Annual Growing Degree Days Research Articles

Improving generalisability and transferability of machine-learning-based maize yield prediction model through domain adaptation

Modern problems in agricultural management require non-traditional solutions, one of which is by utilizing domain adaptive machine learning models for crop yield prediction which are able to perform reliably in different temporal or spatial domains. However, most studies have focused on the application of domain adaptation to classification tasks such as crop type identification, while the application to regression tasks such as crop yield prediction have been limited. In this study, we explore the generalisability and transferability of ordinary Deep Neural Network (DNN) and domain adaptive neural network models created using three domain adaptation algorithms, namely Discriminative Adversarial Neural Network (DANN), Kullback-Leibler Importance Estimation Procedure (KLIEP), and Regular Transfer Neural Network (RTNN). These three algorithms represent feature-based, instance-based, and parameter-based domain adaptations, respectively. Maize yield records, weather variables, and remotely sensed features from 11 states in the US corn belt acquired in 2006–2020 were compiled and segregated into classes according to temporal (year) and spatial characteristics (annual growing degree days [GDD], vapor pressure deficit [VPD], soil organic content [SOC], and green chlorophyll vegetation index/GCI). We found that models trained using datasets from temperate regions with medium-high GDD and moderate VPD perform well whereas SOC does not significantly affect the generalisability. It is not advisable to train models with datasets constrained by GCI as this feature correlates significantly with the maize yield, and adaptation between two domains that rarely intercept will not work well. We also demonstrate that Kullback-Leibler divergence computed using features from source and target domains can be used to justify the feasibility of domain adaptation. Based on the divergence, a model trained in the US (or another region with sufficient data) is expected to work reliably in other regions through domain adaptation, especially feature-based adaptation.

A dataset of spatial distribution of bioclimatic variables in China at 1 km resolution

Bioclimatic variables are indicators reflecting the integrated relationship between living things and climate. They are often used to interprete the relationships between species, vegetations and climate in global change research, and further simulate the geographical distribution patterns of both species and vegetations, as well as their functional characteristics. Regional bioclimate datasets, however, have been rarely reported. Based on an ANUSPIN interpolated dataset (covering temperature, precipitation and sunshine percentage) of 1km-resolution climate variables in China at 30-year basis averaged from 1951 to 1980 and from 1981 to 2010, respectively, we calculated 9 kinds bioclimatic variables in this study, namely mean temperature of the coldest month, mean temperature of the warmest month, absolute maximum temperature, absolute minimum temperature, annual growing degree days above 0°C and 5°C, growing season precipitation, annual drought index and annual moisture index. We plotted their spatial distribution map and analyzed their spatial pattern and trend statistically. Comparative analysis shows that the variation range of corresponding variables is very narrow, and the statistical variables are nearly the same. Therefore, the error of this dataset mainly comes from the spatial distribution dataset of basic climatic factors, and the secondary error in the process is tiny.This dataset provides reasonable environmentally mechanistic explanations for research on the relationships between species, vegetations and climate, and offers a convenient and diverse way for researchers to use bioclimatic variables to simulate species distribution patterns, vegetation structures and functions.

Southern Range Expansion of the Emerald Ash Borer, Agrilus planipennis, in Russia Threatens Ash and Olive Trees in the Middle East and Southern Europe

