Peat, pine stumps and people: interactions behind climate, vegetation change and human activity in wetland archaeology at Loch Farlary, Northern Scotland

First paragraph: In 1993, a peat-cutter, Bruce Field, working on the blanket peat bank he rented from the Sutherland Estate by Loch Farlary, above Golspie in Sutherland (fig 1), reported to Scottish Natural Heritage and Historic Scotland several pieces of pine wood bearing axe marks. Their depth in the peat suggested the cut marks to be prehistoric. This paper summarizes the work undertaken to understand the age and archaeological significance of this find (see also Tipping et al 2001 in press). The pine trees were initially thought to be part of a population that flourished briefly across northern Scotland in the middle of the Holocene period from c 4800 cal BP (Huntley, Daniell & Allen 1997). The subsequent collapse across northernmost Scotland of this population, the pine decline, at around 4200-4000 cal BP is unexplained: climate change has been widely assumed (Dubois & Ferguson 1985; Bridge, Haggart & Lowe 1990; Gear & Huntley 1991) but anthropogenic activity has not been disproved (Birks 1975; Bennett 1995). It was hypothesized that the Farlary find would allow for the first time the direct link between human woodland clearance and the Early Bronze Age pine decline.

Climate-pollen relationships AD 1901-1996 in two small mires near the forest limit in the northern and central Swiss Alps

Climatic relationships were established in two 210Pb dated pollen sequences from small mires closely surrounded by forest just below actual forest limits (but about 300 m below potential climatic forest limits) in the northern Swiss Alps (suboceanic in climate; mainly with Picea) and the central Swiss Alps (subcontinental; mainly Pinus cembra and Larix) at annual or near-annual resolution from ad 1901 to 1996. Effects of vegetational succession were removed by splitting the time series into early and late periods and by linear detrending. Both pollen concentrations detrended by the depth-age model and modified percentages (in which counts of dominant pollen types are down-weighted) are correlated by simple linear regression with smoothed climatic parameters with one-and two-year timelags, including average monthly and April/September daylight air temperatures and with seasonal and annual precipitation sums. Results from detrended pollen concentrations suggest that peat accumulation is favoured in the northern-Alpine mire either by early snowmelt or by summer precipitation, but in the central-Alpine mire by increased precipitation and cooler summers, suggesting a position of the northern-Alpine mire near the upper altitudinal limit of peat formation, but of the central-Alpine mire near the lower limit. Results from modified pollen percentages indicate that pollen pro duction by plants growing near their upper altitudinal limit is limited by insufficient warmth in summer, and pollen production by plants growing near their lower altitudinal limit is limited by too-high temperatures. Only weakly significant pollen/climate relationships were found for Pinus cembra and Larix, probably because they experience little climatic stress growing 300 m below the potential climatic forest limit.

四类气候－植被关系模型的比较研究

本研究应用数字地球技术，基于1950年～1980年的全国958个气象站的基本气象数据（包括气象站的经纬度，海拔，月均温，月降水，年均温， 年降水，日照时数，日照百分率，风速等），比较了四个不同的根据水、热平衡原理设计的气候一植被关系模型(Penman模型、Holdridge生命地带系统、和Kira方法Thomthwaite模型)在中国应用的一致性和适用性。结果表明：(1) Penman模型在温带草原区和青藏高原地区的一致性指数超过50%，在青藏高原最出色，最有发展潜力。(2) Thornthwaite模型在热带雨林、季雨林区达到39. 72%，可以弥补Holdridg模型在热带地区分类精度的不足。(3) Holdridg生命地带系统在不同地带间适用性最广;只在热带地区，例如西部季雨林、雨林区域(52)、西部草原亚区域(63)和青藏高原温性荒漠地带(86)以及青藏高原温性草原地带(84)不理想。(4)吉良(Kira)方法在亚热带常绿阔叶林区可与Holdridg模型相媲美;在低海拔和湿润、半湿润地区效果尚可，但在温带荒漠区与青藏高原区的模拟效果与实际相差较远。 这四个传统的分类方法在中国植被区划一级分类上是适用的，Holdridge生命地带系统KAPPA -致性指数达到0.57模拟效果优于其它三者，但在特定地区，如青藏高原，所有模型均需改进优化或启用新的模型因子才能很好地区分植被亚地带。本研究还指出，数字地球技术的应用有助于推动气候一植被关系的研究，尤其在气候一植被指标（气候参数和模型参数）的大范围实时动态监测、气候一植被关系数据的海量信息高效、有序基础管理和功能型模型库支撑框架体系方面。

