Comparing climate change and species invasions as drivers of coldwater fish population extirpations

Species are influenced by multiple environmental stressors acting simultaneously. Our objective was to compare the expected effects of climate change and invasion of non-indigenous rainbow smelt (Osmerus mordax) on cisco (Coregonus artedii) population extirpations at a regional level. We assembled a database of over 13,000 lakes in Wisconsin, USA, summarising fish occurrence, lake morphology, water chemistry, and climate. We used A1, A2, and B1 scenarios from the Intergovernmental Panel on Climate Change (IPCC) of future temperature conditions for 15 general circulation models in 2046-2065 and 2081-2100 totalling 78 projections. Logistic regression indicated that cisco tended to occur in cooler, larger, and deeper lakes. Depending upon the amount of warming, 25-70% of cisco populations are predicted to be extirpated by 2100. In addition, cisco are influenced by the invasion of rainbow smelt, which prey on young cisco. Projecting current estimates of rainbow smelt spread and impact into the future will result in the extirpation of about 1% of cisco populations by 2100 in Wisconsin. Overall, the effect of climate change is expected to overshadow that of species invasion as a driver of coldwater fish population extirpations. Our results highlight the potentially dominant role of climate change as a driver of biotic change.     

Mopane (Colophospermum mopane): A potential winner under climate change in southern Africa

Distribution and abundance under climate change of particularly non-timber forest product tree species is vital since they sustain many livelihoods, especially in rural sub-Saharan Africa. The aim of the study was to determine the current and future natural range of mopane (Colophospermum mopane (J. Kirk ex Benth.) J. Léonard, Fabaceae), a dominant tree species in mopane woodlands of southern Africa. An ensemble model was built in ‘biomod2’ from eight algorithms and used to estimate the current and future distribution. Seven bioclimatic variables and 269 occurrence records were used to calibrate individual models that were later combined into an ensemble model. The ensemble model was projected to two time periods, 2041–2060 and 2081–2100, under two shared socio-economic pathways (SSPs), SSP2-4.5 and SSP5-8.5, and three general circulation models (GCMs). The ensemble model showed high performance (KAPPA = 0.770, ROC = 0.961, TSS = 0.792, ACCURACY = 0.900). A map of the current distribution shows occurrence predominantly in low-lying areas, including the Zambezi, Save and Limpopo valleys, Okavango and Cuvelai basins, and in southern and central Mozambique. Projection maps show expansion under all SSPs, GCMs and time periods. Averaged across GCMs in 2041–2060, the range expanded by 22.37% under SSP2-4.5, and by 19.94% under SSP5-8.5. In 2081–2100, the range expanded by 20.43% under SSP2-4.5, and by 27.62% under SSP5-8.5. Notably, the range expansion was highest under SSP5-8.5, an SSP that envisages unmitigated greenhouse gas release and the largest mean global temperature increase. It is highly likely that mopane is not directly threatened by climate change. Indirect climate change threats, however, remain uncertain.     

气候舒适度在不同海拔的时空变化特征及其影响因素

气候舒适度是在气候变化背景下评估热量变化的方式之一.本研究基于1984-2013年间贵州省84个气象台站的逐日观测数据,采用通用热气候指数(UTCI)讨论不同海拔的气候舒适度时空变化规律及主要影响因子,定量分析了不同海拔地区各气候因子对UTCI的影响差异.结果表明: 1984-2013年间,贵州省多年平均UTCI与气温在空间分布格局上有很强的一致性,均表现为温度随海拔升高而降低,全省大部分地区年舒适天数在180～240 d之间;贵州省各站点UTCI增幅随海拔升高而增大,且UTCI变化幅度[-0.58～1.38 ℃·(10 a)^-1]高于气温变化幅度[-0.36～0.45 ℃·(10 a)^-1];在全省范围内,UTCI与各气候因子的相关关系由大至小依次为气温、风速、气压、相对湿度和云量,相关系数分别为0.899、-0.855、0.818、-0.373和-0.042;在不同海拔地区,不同因子与UTCI的相关系数变化有很大的不一致性.随海拔升高,UTCI受气温影响逐渐减弱,风速的影响程度增大.     

