Reconstruction of climate change during the Holocene in western and central Europe based on pollen records of indicator species

On the basis of distribution maps showing the first pollen occurrences in the Holocene of the well-known climate indicators Hedera, Ilex and Viscum as well as data for Corylus, a series of maps have been prepared that show summer and winter isotherms at various time intervals during the Holocene. From these maps climate curves for Amsterdam, the Netherlands have been set out. These were compared with curves for the Eemian at the same site. In both of these warm periods there is evidence for increased seasonality in the early phases which were relatively continental. Changes in insolation could account for such differences. Summer optima occurred earlier than winter optima. Changes in land-sea distribution are important, especially with regard to the patterns in winter climate. During the latter half of the Eemian, the climate was distinctly more oceanic than in the Holocene. Early in the Holocene, an influx of warm ocean water resulted in higher winter temperatures in the Gulf of Biscay, the Irish Sea, and areas east of Skagerrak-Kattegat. Temperature decline after the climatic optimum was greatest in the north, i.e. at 60°N, where a depression in the order of 2°C in summer and 2–3°C in winter occurred. Temperature decline was less farther south, i.e. at ca. 50°N, where a distinct west-east gradient in temperature change can be observed.     

Uphill shifts in distribution of butterflies in the Czech Republic: effects of changing climate detected on a regional scale

Aim To assess whether altitude changes in the distribution of butterflies during the second half of the 20th century are consistent with climate warming scenarios. Location The Czech Republic. Methods Distributional data were taken from a recent butterfly distribution atlas, which maps all Czech butterflies using a grid of 10′ longitude to 6′ latitude, equivalent to about 11.1 × 12 km. Cell altitude was used as an independent variable, and altitudinal ranges of individual species (less migrants, extinct species, recent arrivals and extremely rare species) in 1950–80 vs. 1995–2001 and in 1950–80, 1981–94, 1995–2001 were compared using U‐tests and linear regressions. Results Of 117 (U‐tests) and 119 (regressions) species, we found significant uphill increases in 15 and 12 species, respectively. The two groups were nested; none (U‐test) and one (regression) species showed a significant altitudinal decrease. Binomial tests of frequencies of signs of the U‐tests and regression coefficients, including nonsignificant ones, also showed that the increases prevailed. The mean and median of the significant shifts were 60 and 90 m, respectively, and the maximum shift per species was 148 m. The recording effort in individual time periods was not biased with respect to altitude. Main conclusion Altitude shifts in the distribution of Czech butterflies are already detectable on the coarse scales of standard distribution maps. The increasing species do not show any consistent pattern in habitat affiliations, conservation status and mountain vs. nonmountain distribution, which renders climatic explanation as the most likely cause of the distributional shifts.     

Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful?

Modelling strategies for predicting the potential impacts of climate change on the natural distribution of species have often focused on the characterization of a species’ bioclimate envelope. A number of recent critiques have questioned the validity of this approach by pointing to the many factors other than climate that play an important part in determining species distributions and the dynamics of distribution changes. Such factors include biotic interactions, evolutionary change and dispersal ability. This paper reviews and evaluates criticisms of bioclimate envelope models and discusses the implications of these criticisms for the different modelling strategies employed. It is proposed that, although the complexity of the natural system presents fundamental limits to predictive modelling, the bioclimate envelope approach can provide a useful first approximation as to the potentially dramatic impact of climate change on biodiversity. However, it is stressed that the spatial scale at which these models are applied is of fundamental importance, and that model results should not be interpreted without due consideration of the limitations involved. A hierarchical modelling framework is proposed through which some of these limitations can be addressed within a broader, scale‐dependent context.     

The ability of climate envelope models to predict the effect of climate change on species distributions

Climate envelope models (CEMs) have been used to predict the distribution of species under current, past, and future climatic conditions by inferring a species' environmental requirements from localities where it is currently known to occur. CEMs can be evaluated for their ability to predict current species distributions but it is unclear whether models that are successful in predicting current distributions are equally successful in predicting distributions under different climates (i.e. different regions or time periods). We evaluated the ability of CEMs to predict species distributions under different climates by comparing their predictions with those obtained with a mechanistic model (MM). In an MM the distribution of a species is modeled based on knowledge of a species' physiology. The potential distributions of 100 plant species were modeled with an MM for current conditions, a past climate reconstruction (21 000 years before present) and a future climate projection (double preindustrial CO₂ conditions). Point localities extracted from the currently suitable area according to the MM were used to predict current, future, and past distributions with four CEMs covering a broad range of statistical approaches: Bioclim (percentile distributions), Domain (distance metric), GAM (general additive modeling), and Maxent (maximum entropy). Domain performed very poorly, strongly underestimating range sizes for past or future conditions. Maxent and GAM performed as well under current climates as under past and future climates. Bioclim slightly underestimated range sizes but the predicted ranges overlapped more with the ranges predicted with the MM than those predicted with GAM did. Ranges predicted with Maxent overlapped most with those produced with the MMs, but compared with the ranges predicted with GAM they were more variable and sometimes much too large. Our results suggest that some CEMs can indeed be used to predict species distributions under climate change, but individual modeling approaches should be validated for this purpose, and model choice could be made dependent on the purpose of a particular study.     