Alternaria Spores in the Air Across Europe: Abundance, Seasonality and Relationships with Climate, Meteorology and Local Environment

We explored the temporal and spatial variations in airborne Alternaria spore quantitative and phenological features in Europe using 23 sites with annual time series between 3 and 15 years. The study covers seven countries and four of the main biogeographical regions in Europe. The observations were obtained with Hirst-type spore traps providing time series with daily records. Site locations extend from Spain in the south to Denmark in the north and from England in the West to Poland in the East. The study is therefore the largest assessment ever carried out for Europe concerning Alternaria. Aerobiological data were investigated for temporal and spatial patterns in their start and peak season dates and their spore indices. Moreover, the effects of climate were checked using meteorological data for the same period, using a crop growth model. We found that local climate, vegetation patterns and management of landscape are governing parameters for the overall spore concentration, while the annual variations caused by weather are of secondary importance but should not be neglected. The start of the Alternaria spore season varies by several months in Europe, but the peak of the season is more synchronised in central northern Europe in the middle of the summer, while many southern sites have peak dates either earlier or later than northern Europe. The use of a crop growth model to explain the start and peak of season suggests that such methods could be useful to describe Alternaria seasonality in areas with no available observations.

Model results in NetCDF format of North African vegetation-precipitation in early and mid-Holocene climate simulated by CCSM3-DGVM//

The present study analyses the sign, strength, and working mechanism of the vegetation-precipitation feedback over North Africa in middle (6 ka BP) and early Holocene (9 ka BP) simulations using the comprehensive coupled climate-vegetation model CCSM3-DGVM (Community Climate System Model version 3 and a dynamic global vegetation model). The coupled model simulates enhanced summer rainfall and a northward migration of the West African monsoon trough along with an expansion of the vegetation cover for the early and middle Holocene compared to the pre-industrial period. It is shown that dynamic vegetation enhances the orbitally triggered summer precipitation anomaly by approximately 20% in the Sahara-Sahel region (10-25° N, 20° W-30° E) in both the early and mid-Holocene experiments compared to their fixed-vegetation counterparts. The primary vegetation-rainfall feedback identified here operates through surface latent heat flux anomalies by canopy evaporation and transpiration and their effect on the mid-tropospheric African easterly jet, whereas the effects of vegetation changes on surface albedo and local water recycling play a negligible role. Even though CCSM3-DGVM simulates a positive vegetation-precipitation feedback in the North African region, this feedback is not strong enough to produce multiple equilibrium climate-ecosystem states on a regional scale.

How Climate and Vegetation Influence the fire Regime of the Alaskan Boreal Biome: The Holocene Perspective

We synthesize recent results from lake-sediment studies of Holocene fire-climate-vegetation interactions in Alaskan boreal ecosystems. At the millennial time scale, the most robust feature of these records is an increase in fire occurrence with the establishment of boreal forests dominated by Picea mariana: estimated mean fire-return intervals decreased from ≥300 yrs to as low as ∼80 yrs. This fire-vegetation relationship occurred at all sites in interior Alaska with charcoal-based fire reconstructions, regardless of the specific time of P. mariana arrival during the Holocene. The establishment of P. mariana forests was associated with a regional climatic trend toward cooler/wetter conditions. Because such climatic change should not directly enhance fire occurrence, the increase in fire frequency most likely reflects the influence of highly flammable P. mariana forests, which are more conducive to fire ignition and spread than the preceding vegetation types (tundra, and woodlands/forests dominated by Populus or Picea glauca). Increased lightning associated with altered atmospheric circulation may have also played a role in certain areas where fire frequency increased around 4000 calibrated years before present (BP) without an apparent increase in the abundance of P. mariana. When viewed together, the paleo-fire records reveal that fire histories differed among sites in the same modern fire regime and that the fire regime and plant community similar to those of today became established at different times. Thus the spatial array of regional fire regimes was non-static through the Holocene. However, the patterns and causes of the spatial variation remain largely unknown. Advancing our understanding of climate-fire-vegetation interactions in the Alaskan boreal biome will require a network of charcoal records across various ecoregions, quantitative paleoclimate reconstructions, and improved knowledge of how sedimentary charcoal records fire events.