Back to the future: using historical climate variation to project near‐term shifts in habitat suitable for coast redwood

Studies that model the effect of climate change on terrestrial ecosystems often use climate projections from downscaled global climate models (GCMs). These simulations are generally too coarse to capture patterns of fine‐scale climate variation, such as the sharp coastal energy and moisture gradients associated with wind‐driven upwelling of cold water. Coastal upwelling may limit future increases in coastal temperatures, compromising GCMs’ ability to provide realistic scenarios of future climate in these coastal ecosystems. Taking advantage of naturally occurring variability in the high‐resolution historic climatic record, we developed multiple fine‐scale scenarios of California climate that maintain coherent relationships between regional climate and coastal upwelling. We compared these scenarios against coarse resolution GCM projections at a regional scale to evaluate their temporal equivalency. We used these historically based scenarios to estimate potential suitable habitat for coast redwood (Sequoia sempervirens D. Don) under ‘normal’ combinations of temperature and precipitation, and under anomalous combinations representative of potential future climates. We found that a scenario of warmer temperature with historically normal precipitation is equivalent to climate projected by GCMs for California by 2020–2030 and that under these conditions, climatically suitable habitat for coast redwood significantly contracts at the southern end of its current range. Our results suggest that historical climate data provide a high‐resolution alternative to downscaled GCM outputs for near‐term ecological forecasts. This method may be particularly useful in other regions where local climate is strongly influenced by ocean–atmosphere dynamics that are not represented by coarse‐scale GCMs.     

Distinct responses and range shifts of lizard populations across an elevational gradient under climate change

Ongoing climate change has profoundly affected global biodiversity, but its impacts on populations across elevations remain understudied. Using mechanistic niche models incorporating species traits, we predicted ecophysiological responses (activity times, oxygen consumption and evaporative water loss) for lizard populations at high-elevation (<3600 m asl) and extra-high-elevation (≥3600 m asl) under recent (1970–2000) and future (2081–2100) climates. Compared with their high-elevation counterparts, lizards from extra-high-elevation are predicted to experience a greater increase in activity time and oxygen consumption. By integrating these ecophysiological responses into hybrid species distribution models (HSDMs), we were able to make the following predictions under two warming scenarios (SSP1-2.6, SSP5-8.5). By 2081–2100, we predict that lizards at both high- and extra-high-elevation will shift upslope; lizards at extra-high-elevation will gain more and lose less habitat than will their high-elevation congeners. We therefore advocate the conservation of high-elevation species in the context of climate change, especially for those populations living close to their lower elevational range limits. In addition, by comparing the results from HSDMs and traditional species distribution models, we highlight the importance of considering intraspecific variation and local adaptation in physiological traits along elevational gradients when forecasting species' future distributions under climate change.     

Projected Changes in Terrestrial Carbon Storage in Europe under Climate and Land-use Change, 1990–2100

Changes in climate and land use, caused by socio-economic changes, greenhouse gas emissions, agricultural policies and other factors, are known to affect both natural and managed ecosystems, and will likely impact on the European terrestrial carbon balance during the coming decades. This study presents a comprehensive European Union wide (EU15 plus Norway and Switzerland, EU*) assessment of potential future changes in terrestrial carbon storage considering these effects based on four illustrative IPCC-SRES storylines (A1FI, A2, B1, B2). A process-based land vegetation model (LPJ-DGVM), adapted to include a generic representation of managed ecosystems, is forced with changing fields of land-use patterns from 1901 to 2100 to assess the effect of land-use and cover changes on the terrestrial carbon balance of Europe. The uncertainty in the future carbon balance associated with the choice of a climate change scenario is assessed by forcing LPJ-DGVM with output from four different climate models (GCMs: CGCM2, CSIRO2, HadCM3, PCM2) for the same SRES storyline. Decrease in agricultural areas and afforestation leads to simulated carbon sequestration for all land-use change scenarios with an average net uptake of 17–38 Tg C/year between 1990 and 2100, corresponding to 1.9–2.9% of the EU*s CO₂ emissions over the same period. Soil carbon losses resulting from climate warming reduce or even offset carbon sequestration resulting from growth enhancement induced by climate change and increasing atmospheric CO₂ concentrations in the second half of the twenty-first century. Differences in future climate change projections among GCMs are the main cause for uncertainty in the cumulative European terrestrial carbon uptake of 4.4–10.1 Pg C between 1990 and 2100.     