The effects of climate change on species composition,succession and phenology: a case study

Climate change and its role in altering biological interactions and the likelihood of invasion by introduced species in marine systems have received increased attention in recent years. It is difficult to forecast how climate change will influence community function or the probability of invasion as it alters multiple marine environmental parameters including rising water temperature, lower salinity and pH. In the present study, we correlate changes in environmental parameters to shifts in species composition in a subtidal community in Newcastle, NH through comparison of two, 3‐year periods separated by 23 years (1979–1981 and 2003–2005). We observed concurrent shifts in climate related factors and in groups of organisms that dominate the marine community when comparing 1979–1981 to 2003–2005. The 1979–1981 community was dominated by perennial species (mussels and barnacles). In contrast, the 2003–2005 community was dominated by annual native and invasive tunicates (sea‐squirts). We also observed a shift in the environmental factors that characterized both communities. Dissolved inorganic nitrogen and phosphate characterized the 1979–1981 community while sea surface temperature, pH, and chlorophyll a characterized the 2003–2005 community. Elongated warmer water temperatures, through the fall and early winter months of the 2000s, extended the growing season of native organisms and facilitated local dominance of invasive species. Additionally, beta‐diversity was greater between 2003–2005 than 1979–1981 and driven by larger numbers of annual species whose life‐history characteristics (e.g., timing and magnitude of recruitment, growth and mortality) are driven by environmental parameters, particularly temperature.     

Ecosystem dynamics based on plankton functional types for global ocean biogeochemistry models

Ecosystem processes are important determinants of the biogeochemistry of the ocean, and they can be profoundly affected by changes in climate. Ocean models currently express ecosystem processes through empirically derived parameterizations that tightly link key geochemical tracers to ocean physics. The explicit inclusion of ecosystem processes in models will permit ecological changes to be taken into account, and will allow us to address several important questions, including the causes of observed glacial–interglacial changes in atmospheric trace gases and aerosols, and how the oceanic uptake of CO₂ is likely to change in the future. There is an urgent need to assess our mechanistic understanding of the environmental factors that exert control over marine ecosystems, and to represent their natural complexity based on theoretical understanding. We present a prototype design for a Dynamic Green Ocean Model (DGOM) based on the identification of (a) key plankton functional types that need to be simulated explicitly to capture important biogeochemical processes in the ocean; (b) key processes controlling the growth and mortality of these functional types and hence their interactions; and (c) sources of information necessary to parameterize each of these processes within a modeling framework. We also develop a strategy for model evaluation, based on simulation of both past and present mean state and variability, and identify potential sources of validation data for each. Finally, we present a DGOM-based strategy for addressing key questions in ocean biogeochemistry. This paper thus presents ongoing work in ocean biogeochemical modeling, which, it is hoped will motivate international collaborations to improve our understanding of the role of the ocean in the climate system.     

Effects of elevated atmospheric CO2, cutting frequency, and differential day/night atmospheric warming on root growth and turnover of Phalaris swards

We investigated seasonal root production and root turnover of fertilized and well‐watered monocultures of Phalaris for 2 years using minirhizotrons installed in six newly designed temperature gradient tunnels, combined with sequential soil coring. Elevated atmospheric CO₂ treatments were combined with two cutting frequencies and three warming scenarios: no warming, +3.0/+3.0 and +2.2/+4.0°C (day/night) atmospheric warming. The elevated CO₂ treatment increased both new and net root length production primarily when combined with atmospheric warming, where the constant warming treatment had a greater positive effect than the increased night‐time warming treatment. Responses to elevated CO₂ were greater when the swards were cut more frequently and responsiveness varied with season. For Phalaris swards, 17% of total net primary productivity went belowground. On account of root turnover, only one‐third of the new roots produced in the year following establishment could be expected, on average, to be recovered from soil cores. The interaction between the effects of CO₂ and warming, combined with the differential effects of the two warming treatments, has important implications for modelling belowground responses to projected climate change.