Tropical climate and vegetation simulations during the Heinrich event 1 using an Earth System Model of Intermediate Complexity (EMIC) - the University of Victoria Earth System-Climate Model (UVic ESCM)

Abrupt climate changes from 18 to 15 thousand years before present (kyr BP) associated with Heinrich Event 1 (HE1) had a strong impact on vegetation patterns not only at high latitudes of the Northern Hemisphere, but also in the tropical regions around the Atlantic Ocean. To gain a better understanding of the linkage between high and low latitudes, we used the University of Victoria (UVic) Earth System-Climate Model (ESCM) with dynamical vegetation and land surface components to simulate four scenarios of climate-vegetation interaction: the pre-industrial era, the Last Glacial Maximum (LGM), and a Heinrich-like event with two different climate backgrounds (interglacial and glacial). We calculated mega-biomes from the plant-functional types (PFTs) generated by the model to allow for a direct comparison between model results and palynological vegetation reconstructions. Our calculated mega-biomes for the pre-industrial period and the LGM corresponded well with biome reconstructions of the modern and LGM time slices, respectively, except that our pre-industrial simulation predicted the dominance of grassland in southern Europe and our LGM simulation resulted in more forest cover in tropical and sub-tropical South America. The HE1-like simulation with a glacial climate background produced sea-surface temperature patterns and enhanced inter-hemispheric thermal gradients in accordance with the "bipolar seesaw" hypothesis. We found that the cooling of the Northern Hemisphere caused a southward shift of those PFTs that are indicative of an increased desertification and a retreat of broadleaf forests in West Africa and northern South America. The mega-biomes from our HE1 simulation agreed well with paleovegetation data from tropical Africa and northern South America. Thus, according to our model-data comparison, the reconstructed vegetation changes for the tropical regions around the Atlantic Ocean were physically consistent with the remote effects of a Heinrich event under a glacial climate background.

Export of organic matter, sulphate and base cations from boreal headwater catchments downstream to the coast: impacts of land use and climate