Predicted impact of climate change on European bats in relation to their biogeographic patterns

There has been considerable recent interest concerning the impact of climate change on a wide range of taxa. However, little is known about how the biogeographic affinities of taxa may affect their responses to these impacts. Our main aim was to study how predicted climate change will affect the distribution of 28 European bat species grouped by their biogeographic patterns as determined by a spatial Principal Component Analysis. Using presence‐only modelling techniques and climatic data (minimum temperature, average temperature, precipitation, humidity and daily temperature range) for four different climate change scenarios (IPCC scenarios ranging from the most extreme A1FI, A2, B2 to the least severe, B1), we predict the potential geographic distribution of bat species in Europe grouped according to their biogeographic patterns for the years 2020–2030, 2050–2060 and 2090–2100. Biogeographic patterns exert a great influence on a species' response to climate change. Bat species more associated with colder climates, hence northern latitudes, could be more severely affected with some extinctions predicted by the end of the century. The Mediterranean and Temperate groups seem to be more tolerant of temperature increases, however, their projections varied considerably under different climate change scenarios. Scenario A1FI was clearly the most detrimental for European bat diversity, with several extinctions and declines in occupied area predicted for several species. The B scenarios were less damaging and even predicted that some species could increase their geographical ranges. However, all models only took into account climatic envelopes whereas available habitat and species interactions will also probably play an important role in delimiting future distribution patterns. The models may therefore generate ‘best case’ predictions about future changes in the distribution of European bats.     

Forecasting possible changes in zonal vegetation boundaries in European Russia and Western Siberia in connection with global warming

This paper discusses the relationships of zonal vegetation boundaries with some climatic indicators. Possible changes in subzonal vegetation boundaries in the territory of European Russia and Western Siberia are forecasted within the framework of one of the global warming scenarios. The revealed regularities make it possible to suggest a mathematical cartographic model of vegetation zonality for the 2046–2065 period.     

Downy mildew (Plasmopara viticola) epidemics on grapevine under climate change

As climate is a key agro‐ecosystem driving force, climate change could have a severe impact on agriculture. Many assessments have been carried out to date on the possible effects of climate change (temperature, precipitation and carbon dioxide concentration changes) on plant physiology. At present however, likely effects on plant pathogens have not been investigated deeply. The aim of this work was to simulate future scenarios of downy mildew (Plasmopara viticola) epidemics on grape under climate change, by combining a disease model to output from two general circulation models (GCMs). Model runs corresponding to the SRES‐A2 emissions scenario, characterized by high projections of both population and greenhouse gas emissions from present to 2100, were chosen in order to investigate impacts of worst‐case scenarios, among those currently available from IPCC. Three future decades were simulated (2030, 2050, 2080), using as baseline historical series of meteorological data collected from 1955 to 2001 in Acqui Terme, an important grape‐growing area in the north‐west of Italy. Both GCMs predicted increase of temperature and decrease of precipitation in this region. The simulations obtained by combining the disease model to the two GCM outputs predicted an increase of the disease pressure in each decade: more severe epidemics were a direct consequence of more favourable temperature conditions during the months of May and June. These negative effects of increasing temperatures more than counterbalanced the effects of precipitation reductions, which alone would have diminished disease pressure. Results suggested that, as adaptation response to future climate change, more attention would have to be paid in the management of early downy mildew infections; two more fungicide sprays were necessary under the most negative climate scenario, compared with present management regimes. At the same time, increased knowledge on the effects of climate change on host–pathogen interactions will be necessary to improve current predictions.     

气候变化对祁连山蒙古扁桃潜在适生区的影响

气候变化将改变物种的生存环境,影响其分布范围,甚至威胁到某些物种的生存。本文通过ArcGIS软件和最大熵(MaxEnt)模型模拟蒙古扁桃(Amygdalus mongolica)在祁连山当前(1970—2000年)和未来(2081—2100年)2个气候时期背景下的地理分布格局,并分析其主要的环境影响因素。结果表明：(1)在当前气候条件下,蒙古扁桃在祁连山的东南部有较好的适生性;(2)未来4种气候情景下(SSP126,SSP245,SSP245和SSP585),蒙古扁桃在祁连山南部及东南部的适生区有消失的风险,扩张区主要集中在祁连山中北部的国家公园附近;(3)蒙古扁桃的分布格局主要向祁连山北部和高纬度地区迁移;(4)最湿月降水量(Bio13)、坡度(Slope)、最冷季度均温(Bio11)和最热月最高温(Bio5)的累计贡献率达到了80%以上,是影响蒙古扁桃适生分布的主要因子。本研究模拟、分析、预测了当前和未来不同情景下蒙古扁桃在祁连山的潜在分布及其变化,为祁连山生态及物种多样性的保护提供科学依据。     