Agrilus planipennis (Coleoptera: Buprestidae) is the most serious invasive pest of ash trees (Fraxinus spp., Oleaceae) in the world. It has not yet reached the range of olive tree plantations, however it has been shown to complete its life cycle in this host tree. This pest native to East Asia was first found in Europe in Moscow in 2003 and has been spreading ever since. The aims of this study were to determine if the southern border of the range has already reached the Caucasus and to assess the potential range in this region based on host availability and heat availability. In 2021, we surveyed ash trees south to the known range in Russia. We did not find the pest in six cities in the North Caucasus region but found it in the city of Azov close to the Caucasus. Analysis of information about 550 localities of ash trees in the Caucasus showed that Fraxinus spp. is common throughout the region. The calculation of annual growing degree days base 10 °C indicated that the places where Fraxinus spp. grow above 1500 m are too cold for A. planipennis and therefore could potentially become a refuge for ash trees. The spread of A. planipennis to the Caucasus is of concern. First, the forest ecosystems of this region are endangered, since European ash Fraxinus excelsior is much more common there than in the currently infested regions in Russia. Second, the Russian Caucasus can become the gateway to Georgia, Armenia, Azerbaijan, Turkey and other countries of the Middle East and Southern Europe. We propose using Fraxinus angustifolia, F. ornus and Olea europaea growing in the Caucasus and adjacent regions as sentinel trees for the monitoring and pest risk assessment of these tree species.

Low Heat Availability Could Limit the Potential Spread of the Emerald Ash Borer to Northern Europe (Prognosis Based on Growing Degree Days per Year).

Simple SummaryEmerald ash borer is a devastating pest of ash trees. This beetle, native to Asia and established in North America, European Russia and Ukraine is quickly spreading and approaching the borders of the European Union. We made the first prognosis of the potential range of this pest in Europe based on heat availability. Our calculations have shown that, in most European countries, the climate is warm enough for the establishment of the emerald ash borer. However, this pest would probably not be able to establish itself in some regions of Norway, Sweden, Finland, Ireland and Great Britain, because there is not enough heat to complete development (the summer is too cold and too short). Therefore, there is a hope that European ash (Fraxinus excelsior) could escape from the emerald ash borer in some parts of the British Isles and Scandinavia.Emerald ash borer Agrilus planipennis (Coleoptera: Buprestidae) is one of 20 priority quarantine pests of the European Union. It is native to Asia and is established in the USA, Canada, European Russia, and Ukraine. We made the first prognosis of the potential range of A. planipennis in Europe based on heat availability. Mean annual growing degree days base 10 °C (AGDD10) was calculated for each grid square (0.25° × 0.25° latitude x longitude degrees) on the Earth’s surface. Minimal AGDD10 recorded in the grid squares currently occupied by A. planipennis was 714° in Asia, 705° in North America, and 711° in European Russia. Agrilus planipennis has never been recorded in localities with AGDD10 below 700°. If the phenotypic plasticity would not allow this species to overcome this threshold, cold regions of Europe would probably not be invaded by A. planipennis. Thus, Fraxinus excelsior could potentially escape from A. planipennis in some regions of Norway, Sweden, Finland, Ireland, and Great Britain.

Could Pine Wood Nematode (Bursaphelenchus xylophilus) Cause Pine Wilt Disease or Even Establish inside Healthy Trees in Finland Now—Or Ever?

Pine wilt disease (PWD) caused by the pine wood nematode (PWN, Bursaphelenchus xylophilus) can, in suitable conditions, lead to mass mortality of susceptible trees. In the European Union, PWN is a quarantine pest. To support PWN risk management in Finland, we assessed the suitability of the Finnish present and future climate for both PWD and PWN establishment inside susceptible healthy trees. The former was done using the mean summer temperature concept and the latter by relating annual growing degree days to the likelihoods of PWN extinction and establishment inside healthy trees. The likelihoods were derived from the previously published modelling of PWN population dynamics for 139 locations in Germany. Both assessments were conducted using 10 × 10 km resolution climate data from 2000–2019 and Finland-specific climate change projections for 2030–2080. The results indicate that the present Finnish climate is too cool for both PWD and PWN establishment inside healthy trees. Furthermore, even global warming does not appear to turn the Finnish climate suitable for PWD or PWN establishment inside healthy trees by 2080, except under the worst-case representative concentration pathway scenario (RCP8.5). Consequently, giving top priority to PWN when allocating resources for biosecurity activities in Finland might deserve reconsideration.

