Cause-effect modeling as a general method for describing and studying phenomena in complex hierarchical systems

A strict definition of a cause-effect model of a complex phenomenon is given, and the rules for presenting such models in the form of cause-effect diagrams are formulated. The relationship between the cause-effect modeling and conventional methods of mathematical modeling is analyzed. Examples of the cause-effect models (diagrams) of phenomena of various physical nature are presented, and the application of these models to some specific problems is shown. In particular, the mechanism of renormalizing the rate constants of chemical reactions is considered in terms of dissipative resonance. An example of renormalizing the parameters of climate sensitivity and the relaxation time of the Earth’s climatic system in terms of a two-component (CO₂ + H₂O) greenhouse effect is considered.     

Midpoints versus endpoints: The sacrifices and benefits

On May 25–26, 2000 in Brighton (England), the third in a series of international workshops was held under the umbrella of UNEP addressing issues in Life Cycle Impact Assessment (LCIA). The workshop provided a forum for experts to discuss midpoint vs. endpoint modeling. Midpoints are considered to be links in the cause-effect chain (environmental mechanism) of an impact category, prior to the endpoints, at which characterization factors or indicators can be derived to reflect the relative importance of emissions or extractions. Common examples of midpoint characterization factors include ozone depletion potentials, global warming potentials, and photochemical ozone (smog) creation potentials. Recently, however, some methodologies have adopted characterization factors at an endpoint level in the cause-effect chain for all categories of impact (e.g., human health impacts in terms of disability adjusted life years for carcinogenicity, climate change, ozone depletion, photochemical ozone creation; or impacts in terms of changes in biodiversity, etc.). The topics addressed at this workshop included the implications of midpoint versus endpoint indicators with respect to uncertainty (parameter, model and scenario), transparency and the ability to subsequently resolve trade-offs across impact categories using weighting techniques. The workshop closed with a consensus that both midpoint and endpoint methodologies provide useful information to the decision maker, prompting the call for tools that include both in a consistent framework.     

Within‐taxon niche structure: niche conservatism,divergence and predicted effects of climate change

Several studies have observed that taxa below the level of species can vary in the degree to which they differ from one another in the environmental space they occupy. These patterns of within‐species niche variation raise the question of whether these differences should be considered when developing models for predicting the potential effects of climate change on species distributions. We address this question with two divergent datasets, one on sister species and subspecies from the European herpetofauna, the other on subspecies of breeding birds in North America. Atlas and observation data come from the Atlas of Amphibians and Reptiles in Europe and the North American Breeding Bird Survey, respectively. We develop boosted regression tree models of climate–distribution relationships and project the predicted geographic range of each taxon using interpolated weather station data and modeled climate for the year 2080. We find differences between models that distinguish the contributions of subtaxa and those that do not, in terms of prediction of both current and future distributions. In comparison to models that ignore sub‐taxon structure, models that incorporate this structure generally predict larger areas of suitable conditions, consistently perform better, if only marginally, as measured by cross‐validated AUC, and can reveal divergent potential effects of climate change on subtaxa. Differences in niche occupancy and predicted distribution appear between closely related taxa regardless of their phylogenetic distinctness. For these reasons, information on subtaxon membership and phylogeographic structure should be included in modeling exercises when available, in order to identify both the contribution of these units to the niche occupancy of species and the potentially distinct responses of subtaxa to climate change.     

Recent field findings and modeling on non-structural carbohydrates (NSCs): How to synthesize?