The terrestrial export of dissolved organic matter (DOM) is associated with climate, vegetation and land use, and thus is under the influence of climatic variability and human interference with terrestrial ecosystems, their soils and hydrological cycles. The present study provides an assessment of spatial variation of DOM concentrations and export, and interactions between DOM, catchment characteristics, land use and climatic factors in boreal catchments. The influence of catchment characteristics, land use and climatic drivers on the concentrations and export of total organic carbon (TOC), total organic nitrogen (TON) and dissolved organic phosphorus (DOP) was estimated using stream water quality, forest inventory and climatic data from 42 Finnish pristine forested headwater catchments, and water quality monitoring, GIS land use, forest inventory and climatic data from the 36 main Finnish rivers (and their sub-catchments) flowing to the Baltic Sea. Moreover, the export of DOM in relation to land use along a European climatic gradient was studied using river water quality and land use data from four European areas. Additionally, the role of organic and minerogenic acidity in controlling pH levels in Finnish rivers and pristine streams was studied by measuring organic anion, sulphate (SO4) and base cation (Ca, Mg, K and Na) concentrations. In all study catchments, TOC was a major fraction of DOM, with much lower proportions of TON and DOP. Moreover, most of TOC and TON was in a dissolved form. The correlation between TOC and TON concentrations was strong and TOC concentrations explained 78% of the variation in TON concentrations in pristine headwater streams. In a subgroup of 20 headwater catchments with similar climatic conditions and low N deposition in eastern Finland, the proportion of peatlands in the catchment and the proportion of Norway spruce (Picea abies Karsten) of the tree stand had the strongest correlation with the TOC and TON concentrations and export. In Finnish river basins, TOC export increased with the increasing proportion of peatland in the catchment, whereas TON export increased with increasing extent of agricultural land. The highest DOP concentrations and export were recorded in river basins with a high extent of agricultural land and urban areas, reflecting the influence of human impact on DOP loads. However, the most important predictor for TOC, TON and DOP export in Finnish rivers was the proportion of upstream lakes in the catchment. The higher the upstream lake percentage, the lower the export indicating organic matter retention in lakes. Molar TOC:TON ratio decreased from headwater catchments covered by forests and peatlands to the large river basins with mixed land use, emphasising the effect of the land use gradient on the stoichiometry of rivers. This study also demonstrated that the land use of the catchments is related to both organic and minerogenic acidity in rivers and pristine headwater streams. Organic anion dominated in rivers and streams situated in northern Finland, reflecting the higher extent of peatlands in these areas, whereas SO4 dominated in southern Finland and on western coastal areas, where the extent of fertile areas, agricultural land, urban areas, acid sulphate soils, and sulphate deposition is highest. High TOC concentrations decreased pH values in the stream and river water, whereas no correlation between SO4 concentrations and pH was observed. This underlines the importance of organic acids in controlling pH levels in Finnish pristine headwater streams and main rivers. High SO4 concentrations were associated with high base cation concentrations and fertile areas, which buffered the effects of SO4 on pH.

A model investigation of vegetation-atmosphere interactions on a millennial timescale

A terrestrial biosphere model with dynamic vegetation capability, Integrated Biosphere Simulator (IBIS2), coupled to the NCAR Community Atmosphere Model (CAM2) is used to investigate the multiple climate-forest equilibrium states of the climate system. A 1000-year control simulation and another 1000-year land cover change simulation that consisted of global deforestation for 100 years followed by re-growth of forests for the subsequent 900 years were performed. After several centuries of interactive climate-vegetation dynamics, the land cover change simulation converged to essentially the same climate state as the control simulation. However, the climate system takes about a millennium to reach the control forest state. In the absence of deep ocean feedbacks in our model, the millennial time scale for converging to the original climate state is dictated by long time scales of the vegetation dynamics in the northern high latitudes. Our idealized modeling study suggests that the equilibrium state reached after complete global deforestation followed by re-growth of forests is unlikely to be distinguishable from the control climate. The real world, however, could have multiple climate-forest states since our modeling study is unlikely to have represented all the essential ecological processes (e. g. altered fire regimes, seed sources and seedling establishment dynamics) for the reestablishment of major biomes.

The prediction of seasonal and inter-annual climate variations and their impacts on the water resources in the eastern seaboard of Thailand