Relative influence of stand and site factors on aboveground live-tree carbon sequestration and mortality in managed and unmanaged forests

We compiled data from several independent, long-term silvicultural studies on USDA Forest Service experimental forests across a latitudinal gradient in the northeastern and north-central U.S.A. to evaluate factors influencing aboveground live-tree carbon sequestration and mortality. Data represent five sites with more than 70,000 repeated tree records spanning eight decades, five ecoregions, and a range of stand conditions. We used these data to test the relative influence of factors such as climate, treatment history (uneven-aged or no management), species composition, and stand structural conditions on aboveground live-tree carbon sequestration and mortality in repeatedly measured trees. Relative to no management, we found that uneven-aged management tended to have a positive effect on carbon sequestration at low stocking levels and in areas of favorable climate (expressed as a combination of growing season precipitation and annual growing degree days > 5 °C). In addition, losses of carbon from the aboveground live-tree pool due to tree mortality were lower in managed than unmanaged stands. These findings suggest that there may be conditions at which rate of sequestration in living trees is higher in stands managed with uneven-aged silviculture than in unmanaged stands, and that this benefit is greatest where climate is favorable.

Plasticity and selection drive hump-shaped latitudinal patterns of flowering phenology in an invasive intertidal plant.

Patterns of flowering phenology can affect the success of plant invasions, especially when introduced species spread across a wide range of latitude into different climatic conditions. We combined a 4-yr field survey and a 3-yr common garden experiment with the invasive grass Spartina alterniflora that is now widespread along the coast of China to document the latitudinal pattern of flowering phenology, determine if phenology was related to climate or oceanographic variables, and determine whether phenology patterns were fixed versus plastic. In the field, first flowering day displayed a hump-shaped relationship with latitude, with low- and high-latitude plants flowering 100d and 10d earlier than plants at middle latitudes, respectively. Peak flowering day showed a similar hump-shaped relationship with latitude, with the interval between first and peak flowering day decreasing with increasing latitude. First flowering day had a hump-shaped relationship with annual growing degree days but a linear positive relationship with tidal range. In the common garden, first flowering day decreased linearly with increasing latitude of origin, as did peak flowering day, and the interval between first and peak flowering day increased with increasing latitude. First flowering day in the common garden had weak or no relationships with abiotic variables at the sites of origin. In both the field and common garden, first flowering day was later in site years for which plants were taller. These results indicate a high degree of plasticity in flowering phenology, with plants flowering later in the field at sites with intermediate temperatures and high tide ranges. Common garden results indicate some selection for earlier flowering at sites with low temperatures, consistent with a shorter growing season. Consistent with life-history theory, plants flowered later under conditions favoring vigorous growth. Earlier flowering and smaller size of plants at high and low latitudes suggests that S. alterniflora has already occupied much of the geographic range favorable for it on the East Coast of Asia.

The climatic space of European pollen taxa

Pollen data are widely used to reconstruct past climate changes, using relationships between modern pollen abundance in surface samples and climate at the surface-sample sites as a calibration. Visualization of modern pollen data in multidimensional climate space provides a way to establish that taxon abundances are well behaved before using them in climate reconstructions. Visualization is also helpful for ecological interpretation of variations in pollen abundance in space and time. Here, we present Generalized Additive Models for the distribution of 195 European pollen and pteridophyte spore taxa in a bioclimate space defined by seasonal temperatures (as mean temperature of the coldest month and annual growing degree days) and an annual moisture index. These models can be used to explore the realized climate niche of pollen taxa and to build statistical models for palaeoclimate reconstruction. The data set is released under a Creative Commons BY license. When using the data set, we kindly request that you cite this article.