With growing interest in tree decline and die-back events due to increased climate variability, ecophysiological roles and dynamics of non-structural carbohydrates (NSCs) have drawn wide attention recently. Accordingly, a lot of field data have been collected, but these achievements were not well incorporated in process-based vegetation models yet, where NSCs ecophysiology was implicitly applied or ignored. This review tried to fill the knowledge gap between recent developments of empirical and modeling studies on NSCs ecophysiology. We summarized the characteristics and dynamics of NSCs with their respective roles in tree physiology and tree mortality recently found in field studies; examined how these findings have been incorporated into vegetation models so far; then, provided alternative modeling approaches of NSCs dynamics and allocation strategies. As result, we addressed five key modeling issues in simulating spatial and temporal patterns of NSCs dynamics across different scales as follows: (1) interconversion between dual NSCs pools (i.e., rapid soluble sugar and slow starch pools), (2) incorporation of the sink-limited growth allocation strategy, (3) hydraulic limitation of NSCs transports between organs, (4) feedback mechanisms between tree NSCs and root symbionts, and (5) large-scale simulations of NSCs dynamics. This review emphasizes the limitation of traditional source-limited models to simulate die-back and recovery of various tree biomes. The development of process-based vegetation models considering NSCs ecophysiology explicitly will help to enhance our modeling capacity to understand vegetation responses to climate change.     

Integrated analysis of tropical trees growth: a multivariate approach

BACKGROUND AND AIMS: One of the problems analysing cause-effect relationships of growth and environmental factors is that a single factor could be correlated with other ones directly influencing growth. One attempt to understand tropical trees' growth cause-effect relationships is integrating research about anatomical, physiological and environmental factors that influence growth in order to develop mathematical models. The relevance is to understand the nature of the process of growth and to model this as a function of the environment. METHODS: The relationships of Aphananthe monoica, Pleuranthodendron lindenii and Psychotria costivenia radial growth and phenology with environmental factors (local climate, vertical strata microclimate and physical and chemical soil variables) were evaluated from April 2000 to September 2001. The association among these groups of variables was determined by generalized canonical correlation analysis (GCCA), which considers the probable associations of three or more data groups and the selection of the most important variables for each data group. KEY RESULTS: The GCCA allowed determination of a general model of relationships among tree phenology and radial growth with climate, microclimate and soil factors. A strong influence of climate in phenology and radial growth existed. Leaf initiation and cambial activity periods were associated with maximum temperature and day length, and vascular tissue differentiation with soil moisture and rainfall. The analyses of individual species detected different relationships for the three species. CONCLUSIONS: The analyses of the individual species suggest that each one takes advantage in a different way of the environment in which they are growing, allowing them to coexist.     

A Bayesian approach for temporally scaling climate for modeling ecological systems

With climate change becoming more of concern, many ecologists are including climate variables in their system and statistical models. The Standardized Precipitation Evapotranspiration Index (SPEI) is a drought index that has potential advantages in modeling ecological response variables, including a flexible computation of the index over different timescales. However, little development has been made in terms of the choice of timescale for SPEI. We developed a Bayesian modeling approach for estimating the timescale for SPEI and demonstrated its use in modeling wetland hydrologic dynamics in two different eras (i.e., historical [pre‐1970] and contemporary [post‐2003]). Our goal was to determine whether differences in climate between the two eras could explain changes in the amount of water in wetlands. Our results showed that wetland water surface areas tended to be larger in wetter conditions, but also changed less in response to climate fluctuations in the contemporary era. We also found that the average timescale parameter was greater in the historical period, compared with the contemporary period. We were not able to determine whether this shift in timescale was due to a change in the timing of wet–dry periods or whether it was due to changes in the way wetlands responded to climate. Our results suggest that perhaps some interaction between climate and hydrologic response may be at work, and further analysis is needed to determine which has a stronger influence. Despite this, we suggest that our modeling approach enabled us to estimate the relevant timescale for SPEI and make inferences from those estimates. Likewise, our approach provides a mechanism for using prior information with future data to assess whether these patterns may continue over time. We suggest that ecologists consider using temporally scalable climate indices in conjunction with Bayesian analysis for assessing the role of climate in ecological systems.     

