Using large-scale climate indices in climate change ecology studies

Recently, climate change research in ecology has embraced the use of large-scale climate indices in long-term, retrospective studies. In most instances, these indices are related to large-scale teleconnection and atmospheric patterns of which over a dozen have been identified. Although most of these relate to different geographical areas, many are related and interact. Consequently, even the simple task of selecting one to use in ecological research has become complicated, despite our ability to disentangle the results from analyses involving large-scale climate indices. Leaning upon recent reviews of the definition and functioning of large-scale climate indices, as well as reviews on the relationship between these and concomitant changes in ecological variables, we focus here on the usefulness of large-scale climate indices in different aspects of climate change ecology. By providing a general framework for using climate indices, we illustrate the potential advantages of their utility by integrating three case histories focusing on two groups of evolutionarily distinct organisms: birds and mammals.     

Validation of species–climate impact models under climate change

Increasing concern over the implications of climate change for biodiversity has led to the use of species–climate envelope models to project species extinction risk under climate‐change scenarios. However, recent studies have demonstrated significant variability in model predictions and there remains a pressing need to validate models and to reduce uncertainties. Model validation is problematic as predictions are made for events that have not yet occurred. Resubstituition and data partitioning of present‐day data sets are, therefore, commonly used to test the predictive performance of models. However, these approaches suffer from the problems of spatial and temporal autocorrelation in the calibration and validation sets. Using observed distribution shifts among 116 British breeding‐bird species over the past ～20 years, we are able to provide a first independent validation of four envelope modelling techniques under climate change. Results showed good to fair predictive performance on independent validation, although rules used to assess model performance are difficult to interpret in a decision‐planning context. We also showed that measures of performance on nonindependent data provided optimistic estimates of models' predictive ability on independent data. Artificial neural networks and generalized additive models provided generally more accurate predictions of species range shifts than generalized linear models or classification tree analysis. Data for independent model validation and replication of this study are rare and we argue that perfect validation may not in fact be conceptually possible. We also note that usefulness of models is contingent on both the questions being asked and the techniques used. Implementations of species–climate envelope models for testing hypotheses and predicting future events may prove wrong, while being potentially useful if put into appropriate context.     

Influence of local climate and climate change on aeroterrestrial phototrophic biofilms

Aeroterrestrial phototrophic biofilms colonize natural and man-made surfaces and may damage the material they settle on. The occurrence of biofilms varies between regions with different climatic conditions. The aim of this study was to evaluate the influence of meteorological factors on the growth of aeroterrestrial phototrophs. Phototrophic biomass was recorded on roof tiles at six sites within Germany five times over a period of five years and compared to climatic parameters from neighboring weather stations. All correlating meteorological factors influenced water availability on the surface of the roof tiles. The results indicate that the frequency of rainy days and not the mean precipitation per season is more important for biofilm proliferation. It is also inferred that the macroclimate is more important than the microclimate. In conclusion, changed (regional) climatic conditions may determine where in central Europe global change will promote or inhibit phototrophic growth in the future.     

Choice of baseline climate data impacts projected species' responses to climate change

Climate data created from historic climate observations are integral to most assessments of potential climate change impacts, and frequently comprise the baseline period used to infer species‐climate relationships. They are often also central to downscaling coarse resolution climate simulations from General Circulation Models (GCMs) to project future climate scenarios at ecologically relevant spatial scales. Uncertainty in these baseline data can be large, particularly where weather observations are sparse and climate dynamics are complex (e.g. over mountainous or coastal regions). Yet, importantly, this uncertainty is almost universally overlooked when assessing potential responses of species to climate change. Here, we assessed the importance of historic baseline climate uncertainty for projections of species' responses to future climate change. We built species distribution models (SDMs) for 895 African bird species of conservation concern, using six different climate baselines. We projected these models to two future periods (2040–2069, 2070–2099), using downscaled climate projections, and calculated species turnover and changes in species‐specific climate suitability. We found that the choice of baseline climate data constituted an important source of uncertainty in projections of both species turnover and species‐specific climate suitability, often comparable with, or more important than, uncertainty arising from the choice of GCM. Importantly, the relative contribution of these factors to projection uncertainty varied spatially. Moreover, when projecting SDMs to sites of biodiversity importance (Important Bird and Biodiversity Areas), these uncertainties altered site‐level impacts, which could affect conservation prioritization. Our results highlight that projections of species' responses to climate change are sensitive to uncertainty in the baseline climatology. We recommend that this should be considered routinely in such analyses.     