Bergmann's and Allen's Rules in Native European and Mediterranean Phasmatodea

Bergmann’s rule states that organisms at higher latitudes should be larger and thicker than those closer to the equator to better conserve heat, and Allen’s rule states that they will have shorter and thicker limbs at higher latitudes. Alternative explanations for latitudinal size clines include plant productivity and seasonality. The rules generally hold in endotherms, but in insects different species within the same genus can respond to latitude in unpredictable ways. We present the first biogeographical analysis of these rules in stick insects (order Phasmatodea), using four European species. Their long and thin bauplan makes the Phasmatodea ideal for ecomorphological studies of body length, which could identify the evolutionary drivers of their remarkable size range (including the world’s longest insects). Using preserved specimens from collections across Europe; body segment and limb measurements were taken for both genders of the species Bacillus rossius, Clonopsis gallica, Leptynia attenuata, and Pijnackeria hispanica. Lengths and volumetric features were compared to latitude as well as annual mean temperature, net primary productivity, and annual growing degree days, using weighted linear regressions and ANOVA analyses. At lower latitudes / higher temperatures, B. rossius and L. attenuata had longer limbs [Allen clines] and were larger bodied and/or longer [converse-Bergmann clines], while the other species did not show latitudinal clines per se. This matches what was predicted based on closely related insects and the presence of large Phasmatodea in the tropics, but violates the temperature-size rule. Most variation in size could be attributed to temperature, but untested factors could also play a role Whether these ecogeographic rules hold true for tropical Phasmatodea and whether genetics or environment play are more important in determining adult length are topics for future research.

A Landscape View of Agricultural Insecticide Use across the Conterminous US from 1997 through 2012.

Simplification of agricultural landscapes is expected to have positive effects on many crop pests and negative effects on their natural enemies, potentially leading to increased pest pressure, decreased crop yield, and increased insecticide use. While many intermediate links in this causal chain have empirical support, there is mixed evidence for ultimate relationships between landscape simplification, crop yield, and insecticide use, especially at large spatial and temporal scales. We explored relationships between landscape simplification (proportion of a county in harvested cropland) and insecticide use (proportion of harvested cropland treated with insecticides), using county-level data from the US Census of Agriculture and a variety of standard and spatiotemporal regression techniques. The best model indicated that insecticide use across the US has increased between 1997 and 2012, was strongly dependent on the crops grown in a county, increased with average farm income and size, and increased with annual growing degree days. After accounting for those variables, and other unidentified spatial and temporal structure in the data, there remained a statistically significant, moderate, positive relationship between insecticide use and landscape simplification. These results lend general support to the causal chain outlined above, and to the notion that a landscape perspective is useful for managing ecosystem services that are provided by mobile organisms and valuable to agriculture.

Development of an effective and potentially scalable weather generator for temperature and growing degree days

The main purpose of this study is to develop an easy-to-use weather generator (WG) for the downscaling of gridded data to point measurements at regional scale. The WG is applied to daily averaged temperatures and annual growing degree days (GDD) of wheat. This particular choice of variables is motivated by future investigations on temperature impacts as the most important climate variable for wheat cultivation under irrigation in Iran. The proposed statistical downscaling relates large-scale ERA-40 reanalysis to local daily temperature and annual GDD. Long-term local observations in Iran are used at 16 synoptic stations from 1961 to 2001, which is the common period with ERA-40 data. We perform downscaling using two approaches: the first is a linear regression model that uses the ERA-40 fingerprints (FP) defined by the squared correlation with local variability, and the second employs a linear multiple regression (MR) analysis to relate the large-scale information at the neighboring grid points to the station data. Extending the usual downscaling, we implement a WG providing uncertainty information and realizations of the local temperatures and GDD by adding a Gaussian random noise. ERA-40 reanalysis well represents the local daily temperature as well as the annual GDD variability. For 2-m temperature, the FPs are more localized during the warm compared with the cold season. While MR is slightly superior for daily temperature time series, FP seems to perform best for annual GDD. We further assess the quality of the WGs applying probabilistic verification scores like the continuous ranked probability score (CRPS) and the respective skill score. They clearly demonstrate the superiority of WGs compared with a deterministic downscaling.

