on, from observed data. Statistical homogenization usually reduces the nonclimatic effects but does not remove them completely. In the Spanish “MULTITEST” project, the efficiencies of automatic homogenization methods were tested on large benchmark datasets of a wide range of statistical properties. In this study, test results for nine versions, based on five homogenization methods—the adapted Caussinus-Mestre algorithm for the homogenization of networks of climatic time series (ACMANT), “Climatol,” multiple analysis of series for homogenization (MASH), the pairwise homogenization algorithm (PHA), and “RHtests”—are presented and evaluated. The tests were executed with 12 synthetic/surrogate monthly temperature test datasets containing 100–500 networks with 5–40 time series in each. Residual centered root-mean-square errors and residual trend biases were calculated both for individual station series and for network mean series. The results show that a larger fraction of the nonclimatic biases can be removed from station series than from network-mean series. The largest error reduction is found for the long-term linear trends of individual time series in datasets with a high signal-to-noise ratio (SNR), where the mean residual error is only 14%–36% of the raw data error. When the SNR is low, most of the results still indicate error reductions, although with smaller ratios than for large SNR. In general, ACMANT gave the most accurate homogenization results. In the accuracy of individual time series ACMANT is closely followed by Climatol, and for the accurate calculation of mean climatic trends over large geographical regions both PHA and ACMANT are recommended.

RESTREND-based assessment of factors affecting vegetation dynamics on the Mongolian Plateau

The landscape of the Mongolian Plateau (MP) is shaped by both climatic change and human activities. It is noteworthy to monitor regional vegetation dynamics and to discriminate the impacts of climatic and anthropogenic factors on vegetation productivity and diversity. To investigate human- and climate-driven changes in vegetation cover across the MP during 2000−2014, the residual trend analysis (RESTREND) method was applied to analyze the residuals of potential and actual net primary productivity (NPP) and further identify non-climatic effects on vegetation dynamics. Results suggested that the normalized difference vegetation index (NDVI) in growing seasons had been increasing at the rate of 0.002/a in the whole MP during 2000–2015. And potential NPP increased across 71% of the study area, revealed that climate change displayed a generally positive effect on vegetation recovery across the plateau; However, the 53% of the total study area exhibited an decreasing residuals trend, indicated that human activity played a negative role in vegetation recovery. Analysis of the combined effects of climate change and human activities indicated that vegetation recovered in 74% but degraded in 22% of area of the MP. Anthropogenic activity could thus be considered as the main influencing factor of vegetation degradation, while climate change was the main controlling factor of vegetation restoration. Besides, Climatic factors had a similar effect on vegetation dynamics in inner and outer Mongolia, but human activities showed a different pattern with a lesser (greater) effect on vegetation degradation (recovery) in inner Mongolia than in outer Mongolia, respectively.

Observational Quantification of Climatic and Human Influences on Vegetation Greening in China

This study attempts to quantify the relative contributions of vegetation greening in China due to climatic and human influences from multiple observational datasets. Satellite measured vegetation greenness, Normalized Difference Vegetation Index (NDVI), and relevant climate, land cover, and socioeconomic data since 1982 are analyzed using a multiple linear regression (MLR) method. A statistically significant positive trend of average growing-season (April–October) NDVI is found over more than 34% of the vegetated areas, mainly in North China, while significant decreases in NDVI are only seen in less than 5% of the areas. The relationships between vegetation and climate (temperature, precipitation, and radiation) vary by geographical location and vegetation type. We estimate the NDVI changes in association with the non-climatic effects by removing the climatic effects from the original NDVI time series using the MLR analysis. Our results indicate that land use change is the dominant factor driving the long-term changes in vegetation greenness. The significant greening in North China is due to the increase in crops, grasslands, and forests. The socioeconomic datasets provide consistent and supportive results for the non-climatic effects at the provincial level that afforestation and reduced fire events generally have a major contribution. This study provides a basis for quantifying the non-climatic effects due to possible human influences on the vegetation greening in China.