Climate change,woodpeckers, and forests: Current trends and future modeling needs

The structure and composition of forest ecosystems are expected to shift with climate‐induced changes in precipitation, temperature, fire, carbon mitigation strategies, and biological disturbance. These factors are likely to have biodiversity implications. However, climate‐driven forest ecosystem models used to predict changes to forest structure and composition are not coupled to models used to predict changes to biodiversity. We proposed integrating woodpecker response (biodiversity indicator) with forest ecosystem models. Woodpeckers are a good indicator species of forest ecosystem dynamics, because they are ecologically constrained by landscape‐scale forest components, such as composition, structure, disturbance regimes, and management activities. In addition, they are correlated with forest avifauna community diversity. In this study, we explore integrating woodpecker and forest ecosystem climate models. We review climate–woodpecker models and compare the predicted responses to observed climate‐induced changes. We identify inconsistencies between observed and predicted responses, explore the modeling causes, and identify the models pertinent to integration that address the inconsistencies. We found that predictions in the short term are not in agreement with observed trends for 7 of 15 evaluated species. Because niche constraints associated with woodpeckers are a result of complex interactions between climate, vegetation, and disturbance, we hypothesize that the lack of adequate representation of these processes in the current broad‐scale climate–woodpecker models results in model–data mismatch. As a first step toward improvement, we suggest a conceptual model of climate–woodpecker–forest modeling for integration. The integration model provides climate‐driven forest ecosystem modeling with a measure of biodiversity while retaining the feedback between climate and vegetation in woodpecker climate change modeling.     

Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal‐scale biological variability

In areas of the North Pacific that are largely free of overfishing, climate regime shifts – abrupt changes in modes of low‐frequency climate variability – are seen as the dominant drivers of decadal‐scale ecological variability. We assessed the ability of leading modes of climate variability [Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), Arctic Oscillation (AO), Pacific‐North American Pattern (PNA), North Pacific Index (NPI), El Niño‐Southern Oscillation (ENSO)] to explain decadal‐scale (1965–2008) patterns of climatic and biological variability across two North Pacific ecosystems (Gulf of Alaska and Bering Sea). Our response variables were the first principle component (PC1) of four regional climate parameters [sea surface temperature (SST), sea level pressure (SLP), freshwater input, ice cover], and PCs 1–2 of 36 biological time series [production or abundance for populations of salmon (Oncorhynchus spp.), groundfish, herring (Clupea pallasii), shrimp, and jellyfish]. We found that the climate modes alone could not explain ecological variability in the study region. Both linear models (for climate PC1) and generalized additive models (for biology PC1–2) invoking only the climate modes produced residuals with significant temporal trends, indicating that the models failed to capture coherent patterns of ecological variability. However, when the residual climate trend and a time series of commercial fishery catches were used as additional candidate variables, resulting models of biology PC1–2 satisfied assumptions of independent residuals and out‐performed models constructed from the climate modes alone in terms of predictive power. As measured by effect size and Akaike weights, the residual climate trend was the most important variable for explaining biology PC1 variability, and commercial catch the most important variable for biology PC2. Patterns of climate sensitivity and exploitation history for taxa strongly associated with biology PC1–2 suggest plausible mechanistic explanations for these modeling results. Our findings suggest that, even in the absence of overfishing and in areas strongly influenced by internal climate variability, climate regime shift effects can only be understood in the context of other ecosystem perturbations.     

基于激光雷达数据的物种分布模拟: 以美国加州内华达山脉南部区域食鱼貂分布模拟为例

生态位模型通过拟合物种分布与环境变量之间的关系提供物种空间分布预测, 在生物多样性研究中有广泛应用。激光雷达(LiDAR)是一种新兴的主动遥感技术, 已被大量应用于森林三维结构信息的提取, 但其在物种分布模拟的应用研究比较缺乏。本研究以美国加州内华达山脉南部地区的食鱼貂(Martes pennanti)的分布模拟为例, 探索LiDAR技术在物种分布模拟中的有效性。生态位模型采用5种传统多类分类器, 包括神经网络、广义线性模型、广义可加模型、最大熵模型和多元自适应回归样条模型, 并使用正样本-背景学习(presence and background learning, PBL)算法进行模型校正; 同时对这5种模型使用加权平均进行模型集成, 作为第6个模型。此外, 一类最大熵模型也被用于模拟该物种的空间分布。模型的连续输出和二值输出分别使用AUC (area under the receiver operating characteristic curve)以及基于正样本-背景数据的评价指标F_pb进行评价。结果表明, 仅考虑气候因子(温度和降水)时, 7个模型的AUC和F_pb平均值分别为0.779和1.077; 当考虑LiDAR变量(冠层容重、枝下高、叶面积指数、高程、坡度等)后, AUC和F_pb分别为0.800和1.106。该研究表明, LiDAR数据能够提高食鱼貂空间分布的预测精度, 在物种分布模拟方面存在一定的应用价值。     