Analysis of macrophyte indicator variation as a function of sampling, temporal, and stressor effects

Biological indicators that signal changes in lake condition are essential tools for guiding resource management decisions. Macrophyte-based indicators have traditionally been selected and evaluated in the context of nutrient-based stressors, although the need to evaluate indicators that are sensitive to climate stressors has been increasingly relevant. Moreover, indicators should ideally exhibit minimal sampling variation and have low natural temporal variation so there is high power to detect changes in the mean value over time. Eight macrophyte indicators were estimated in 23 Minnesota (USA) lakes using four years of repeated surveys to estimate sampling and temporal variation, response to development (phosphorus concentration) and climate stress (annual growing degree days), and power to detect significant change at various annual sampling intervals. Indicators included a macrophyte index of biotic integrity, floristic quality index, maximum depth of growth, total species richness, common species richness, mean richness, and frequency occurrence of rooted species and Chara sp. Overall, regression and smoothed additive models indicated significant relationships of indicators to total lake phosphorus and mean annual growing degree days. The macrophyte index of biotic integrity, floristic quality index, and the frequency rooted species had minimal sampling variation in this study, were responsive to development or climate stress, and had low annual variation (coefficients of variation 0.08, 0.10, and 0.19, respectively) resulting in high to moderate power (>50%) for detecting significant change over a 20 year period. Results from these analyses will facilitate the use of precise and powerful indicators that respond to stressors that are of concern for the management of freshwater glacial lakes.

GIS-BASED ANALYSIS OF SPATIAL DISTRIBUTION PATTERNS OF GROWING DEGREE-DAYS FOR AGRICULTURAL APPLICATIONS IN IRAN

The geographical distribution of growing degree-days (GDDs) within Iran was studied using GIS-based maps. GDDs were calculated using daily thermal parameters (daily maximum and minimum air temperature). Based on the purpose of the study and climatic conditions of Iran, the average value of 5?C was chosen for GDD calculation. The calculations were carried out using daily weather data of 113 meteorological stations throughout Iran. The clustering of the 113 point stations’ data were achieved by using statistical models combined with a digital terrain model. The final outcomes were five GDD maps (two for start and end of heating period, one for January, one for cold season and the last one annual growing degree days). The relationships between calculated GDDs and key variables that may affect temperature were carefully studied. (e.g. geographical data of latitude and longitude, elevation, nearest grid distance from the sea) Geographical distributions of GDDs were found to be correlated closely with the climatic types of different regions that are mainly based on relief. The distribution of the GDDs presented in the maps showed that the calculated values were close to the measured ones, which confirmed the validity of the GIS-based approach. In few cases significant differences between predicted and calculated values were observed, mostly in the regions with less number of weather stations. Consequently, the highly accurate generated maps can be used as a useful tool for prediction of crops and pests phonological events and crop modeling.