Phosphorus in the Minnesota River Basin: The debate over its source and ways to mitigate impacts

Phosphorus in the Minnesota River Basin: The debate over its source and ways to mitigate impacts

Beyond climate envelope projections: Roe deer survival and environmental change

Research on climate change impacts has focused on projecting changes in the geographic ranges of species, with less emphasis on the vital rates giving rise to species distributions. Managing ungulate populations under future climate change will require an understanding of how their vital rates are affected by direct climatic effects and the indirect climatic and non-climatic effects that are often overlooked by climate impact studies. We used generalized linear models and capture–mark–recapture models to assess the influence of a variety of direct climatic, indirect climatic, and non-climatic predictors on the survival of roe deer (Capreolus capreolus) at 2 sites in Sweden. The models indicated that although direct climatic effects (e.g., precipitation) explained some variation in survival, indirect climatic effects (e.g., an index of vegetation production), and non-climatic effects (hunting by lynx [Lynx lynx] and humans) had greater explanatory power. Climate change is likely to increase vegetation productivity in northern Europe, and, coupled with the positive effects of vegetation productivity on roe deer survival, might lead to population increases in the future. Survival was negatively affected by lynx presence where these predators occur and by human harvest in the site that lacked predators. In the future, managers might find that a combination of increased harvest and predation by recovering carnivore populations may be necessary to mitigate climate-induced increases in roe deer survival. Considering vegetation availability and predation effects is likely to improve predictions of ungulate population responses to variation in climate and, therefore, inform management under future climate change.

Predicting Fire Frequency with Chemistry and Climate

A predictive equation for estimating fire frequency was developed from theories and data in physical chemistry, ecosystem ecology, and climatology. We refer to this equation as the Physical Chemistry Fire Frequency Model (PC2FM). The equation was calibrated and validated with North American fire data (170 sites) prior to widespread industrial influences (before � 1850 CE) related to land use, fire suppression, and recent climate change to minimize non-climatic effects. We derived and validated the empirically based PC2FM for the purpose of estimating mean fire intervals (MFIs) from proxies of mean maximum temperature, precipitation, their interaction, and estimated reactant concentrations. Parameterization of the model uses reaction rate equations based on the concentration and physical chemistry of fuels and climate. The model was then calibrated and validated using centuries of empirical fire history data. An application of the PC2FM regression equation is presented and used to estimate historic MFI as controlled by climate. We discuss the effects of temperature, precipitation, and their interactions on fire frequency using the PC2FM concept and results. The exclusion of topographic, vegetation, and ignition variables from the PC2FM increased error at fine spatial scales, but allowed for the prediction of complex climate effects at broader temporal and spatial scales. The PC2FM equation is used to map coarse-scale historic fire frequency and assess climate impacts on landscapescale fire regimes.

How barley growing conditions and its output change in Hungary

There is no doubt that climate change has started. It is very important to make effort in developing impact analyses and adaptation strategies. First we were investigated how the production risk of winter barley is changing with time using the E,V efficiency criterion. Based on the regional yearly production data of the crop, we can conclude that beside other non-climatic effects, the changing climate has considerable impact on crops yield; its variability is increasing with the variability of meteorological parameters. We have used production data from 1951 to nowadays. Next, using comparison analyses for climate scenarios, we predict what we can expect in the future. For detecting the reasons of risk increase in the past, and forecasting the potential main points of future risk we have analysed statistically whether the climate needs of winter barley will be satisfied or not in its important periods of growing. Frequency calculations were made based on the daily meteorological data. The situation doesn’t show big change, but It is no doubt that the anomalies of the indicators have been becoming more and more frequent. The more frequent the extreme weather events are, the more we can be convinced of uncertainty.

Socioeconomic patterns in climate data

Summary To generate a climate data set, temperature data collected at the Earth’s surface must be adjusted to remove non-climatic effects such as urbanization and measurement discontinuities. Some studies have shown that the post-1980 spatial pattern of temperature trends over land in prominent climate data sets is strongly correlated with the spatial pattern of socioeconomic development, implying that the adjustments are inadequate, leaving a residual warm bias. This evidence has been disputed on three grounds: spatial autocorrelation of the temperature field undermines significance of test results; counterfactual experiments using model-generated data suggest such correlations have an innocuous interpretation; and different satellite covariates yield unstable results. Somewhat surprisingly, these claims have not been put into a coherent framework for the purpose of statistical testing. We combine economic and climatological data sets from various teams with trend estimates from global climate models and we use spatial regressions to test the competing hypotheses. Overall we find that the evidence for contamination of climatic data is robust across numerous data sets, it is not undermined by controlling for spatial autocorrelation, and the patterns are not explained by climate models. Consequently we conclude that important data products used for the analysis of climate change over global land surfaces may be contaminated with socioeconomic patterns related to urbanization and other socioeconomic processes. Research Supported by Social Sciences and Humanities Research Council of Canada Grant Number 430002