Phase diagrams for DNA crystallization systems

Phase diagrams for several oligonucleotide duplex-spermine systems have been constructed. These diagrams characterize the duplex and spermine concentrations ranges in which crystalline precipitates are formed. All of them are wedge-like form. The slope of the upper branch of the diagram is determined by the oligonucleotide length. The position of the lower branch depends on both the nucleotide sequence and its length. The position of the lower branch depends on both the nucleotide sequence and its length. It has been shown that the addition to the system of MgCl2 and NaCl salts and MPD results in specific changes in the diagrams. A model for oligonucleotide duplex-spermine system has been suggested which explains the main characteristic features of the obtained phase diagrams. The experimental phase diagrams for the (pGpT)n (pApC)n-spermine system (n = 2,3,4) have been analyzed ion terms of this model and the values of the binding constants of spermine and Mg2+ ions binding to duplexes have been determined. It permitted to identify the complexes that precipitated in different regions of the phase diagrams under various conditions. The diagram obtained in the presence of a cobalt hexammine counterion is also considered. It has been shown that this phase diagram, in general, is similar to those obtained for the oligonucleotide duplex-spermine system.     

Climate Change-Induced Range Expansion of a Subterranean Rodent: Implications for Rangeland Management in Qinghai-Tibetan Plateau

Disturbances, both human-induced and natural, may re-shape ecosystems by influencing their composition, structure, and functional processes. Plateau zokor (Eospalax baileyi) is a typical subterranean rodent endemic to Qinghai-Tibetan Plateau (QTP), which are considered ecosystem engineers influencing the alpine ecosystem function. It is also regarded as a pest aggravating the degradation of overgrazed grassland and subject to regular control in QTP since 1950s. Climate change has been predicted in this region but little research exists exploring its impact on such subterranean rodent populations. Using plateau zokor as a model, through maximum entropy niche-based modeling (Maxent) and sustainable habitat models, we investigate zokor habitat dynamics driven by the future climate scenarios. Our models project that zokor suitable habitat will increase by 6.25% in 2050 in QTP. The predication indicated more threats in terms of grassland degradation as zokor suitable habitat will increase in 2050. Distribution of zokors will shift much more in their southern range with lower elevation compare to northern range with higher elevation. The estimated distance of shift ranges from 1 km to 94 km from current distribution. Grassland management should take into account such predictions in order to design mitigation measures to prevent further grassland degradation in QTP under climate change scenarios.     

Climatic mean diagrams: A technique for assessing the climatic differentiation of species

 A new method for comparisons of the ecogeographical and climatic constitutions of taxa is presented. The method will be important for understanding the evolution of species in time and space because ecogeographical characters of the species become directly comparable. On a global analytical level, distribution ranges of species may be considered as a function of the ecological constitution of the species, i.e. their endogenous hardiness to environmental forces, and climate. Frequency diagrams of the species' occurrences are calculated for the monthly climatic means of temperature and precipitation using high-resolution maps of distribution and climate. These frequency diagrams are used to construct monthly temperature-precipitation diagrams (TPD) that show the monthly climate spaces of the species'. For the first time, within the TPDs the climate spaces of the plants become directly comparable. However, comparability is somewhat restricted because of the necessity to consider the TPDs of all 12 months. A higher degree of abstraction is obtained using the climatic centre of a species as inferred from the TPD. The twelve monthly climatic means are transferred to the climatic mean diagram (CMD). In the CMD the climate spaces of the species become directly comparable in the course of the year. Despite the high degree of abstraction each diagram type reflects particular ecogeographical characteristics of the species even at a regional geographical level. Especially the CMD offers ways for understanding evolutionary shifts in the ecogeographical constitution of closely related species. The reasons for the shifts are composed of a hydric and thermal component. They may be addressed in molecular and physiological studies concerning evolutionary changes of these ecogeographical traits. Received August 7, 2000 Accepted November 5, 2001     