Impacts of climate change on paddy rice yield in a temperate climate

The crop simulation model is a suitable tool for evaluating the potential impacts of climate change on crop production and on the environment. This study investigates the effects of climate change on paddy rice production in the temperate climate regions under the East Asian monsoon system using the CERES‐Rice 4.0 crop simulation model. This model was first calibrated and validated for crop production under elevated CO₂ and various temperature conditions. Data were obtained from experiments performed using a temperature gradient field chamber (TGFC) with a CO₂ enrichment system installed at Chonnam National University in Gwangju, Korea in 2009 and 2010. Based on the empirical calibration and validation, the model was applied to deliver a simulated forecast of paddy rice production for the region, as well as for the other Japonica rice growing regions in East Asia, projecting for years 2050 and 2100. In these climate change projection simulations in Gwangju, Korea, the yield increases (+12.6 and + 22.0%) due to CO₂ elevation were adjusted according to temperature increases showing variation dependent upon the cultivars, which resulted in significant yield decreases (?22.1% and ?35.0%). The projected yields were determined to increase as latitude increases due to reduced temperature effects, showing the highest increase for any of the study locations (+24%) in Harbin, China. It appears that the potential negative impact on crop production may be mediated by appropriate cultivar selection and cultivation changes such as alteration of the planting date. Results reported in this study using the CERES‐Rice 4.0 model demonstrate the promising potential for its further application in simulating the impacts of climate change on rice production from a local to a regional scale under the monsoon climate system.     

Palms tracking climate change

Aim  Many species are currently expanding their ranges in response to climate change, but the mechanisms underlying these range expansions are in many cases poorly understood. In this paper we explore potential climatic factors governing the recent establishment of new palm populations far to the north of any other viable palm population in the world.
Location  Southern Switzerland, Europe, Asia and the world.
Methods  We identified ecological threshold values for the target species, Trachycarpus fortunei , based on gridded climate data, altitude and distributional records from the native range and applied them to the introduced range using local field monitoring and measured meteorological data as well as a bioclimatic model.
Results  We identified a strong relationship between minimum winter temperatures, influenced by growing season length and the distribution of the palm in its native range. Recent climate change strongly coincides with the palm's recent spread into southern Switzerland, which is in concert with the expansion of the global range of palms across various continents.
Main conclusions  Our results strongly suggest that the expansion of palms into (semi-)natural forests is driven by changes in winter temperature and growing season length and not by delayed population expansion. This implies that this rapid expansion is likely to continue in the future under a warming climate. Palms in general, and T. fortunei in particular, are significant bioindicators across continents for present-day climate change and reflect a global signal towards warmer conditions.     

Indoor versus outdoor climate

Investigations in this field have been carried out before. Some of them will be mentioned in conjunction with this investigation. The previous investigations were about pollutants that infiltrate a building or come in with the ventilation air. This was one of the reasons that so-called natural ventilation began to be abandoned in the 1950s. Prior to that, ventilation air was taken directly from the street. In fact, the conditions that will be investigated here received attention long ago. One of the reasons that the outdoor conditions have been considered is because of the transition from older ventilation systems to current ones, where air may be taken from roof level and subjected to some treatment and cleaning. Although the subject is understood at least qualitatively, it can be interesting to look at it again. Modern calculation methods make it easier to study the problem quantitively, i.e., to calculate the indoor concentrations that can arise as a result of pollutants in the outdoor air. Such calculations can also give an idea of how long high levels of pollutants can be maintained under various circumstances.     

The climate of Atndalen

The climate of Atndalen Valley is described by data collected by the standard network of stations currently run by the Norwegian Meteorological institute. It consists of one weather station (Sørneset) with full instrumental equipment, and three precipitation stations with a reduced set of equipment. At the latter stations, precipitation, snow depth, and snow cover are observed. Most of the stations, including the weather station, are situated in the central part of the watershed, near Atnsjøen. The climate of the Atndalen is of a continental type with precipitation minimum in late winter or spring and maximum during summer. The mean annual precipitation is about 500 mm near Atnsjøen (701 m a.s.l.) for the 30 year normal period 1961–1990. At the meteorological station Sørneset the warmest month is July, 11.2?°C, while the coldest month is January, ?9.9?°C, i.e. an annual amplitude of 21.1?°C. The mean cloud cover varies from 4.5 oktas in February to 5.4 oktas in July, September and October. The highest ratio of relative sunshine is about 50% in spring. The mean snow depth increases during winter and early spring and reaches its maximum of 68 cm in March. The snow cover disappears on 9 May ±12 days and establishes on 5 November ±18 days. Variations in precipitation (since 1904) and temperature (since 1864) were studied on a decadal time scale by Gaussian filtering technique, and the significance of trends on the 0.05 level were studied by the Mann–Kendall test. For the whole period no significant trend in annual precipitation was detected. The maximum value was located to the 1920s and the minimum value to the 1910s. Annual mean temperature has increased significantly since 1864, and the classical temperature optimum in the 1930s was surpassed in the 1990s. By adopting a sinus model including the first Fourier component, trends and variations in climatological periods as well as heat and frost sums were studied. The frost free period has since 1864 increased by 13 days within 100 years based on a linear trend line. Earlier passing dates in spring largely account for the increase. The length of the growth season also increased up to about 1950. The annual heat sum shows a linear increase of about 103 daydegrees per 100 years while the annual frost sum varies considerably from period to period and fitted badly with a linear model.