월별 전자기후도를 이용한 생장도일 분포도 제작에 관하여

생장도일을 품종별로 계산해 두면 농작물의 지역 적응여부를 판단하는데 유용하며, 넓은 지역에 적용하여 분포도를 작성하면 수목이나 작물의 기후학적 적응도 판단의 기준으로 활용할 수 있어 농업기후지대 구분에 이용된다. 이미 제작된 30m 해상도 전자기후도를 이용하여 생장도일(GDD) 분포도를 작성할 수 있다면 현재의 기후조건에서 적지적작, 적지적수를 위한 토대를 마련할 수 있을 뿐 아니라 기후변화에 따른 향후 우리나라 농림업 분야의 적응방안을 도출하는 데 큰 도움이 될 것이다. 전자기후도 형태로 공급되는 기후학적 평년의 월별 기온자료에 의해 식물의 생장도일 분포도를 작성할 수 있는지를 경남 합천지역을 대상으로 검토한 결과, 생육임계온도 <TEX>$0^{\circ}C$</TEX>에서 계산된 GDD만이 일별 기온자료에 의해 계산된 GDD와 그 값이 유사했으며, 생육임계온도가 <TEX>$5^{\circ}C$</TEX>와 <TEX>$10^{\circ}C$</TEX>로 높아질수록 오차가 급격하게 증가하여 실용성이 떨어지는 것으로 나타났다. 실용성이 인정되는 기준온도 <TEX>$0^{\circ}C$</TEX>에서 1971-2000년 평년의 남한 전역 GDD를 30m 해상도로 추정하고, 이것을 IPCC SRES A2 시나리오(2011-2040, 2041-2700, 2071-2100년)에서 예상되는 미래 GDD 분포와 비교한 결과 100년 후에는 현재의 GDD보다 약 38% 증가할 것이며 그 증가폭은 평야지보다는 고랭지에서 현저하게 나타날 것으로 예상되었다. The concept of growing degree-days (GDD) is widely accepted as a tool to relate plant growth, development, and maturity to temperature. Information on GDD can be used to predict the yield and quality of several crops, flowering date of fruit trees, and insect activity related to agriculture and forestry. When GDD is expressed on a spatial basis, it helps identify the limits of geographical areas suitable for production of various crops and to evaluate areas agriculturally suitable for new or nonnative plants. The national digital climate maps (NDCM, the fine resolution, gridded climate data for climatological normal years) are not provided on a daily basis but on a monthly basis, prohibiting GDD calculation. We applied a widely used GDD estimation method based on monthly data to a part of the NDCM (for Hapcheon County) to produce the spatial GDD data for each month with three different base temperatures (0, 5, and <TEX>$10^{\circ}C$</TEX>). Synthetically generated daily temperatures from the NCDM were used to calculate GDD over the same area and the deviations were calculated for each month. The monthly-data based GDD was close to the reference GDD using daily data only for the case of base temperature <TEX>$0^{\circ}C$</TEX>. There was a consistent overestimation in GDD with other base temperatures. Hence, we estimated spatial GDD with base temperature <TEX>$0^{\circ}C$</TEX> over the entire nation for the current (1971-2000, observed) and three future (2011-2040, 2041-2070, and 2071-2100, predicted) climatological normal years. Our estimation indicates that the annual GDD in Korea may increase by 38% in 2071-2100 compared with that in 1971-2000.

A GROWING DEGREE-DAYS BASED TIME-SERIES ANALYSIS FOR PREDICTION OF SCHISTOSOMA JAPONICUM TRANSMISSION IN JIANGSU PROVINCE, CHINA

It has been suggested that global warming may alter the frequency and transmission dynamics of vector-borne diseases. To test this claim for schistosomiasis, we conducted a time-series analysis from 1972-2002 for 39 of the 70 counties of Jiangsu province, eastern China, where Schistosoma japonicum is partially endemic. We used a modeling approach to estimate the annual growing degree-days (AGDD), employing a lower temperature threshold of 15.3 degrees C. Our final model included both temporal and spatial components, the former consisting of second order polynomials in time plus a seasonality component, whereas the spatial trend was formed by second order polynomials of the coordinates plus the thin-plate smoothing splines. We found that temperature increased over the past 30 years in all observing stations. There were distinct temporal trends with seasonality and periodicities of 12, 6, and 3 months, whereas only marginal spatial variation was observed. The predicted AGDDs for 2006 and 2003 showed increases for the entire Jiangsu province, with the AGDDs difference between these two time points exhibiting an increase from north to south. Our data suggest that changes in temperature will alter the extent and level of schistosomiasis transmission, which is relevant for the control of S. japonicum in a future warmer China.