Evolution of the realized climatic niche in the genus Arabidopsis (Brassicaceae)

The evolution of the realized climatic niche in the genus Arabidopsis was studied using an almost complete phylogenetic tree based on DNA sequences of the ribosomal internal transcribed spacers. The realized climatic niche (climate space) was determined by the intersections of the distribution ranges of the taxa with climate data and is presented in temperature/precipitation diagrams. A positive correlation exists between the climate spaces of the taxa and their range sizes. The diagrams revealed a core climate; that is, a climate space in which all taxa co-exist. This core climate is almost identical to the most parsimonious reconstruction of the genus' ancestral climate space and may be considered an ancestral state of these characters. Mapping the evolutionary changes occurring in the realized climatic space on the phylogenetic tree from the core climate proved to be the most parsimonious procedure. The character complex is homoplastic; that is, many parallel evolutionary events have occurred in the subclades. With the exception of A. thaliana, which is sister to the other species of the genus and occupies a very large climate space, the late-diverged taxa of the other subclades experienced great evolutionary changes whereas the realized climate space of the taxa that diverged earlier resembles the core climate. The latter also show some parallel contractions in the climate space. It is hypothesized that the diversification of Arabidopsis may have started from small to midsized ranges in a temperate climate.     

Impacts from hydropower production on biodiversity in an LCA framework—review and recommendations

Purpose

Expanding renewable energy production is widely accepted as a promising strategy in climate change mitigation. However, even renewable energy production has some environmental impacts, some of which are not (yet) covered in life cycle impact assessment (LCIA). We aim to identify the most important cause-effect pathways related to hydropower production on biodiversity, as one of the most common renewable energy sources, and to provide recommendations for future characterization factor (CF) development.

Methods

We start with a comprehensive review of cause-effect chains related to hydropower production for both aquatic and terrestrial biodiversity. Next, we explore contemporary coverage of impacts on biodiversity from hydropower production in LCA. Further, we select cause-effect pathways displaying some degree of consistency with existing LCA frameworks for method development recommendations. For this, we compare and contrast different hydrologic models and discuss how existing LCIA methodologies might be modified or combined to improve the assessment of biodiversity impacts from hydropower production.

Results and discussion

Hydropower impacts were categorized into three overarching impact pathways: (1) freshwater habitat alteration, (2) water quality degradation, and (3) land use change. Impacts included within these pathways are flow alteration, geomorphological alteration to habitats, changes in water quality, habitat fragmentation, and land use transformation. For the majority of these impacts, no operational methodology exists currently. Furthermore, the seasonal nature of river dynamics requires a level of temporal resolution currently beyond LCIA modeling capabilities. State-of-the-art LCIA methods covering biodiversity impacts exist for land use and impacts from consumptive water use that can potentially be adapted to cases involving hydropower production, while other impact pathways need novel development.

Conclusions

In the short term, coverage of biodiversity impacts from hydropower could be significantly improved by adding a time step representing seasonal ecological water demands to existing LCIA methods. In the long term, LCIA should focus on ecological response curves based on multiple hydrologic indices to capture the spatiotemporal aspects of river flow, by using models based on the “ecological limits to hydrologic alteration” (ELOHA) approach. This approach is based on hydrologic alteration-ecological response curves, including site-specific environmental impact data. Though data-intensive, ELOHA represents the potential to build a global impact assessment framework covering multiple ecological indicators from local impacts. Further, we recommend LCIA methods based on degree of regulation for geomorphologic alteration and a fragmentation index based on dam density for “freshwater habitat alteration,” which our review identified as significant unquantified threats to aquatic biodiversity.

     

Modeling to Predict Cases of Hantavirus Pulmonary Syndrome in Chile

Background

Hantavirus pulmonary syndrome (HPS) is a life threatening disease transmitted by the rodent Oligoryzomys longicaudatus in Chile. Hantavirus outbreaks are typically small and geographically confined. Several studies have estimated risk based on spatial and temporal distribution of cases in relation to climate and environmental variables, but few have considered climatological modeling of HPS incidence for monitoring and forecasting purposes.