Atmospheric Circulations Do Not Explain the Temperature-Industrialization Correlation

Gridded land surface temperature data products are used in climatology on the assumption that contaminating effects from urbanization, land-use change and related socioeconomic processes have been identified and filtered out, leaving behind a “pure” record of climatic change. But several studies have shown a correlation between the spatial pattern of warming trends in climatic data products and the spatial pattern of industrialization, indicating that local non-climatic effects may still be present. This, in turn, could bias measurements of the amount of global warming and its attribution to greenhouse gases. The 2007 report of the Intergovernmental Panel on Climate Change (IPCC) set aside those concerns with the claim that the temperature-industrialization correlation becomes statistically insignificant if certain atmospheric circulation patterns, also called oscillations, are taken into account. But this claim has never been tested and the IPCC provided no evidence for its assertion. I estimate two spatial models that simultaneously control for the major atmospheric oscillations and the distribution of socioeconomic activity. The correlations between warming patterns and patterns of socioeconomic development remain large and significant in the presence of controls for atmospheric oscillations, contradicting the IPCC claim. Tests for outlier influence, spatial autocorrelation, endogeneity bias, residual nonlinearity and other problems are discussed.

Quantifying the influence of anthropogenic surface processes and inhomogeneities on gridded global climate data

Local land surface modification and variations in data quality affect temperature trends in surface‐measured data. Such effects are considered extraneous for the purpose of measuring climate change, and providers of climate data must develop adjustments to filter them out. If done correctly, temperature trends in climate data should be uncorrelated with socioeconomic variables that determine these extraneous factors. This hypothesis can be tested, which is the main aim of this paper. Using a new database for all available land‐based grid cells around the world we test the null hypothesis that the spatial pattern of temperature trends in a widely used gridded climate data set is independent of socioeconomic determinants of surface processes and data inhomogeneities. The hypothesis is strongly rejected (P = 7.1 × 10−14), indicating that extraneous (nonclimatic) signals contaminate gridded climate data. The patterns of contamination are detectable in both rich and poor countries and are relatively stronger in countries where real income is growing. We apply a battery of model specification tests to rule out spurious correlations and endogeneity bias. We conclude that the data contamination likely leads to an overstatement of actual trends over land. Using the regression model to filter the extraneous, nonclimatic effects reduces the estimated 1980–2002 global average temperature trend over land by about half.

A test of corrections for extraneous signals in gridded surface temperature data

Monthly surface temperature records from 1979 to 2000 were obtained from 218 indi- vidual stations in 93 countries and a linear trend coefficient determined for each site. This vector of trends was regressed on measures of local climate, as well as indicators of local economic activity (income, gross domestic product (GDP) growth rates, coal use) and data quality. The spatial pattern of trends is shown to be significantly correlated with non-climatic factors, including economic activ- ity and sociopolitical characteristics of the region. The analysis is then repeated on the corresponding Intergovernmental Panel on Climate Change (IPCC) gridded data, and very similar correlations appear, despite previous attempts to remove non-climatic effects. The socioeconomic effects in the data are shown to add up to a net warming bias, although more precise estimation of its magnitude will require further research.