Relationships among phenological growing season, time‐integrated normalized difference vegetation index and climate forcing in the temperate region of eastern China

AbstractPhenological, meteorological, and time‐integrated normalized difference vegetation index (TI NDVI) data from 1982 to 1993, at three sample stations, were used to investigate the response of the growing season of local plant communities to climate change and the linkage of satellite sensor‐derived greenness to the surface growing season. Results suggest that mean air temperature and growing degree days (GDDs) above 5 °C during late winter and spring, and precipitation in autumn, are the most important controls on the beginning and end dates of the growing season (BGS and EGS). In contrast, annual mean air temperature, annual GDD totals, mean air temperature during late winter and spring, and growing season TI NDVI are the most important controls on length of the growing season (LGS).Using correlation and regression analysis, simple and multiple linear regression models were developed for individual and all stations. Since the standard error of the estimates (SE) of the BGS models for all stations are smaller than those of the EGS models, estimates of the beginning date of the growing season are probably more reliable than estimates of the end date. On average, if the mean air temperature in late winter and spring increases by 1° C, then the beginning date of the growing season will advance 5–6 days, and the end date will be 5 days later. Moreover, if autumn precipitation increases 100 mm, then the end date will advance 6–8 days. In terms of the LGS models, mean air temperature in late winter and spring, annual mean air temperature, and annual GDD totals have significant positive correlations with growing season duration, whereas growing season TI NDVI has a negative relationship. Comparing the SE of different LGS models, those developed with each of the three temperature variables fit the observed growing season duration data much better than those using growing season TI NDVI. Copyright © 2002 Royal Meteorological Society.

The effects of fragmentation and disturbance of rainforest on ground‐dwelling small mammals on the Robertson Plateau, New South Wales, Australia

A bioclimatic model based on physiological constraints to plant growth and regeneration is used here in an empirical way to describe the present natural distributions of northern Europe's major trees. Bioclimatic variables were computed from monthly means of temperature, precipitation and sunshine (%) interpolated to a 10' grid taking into account elevation. Minimum values of mean coldest-month temperature (T c ) and 'effective' growing degree days (GDD*) were fitted to species' range limits. GDD* is total annual growing degree days (GDD) minus GDD to budburst (GDD°). Each species was assigned to one of the chilling-response categories identified by Murray, Cannell & Smith (1989) to calculate GDD°. Maximum T c values were fitted to continental species' mild-winter limits and other deciduous species' warm-winter limits. Minimum values of relative growing-season moisture availability (α*) were estimated from silvics. Growth indices were calculated based on potential net assimilation (a quadratic in daily temperature) and α*. Growth can be rapid near a range limit, e.g. Picea abies (L.) Karsten in southern Sweden. Climate changes expected for CO 2 doubling were projected on to the grid. Simulated distribution changes reflected interspecific differences in response to changing seasonality. Chilling responses proved important, e.g. the predicted range limit of Fagus sylvatica L. contracts in the west while expanding northwards as winters warm more than summers. Transient responses to climate change can be modelled using the same information provided that fundamental and realized niche limitations are distinguished-a caveat that underlines the dearth of experimental information on the climatic requirements for growth, and especially regeneration, of many important trees.

Holocene climatic change and the distribution of peatlands in western interior Canada

Dates of basal fen peat at 52 locations across west-central Canada indicate that peat deposition began <6000 yr B.P. in a broad zone north of the present-day grassland. The isopleth of >6000 yr B.P. basal fen peat parallels the foothills of the Rocky Mountains, and extends eastward along 54°30′ north latitude. The absence of >6000 yr B.P. peat within this zone is attributed to a warmdry early to middle Holocene climate that caused severe seasonal droughts and prevented the establishment of peat-forming fen vegetation. Wetlands west (and probably north) of this line experienced lower water tables, but supported fen vegetation. As the climate became cooler and moister, stable water tables allowed the development of fens and rapid peat accumulation ensued, reaching the modern distribution of fens between 2000 and 3500 yr B.P. Projections of climatic parameters indicate that the mean annual growing degree days were 6 to 21% higher during the early and middle Holocene, and that precipitation was reduced through most of the area, resulting in much higher (by 17 to 29%) aridity than at present.