Methodology

Monthly counts of confirmed HPS cases were obtained from the Chilean Ministry of Health for 2001–2012. There were an estimated 667 confirmed HPS cases. The data suggested a seasonal trend, which appeared to correlate with changes in climatological variables such as temperature, precipitation, and humidity. We considered several Auto Regressive Integrated Moving Average (ARIMA) time-series models and regression models with ARIMA errors with one or a combination of these climate variables as covariates. We adopted an information-theoretic approach to model ranking and selection. Data from 2001–2009 were used in fitting and data from January 2010 to December 2012 were used for one-step-ahead predictions.

Results

We focused on six models. In a baseline model, future HPS cases were forecasted from previous incidence; the other models included climate variables as covariates. The baseline model had a Corrected Akaike Information Criterion (AICc) of 444.98, and the top ranked model, which included precipitation, had an AICc of 437.62. Although the AICc of the top ranked model only provided a 1.65% improvement to the baseline AICc, the empirical support was 39 times stronger relative to the baseline model.

Conclusions

Instead of choosing a single model, we present a set of candidate models that can be used in modeling and forecasting confirmed HPS cases in Chile. The models can be improved by using data at the regional level and easily extended to other countries with seasonal incidence of HPS.     

Pleistocene climate, phylogeny, and climate envelope models: an integrative approach to better understand species' response to climate change

Mean annual temperature reported by the Intergovernmental Panel on Climate Change increases at least 1.1°C to 6.4°C over the next 90 years. In context, a change in climate of 6°C is approximately the difference between the mean annual temperature of the Last Glacial Maximum (LGM) and our current warm interglacial. Species have been responding to changing climate throughout Earth's history and their previous biological responses can inform our expectations for future climate change. Here we synthesize geological evidence in the form of stable oxygen isotopes, general circulation paleoclimate models, species' evolutionary relatedness, and species' geographic distributions. We use the stable oxygen isotope record to develop a series of temporally high-resolution paleoclimate reconstructions spanning the Middle Pleistocene to Recent, which we use to map ancestral climatic envelope reconstructions for North American rattlesnakes. A simple linear interpolation between current climate and a general circulation paleoclimate model of the LGM using stable oxygen isotope ratios provides good estimates of paleoclimate at other time periods. We use geologically informed rates of change derived from these reconstructions to predict magnitudes and rates of change in species' suitable habitat over the next century. Our approach to modeling the past suitable habitat of species is general and can be adopted by others. We use multiple lines of evidence of past climate (isotopes and climate models), phylogenetic topology (to correct the models for long-term changes in the suitable habitat of a species), and the fossil record, however sparse, to cross check the models. Our models indicate the annual rate of displacement in a clade of rattlesnakes over the next century will be 2 to 3 orders of magnitude greater (430-2,420 m/yr) than it has been on average for the past 320 ky (2.3 m/yr).     

Predicting the impacts of climate change on the distribution of threatened forest‐restricted birds in Madagascar

The greatest common threat to birds in Madagascar has historically been from anthropogenic deforestation. During recent decades, global climate change is now also regarded as a significant threat to biodiversity. This study uses Maximum Entropy species distribution modeling to explore how potential climate change could affect the distribution of 17 threatened forest endemic bird species, using a range of climate variables from the Hadley Center's HadCM3 climate change model, for IPCC scenario B2a, for 2050. We explore the importance of forest cover as a modeling variable and we test the use of pseudo‐presences drawn from extent of occurrence distributions. Inclusion of the forest cover variable improves the models and models derived from real‐presence data with forest layer are better predictors than those from pseudo‐presence data. Using real‐presence data, we analyzed the impacts of climate change on the distribution of nine species. We could not predict the impact of climate change on eight species because of low numbers of occurrences. All nine species were predicted to experience reductions in their total range areas, and their maximum modeled probabilities of occurrence. In general, species range and altitudinal contractions follow the reductive trend of the Maximum presence probability. Only two species (Tyto soumagnei and Newtonia fanovanae) are expected to expand their altitude range. These results indicate that future availability of suitable habitat at different elevations is likely to be critical for species persistence through climate change. Five species (Eutriorchis astur, Neodrepanis hypoxantha, Mesitornis unicolor, Euryceros prevostii, and Oriola bernieri) are probably the most vulnerable to climate change. Four of them (E. astur, M. unicolor, E. prevostii, and O. bernieri) were found vulnerable to the forest fragmentation during previous research. Combination of these two threats in the future could negatively affect these species in a drastic way. Climate change is expected to act differently on each species and it is important to incorporate complex ecological variables into species distribution models.     