Vegetation sensitivity to global anthropogenic carbon dioxide emissions in a topographically complex region

Anthropogenic increases in atmospheric carbon dioxide (CO2) concentrations may affect vegetation distribution both directly through changes in photosynthesis and water‐use efficiency, and indirectly through CO2‐induced climate change. Using an equilibrium vegetation model (BIOME4) driven by a regional climate model (RegCM2.5), we tested the sensitivity of vegetation in the western United States, a topographically complex region, to the direct, indirect, and combined effects of doubled preindustrial atmospheric CO2 concentrations. Those sensitivities were quantified using the kappa statistic. Simulated vegetation in the western United States was sensitive to changes in atmospheric CO2 concentrations, with woody biome types replacing less woody types throughout the domain. The simulated vegetation was also sensitive to climatic effects, particularly at high elevations, due to both warming throughout the domain and decreased precipitation in key mountain regions such as the Sierra Nevada of California and the Cascade and Blue Mountains of Oregon. Significantly, when the direct effects of CO2 on vegetation were tested in combination with the indirect effects of CO2‐induced climate change, new vegetation patterns were created that were not seen in either of the individual cases. This result indicates that climatic and nonclimatic effects must be considered in tandem when assessing the potential impacts of elevated CO2 levels.

Mid-Holocene climate and the hemlock decline: the range limit of Tsuga canadensis in the western Great Lakes region, USA

Eastern hemlock (Tsuga canadensis) expanded rapidly across Upper Peninsula Michigan from ~6500 to 5500 cal. yr BP, followed by a sudden decline of hemlock pollen percentages that lasted over 1000 years. Hemlock declined throughout its range, apparently due to insect/pathogen outbreaks, which may have been affected by regional climatic shifts. Modern analogues were used to reconstruct submillennial climatic trends from fossil pollen sites spanning the western range limit of hemlock. Reconstructions from eight sites inside the range of hemlock at the time of the decline (5400 cal. yr BP) are compared with eight sites outside the range, which should be independent of variation in hemlock pollen percentages and the non-climatic effects of insects/pathogens. Expansion of hemlock before the decline occurred at a time of increasing precipitation and January temperature. Long-term precipitation averages stabilized at ~5500 cal. yr BP and remained fairly constant throughout the period of low hemlock abundance. January temperature reconstructions decrease at the time of the hemlock decline to approximately modern values at sites inside the range, as well as at oak dominated sites just outside the range. The lower-than-modern precipitation of the mid-Holocene may have reduced hemlock's tolerance for cold stress and winter desiccation and perhaps increased its susceptibility to insects or pathogens. January temperature reconstructions for pine-dominated sites outside the pre-decline hem lock range show little change, possibly due to the insensitivity of pine-dominated pollen assemblages to small climatic fluctuations. Hemlock began a new expansion across the region after 4000 cal. yr BP as July tempera ture decreased and precipitation increased.

Climatic and non-climatic effects on the δ 18O and δ 13C compositions of Lake Awassa, Ethiopia, during the last 6.5 ka

A comparison of a 6450 14C yr δ 18O and δ 13C record of authigenic calcite from Lake Awassa, Ethiopia, with other proxy climate records in the area suggests that the lake records long-term regional climate changes. Co-varying and increasing δ 18O and δ 13C values from ∼4800 BP suggest an aridification of climate after the early Holocene insolation maximum. After 4000 BP, humid conditions return until after ∼2800 BP when δ 18O increases again, reflecting more arid conditions recorded elsewhere in Ethiopia. In addition to these long-term changes, there are abrupt decreases in both δ 18O calcite and δ 13C calcite immediately after tephra layers. The likeliest explanation for these abrupt decreases in isotopes is the effect of tephra on the lake's catchment vegetation. δ 18O, δ 13C and lake-level measurements from Lake Awassa since the 1970s suggest that the lake is currently isotopically sensitive to short-term (annual–decadal) climate change. However, during this period, the catchment has undergone progressive deforestation that may have caused an increase in runoff. Caution is therefore required when reconstructing palaeoclimates as a contemporary lake may not always be a good analogue for lake hydrology in the past.

Quaternary vegetation and climate changes on Banks Peninsula, South Island, New Zealand