The research of this thesis dissertation covers developments and applications of short-and long-term climate predictions. The short-term prediction emphasizes monthly and seasonal climate, i.e. forecasting from up to the next month over a season to up to a year or so. The long-term predictions pertain to the analysis of inter-annual- and decadal climate variations over the whole 21st century. These two climate prediction methods are validated and applied in the study area, namely, Khlong Yai (KY) water basin located in the eastern seaboard of Thailand which is a major industrial zone of the country and which has been suffering from severe drought and water shortage in recent years. Since water resources are essential for the further industrial development in this region, a thorough analysis of the potential climate change with its subsequent impact on the water supply in the area is at the heart of this thesis research. The short-term forecast of the next-season climate, such as temperatures and rainfall, offers a potential general guideline for water management and reservoir operation. To that avail, statistical models based on autoregressive techniques, i.e., AR-, ARIMA- and ARIMAex-, which includes additional external regressors, and multiple linear regression- (MLR) models, are developed and applied in the study region. Teleconnections between ocean states and the local climate are investigated and used as extra external predictors in the ARIMAex- and the MLR-model and shown to enhance the accuracy of the short-term predictions significantly. However, as the ocean state – local climate teleconnective relationships provide only a one- to four-month ahead lead time, the ocean state indices can support only a one-season-ahead forecast. Hence, GCM- climate predictors are also suggested as an additional predictor-set for a more reliable and somewhat longer short-term forecast. For the preparation of “pre-warning” information for up-coming possible future climate change with potential adverse hydrological impacts in the study region, the long-term climate prediction methodology is applied. The latter is based on the downscaling of climate predictions from several single- and multi-domain GCMs, using the two well-known downscaling methods SDSM and LARS-WG and a newly developed MLR-downscaling technique that allows the incorporation of a multitude of monthly or daily climate predictors from one- or several (multi-domain) parent GCMs. The numerous downscaling experiments indicate that the MLR- method is more accurate than SDSM and LARS-WG in predicting the recent past 20th-century (1971-2000) long-term monthly climate in the region. The MLR-model is, consequently, then employed to downscale 21st-century GCM- climate predictions under SRES-scenarios A1B, A2 and B1. However, since the hydrological watershed model requires daily-scale climate input data, a new stochastic daily climate generator is developed to rescale monthly observed or predicted climate series to daily series, while adhering to the statistical and geospatial distributional attributes of observed (past) daily climate series in the calibration phase. Employing this daily climate generator, 30 realizations of future daily climate series from downscaled monthly GCM-climate predictor sets are produced and used as input in the SWAT- distributed watershed model, to simulate future streamflow and other hydrological water budget components in the study region in a multi-realization manner. In addition to a general examination of the future changes of the hydrological regime in the KY-basin, potential future changes of the water budgets of three main reservoirs in the basin are analysed, as these are a major source of water supply in the study region. The results of the long-term 21st-century downscaled climate predictions provide evidence that, compared with the past 20th-reference period, the future climate in the study area will be more extreme, particularly, for SRES A1B. Thus, the temperatures will be higher and exhibit larger fluctuations. Although the future intensity of the rainfall is nearly constant, its spatial distribution across the region is partially changing. There is further evidence that the sequential rainfall occurrence will be decreased, so that short periods of high intensities will be followed by longer dry spells. This change in the sequential rainfall pattern will also lead to seasonal reductions of the streamflow and seasonal changes (decreases) of the water storage in the reservoirs. In any case, these predicted future climate changes with their hydrological impacts should encourage water planner and policy makers to develop adaptation strategies to properly handle the future water supply in this area, following the guidelines suggested in this study.

Predicting the likely response of data-poor ecosystems to climate change using space-for-time substitution across domains

Predicting ecological response to climate change is often limited by a lack of relevant local data from which directly applicable mechanistic models can be developed. This limits predictions to qualitative assessments or simplistic rules of thumb in data-poor regions, making management of the relevant systems difficult. We demonstrate a method for developing quantitative predictions of ecological response in data-poor ecosystems based on a space-for-time substitution, using distant, well-studied systems across an inherent climatic gradient to predict ecological response. Changes in biophysical data across the spatial gradient are used to generate quantitative hypotheses of temporal ecological responses that are then tested in a target region. Transferability of predictions among distant locations, the novel outcome of this method, is demonstrated via simple quantitative relationships that identify direct and indirect impacts of climate change on physical, chemical and ecological variables using commonly available data sources. Based on a limited subset of data, these relationships were demonstrably plausible in similar yet distant (>2000 km) ecosystems. Quantitative forecasts of ecological change based on climate-ecosystem relationships from distant regions provides a basis for research planning and informed management decisions, especially in the many ecosystems for which there are few data. This application of gradient studies across domains - to investigate ecological response to climate change - allows for the quantification of effects on potentially numerous, interacting and complex ecosystem components and how they may vary, especially over long time periods (e.g. decades). These quantitative and integrated long-term predictions will be of significant value to natural resource practitioners attempting to manage data-poor ecosystems to prevent or limit the loss of ecological value. The method is likely to be applicable to many ecosystem types, providing a robust scientific basis for estimating likely impacts of future climate change in ecosystems where no such method currently exists.