Phase Diagrams for DNA Crystallization Systems

Abstract

Phase diagrams for several oligonucleotide duplex -spermine systems have been constructed. These diagrams characterize the duplex and spermine concentrations ranges in which crystalline precipitates are formed. All of them are wedge-like form. The slope of the upper branch of the diagram is determined by the oligonucleotide length. The position of the lower branch depends on both the nucleotide sequence and its length. The position of the lower branch depends on both the nucleotide sequence and its length. It has been shown that the addition to the system ofMgCl₂ and NaCl salts and MPD results in specific changes in the diagrams. A model for oligonucleotide duplex-spermine system has been suggested which explains the main characteristic features of the obtained phase diagrams. The experimental phase diagrams for the (pGpT)_n · (pApC)_n-spermine system (n = 2,3,4) have been analyzed ion terms of this model and the values of the binding constants of spermine and Mg²⁺ions binding to duplexes have been determined. It permitted to identify the complexes that precipitated in different regions of the phase diagrams under various conditions. The diagram obtained in the presence of a cobalt hexammine counterion is also considered. It has been shown that this phase diagram, in general, is similar to those obtained for the oligonucleotide duplex-spermine system.     

区域气候变化统计降尺度研究进展

统计降尺度方法(the Statistical Downscaling Methods, SDM)是为合理预测区域尺度的气候变化情景而提出的新型研究方法。统计降尺度法利用多年大气环流的观测资料建立大尺度气候要素和区域气候要素之间的统计关系,并用独立的观测资料检验这种关系的合理性。把这种关系应用于大气环流模式(Global atmospheric general circulation models, GCMs)中输出大尺度气候信息,来预估区域未来的气候变化情景(如气温和降水)。同时,10a来降尺度方法在生态过程模拟以及气候变化与生态预报关系拟合研究方面也取得一定进展。对统计降尺度方法概念的内涵和外延、基本原理和操作步骤的创新研究方面进行了综述,归纳了该方法在模拟区域气候变化中的应用进展、研究热点及发展趋势,介绍了降尺度在生态预报中的相关应用,为相关研究提供参考。     

Adaptive thermoregulation in endotherms may alter responses to climate change

Climate change is one of the major issues facing natural populations and thus a focus of recent research has been to predict the responses of organisms to these changes. Models are becoming more complex and now commonly include physiological traits of the organisms of interest. However, endothermic species have received less attention than have ectotherms in these mechanistic models. Further, it is not clear whether responses of endotherms to climate change are modified by variation in thermoregulatory characteristics associated with phenotypic plasticity and/or adaptation to past selective pressures. Here, we review the empirical data on thermal adaptation and acclimatization in endotherms and discuss how those factors may be important in models of responses to climate change. We begin with a discussion of why thermoregulation and thermal sensitivity at high body temperatures should be co-adapted. Importantly, we show that there is, in fact, considerable variation in the ability of endotherms to tolerate high body temperatures and/or high environmental temperatures, but a better understanding of this variation will likely be critical for predicting responses to future climatic scenarios. Next, we discuss why variation in thermoregulatory characteristics should be considered when modeling the effects of climate change on heterothermic endotherms. Finally, we review some biophysical and biochemical factors that will limit adaptation and acclimation in endotherms. We consider both long-term, directional climate change and short-term (but increasingly common) anomalies in climate such as extreme heat waves and we suggest areas of important future research relating to both our basic understanding of endothermic thermoregulation and the responses of endotherms to climate change.