Late Quaternary terrestrial and marine pollen records from the Canterbury Plains and Banks Peninsula suggest that climates during the peak of Marine Isotope Stage 7 (MIS 7) were similar to those prevailing during stage 5e and the Holocene. Podocarp forest (notably Prumnopitys taxifolia—matai) characterises each interglaciation. In contrast, marine records from DSDP 594 cores, off the east coast of Canterbury, indicate that stage 7 was dominated by montane forest ( Libocedrus sp. and Phyllocladus). This suggests temperatures as much as 3 °C colder than indicated by the Banks Peninsula assemblage. Age control from both sites appears to be robust. Some of the differences may be related to the taphonomy of the pollen at both sites. DSDP 594 may reflect a more southerly catchment of fluvially and aeolian-derived pollen than does the Banks Peninsula site. Banks Peninsula was alternately separated from, and joined to, the mainland as Quaternary sea levels fell and rose. Assuming modern ocean current patterns, during interglacials the south–north Southland Current would have swept through the seaway separating the island from the mainland, diverting the flow of rivers embouching on the Canterbury coast, and moving sediments and fluvially transported pollen northwards. Little of this material would have reached DSDP 594, nor, if wind patterns were similar to those of today, would wind-borne pollen from Banks Peninsula have reached the site. It is probable that vegetation on the Peninsula was consistently distinct from that recorded at DSDP 594, which has a more southerly derivation. In contrast to the high mountain areas of the South Island, the low levels of grass pollen in the available record suggest that the Peninsula retained a woody vegetation over much of its area during glacial periods. This was favoured by the physiography of the area, with a variety of micro-climates, and by the extensive areas available for colonisation at times of low sea level. The podocarp forest of MIS 7 was replaced by an open shrubby vegetation in which Leptospermum and Kunzea ( Leptospermum-type pollen) was locally dominant, and in which Plagianthus, Phyllocladus, Coprosma and Myrsine were prominent. Charcoal is associated with this change. Most of the recorded taxa, with the exception of Phyllocladus, are present on the Peninsula today. A gap in the pollen record coincides with the Last Interglacial and Last Glaciation, but a return of forest vegetation is documented in the later Holocene. The reconstructions do not exclude the possibility of a cooler stage 7. They do highlight the importance of excluding local/regional non-climatic effects before interpreting climate change from data sets, and reinforce the necessity of testing marine records against compatible terrestrial ones.

Water Resources Implications of Global Warming: A U.S. Regional Perspective

The implications of global warming for the performance of six U.S. water resource systems are evaluated. The six case study sites represent a range of geographic and hydrologic, as well as institutional and social settings. Large, multi-reservoir systems (Columbia River, Missouri River, Apalachicola-Chatahoochee-Flint (ACF) Rivers), small, one or two reservoir systems (Tacoma and Boston) and medium size systems (Savannah River) are represented. The river basins range from mountainous to low relief and semi-humid to semi-arid, and the system operational purposes range from predominantly municipal to broadly multi-purpose. The studies inferred, using a chain of climate downscaling, hydrologic and water resources systems models, the sensitivity of six water resources systems to changes in precipitation, temperature and solar radiation. The climate change scenarios used in this study are based on results from transient climate change experiments performed with coupled ocean-atmosphere General Circulation Models (GCMs) for the 1995 Intergovernmental Panel on Climate Change (IPCC) assessment. An earlier doubled-CO2 scenario from one of the GCMs was also used in the evaluation. The GCM scenarios were transferred to the local level using a simple downscaling approach that scales local weather variables by fixed monthly ratios (for precipitation) and fixed monthly shifts (for temperature). For those river basins where snow plays an important role in the current climate hydrology (Tacoma, Columbia, Missouri and, to a lesser extent, Boston) changes in temperature result in important changes in seasonal streamflow hydrographs. In these systems, spring snowmelt peaks are reduced and winter flows increase, on average. Changes in precipitation are generally reflected in the annual total runoff volumes more than in the seasonal shape of the hydrographs. In the Savannah and ACF systems, where snow plays a minor hydrological role, changes in hydrological response are linked more directly to temperature and precipitation changes. Effects on system performance varied from system to system, from GCM to GCM, and for each system operating objective (such as hydropower production, municipal and industrial supply, flood control, recreation, navigation and instream flow protection). Effects were generally smaller for the transient scenarios than for the doubled CO2 scenario. In terms of streamflow, one of the transient scenarios tended to have increases at most sites, while another tended to have decreases at most sites. The third showed no general consistency over the six sites. Generally, the water resource system performance effects were determined by the hydrologic changes and the amount of buffering provided by the system's storage capacity. The effects of demand growth and other plausible future operational considerations were evaluated as well. For most sites, the effects of these non-climatic effects on future system performance would about equal or exceed the effects of climate change over system planning horizons.