Evaluating the effectiveness of conservation site networks under climate change: accounting for uncertainty

We forecasted potential impacts of climate change on the ability of a network of key sites for bird conservation (Important Bird Areas; IBAs) to provide suitable climate for 370 bird species of current conservation concern in two Asian biodiversity hotspots: the Eastern Himalaya and Lower Mekong. Comparable studies have largely not accounted for uncertainty, which may lead to inappropriate conclusions. We quantified the contribution of four sources of variation (choice of general circulation models, emission scenarios and species distribution modelling methods and variation in species distribution data) to uncertainty in forecasts and tested if our projections were robust to these uncertainties. Declines in the availability of suitable climate within the IBA network by 2100 were forecast as ‘extremely likely’ for 45% of species, whereas increases were projected for only 2%. Thus, we predict almost 24 times as many ‘losers’ as ‘winners’. However, for no species was suitable climate ‘extremely likely’ to be completely lost from the network. Considerable turnover (median = 43%, 95% CI = 35–69%) in species compositions of most IBAs were projected by 2100. Climatic conditions in 47% of IBAs were projected as ‘extremely likely’ to become suitable for fewer priority species. However, no IBA was forecast to become suitable for more species. Variation among General Circulation Models and Species Distribution Models contributed most to uncertainty among forecasts. This uncertainty precluded firm conclusions for 53% of species and IBAs because 95% confidence intervals included projections of no change. Considering this uncertainty, however, allows robust recommendations concerning the remaining species and IBAs. Overall, while the IBA network will continue to sustain bird conservation, climate change will modify which species each site will be suitable for. Thus, adaptive management of the network, including modified site conservation strategies and facilitating species' movement among sites, is critical to ensure effective future conservation.     

MigClim: Predicting plant distribution and dispersal in a changing climate

Aim Many studies have forecasted the possible impact of climate change on plant distributions using models based on ecological niche theory, but most of them have ignored dispersal‐limitations, assuming dispersal to be either unlimited or null. Depending on the rate of climatic change, the landscape fragmentation and the dispersal capabilities of individual species, these assumptions are likely to prove inaccurate, leading to under‐ or overestimation of future species distributions and yielding large uncertainty between these two extremes. As a result, the concepts of ‘potentially suitable’ and ‘potentially colonizable’ habitat are expected to differ significantly. To quantify to what extent these two concepts can differ, we developed Mig Clim, a model simulating plant dispersal under climate change and landscape fragmentation scenarios. Mig Clim implements various parameters, such as dispersal distance, increase in reproductive potential over time, landscape fragmentation or long‐distance dispersal. Location Western Swiss Alps. Methods Using our Mig Clim model, several simulations were run for two virtual species by varying dispersal distance and other parameters. Each simulation covered the 100‐year period 2001–2100 and three different IPCC‐based temperature warming scenarios were considered. Results of dispersal‐limited projections were compared with unlimited and no‐dispersal projections. Results Our simulations indicate that: (1) using realistic parameter values, the future potential distributions generated using Mig Clim can differ significantly (up to more than 95% difference in colonized surface) from those that ignore dispersal; (2) this divergence increases under more extreme climate warming scenarios and over longer time periods; and (3) the uncertainty associated with the warming scenario can be as large as the one related to dispersal parameters. Main conclusions Accounting for dispersal, even roughly, can importantly reduce uncertainty in projections of species distribution under climate change scenarios.     

Future hydrological constraints of the Montseny brook newt (Calotriton arnoldi) under changing climate and vegetation cover

The Montseny brook newt (Calotriton arnoldi) is a critically endangered amphibian species which inhabits a small 20 km² holm oak and beech forest area in NE Spain. Calotriton arnoldi strictly lives in running waters and might be highly vulnerable to hydrological perturbations expected to occur under climate and vegetation cover changes. Knowledge about the potential response of the species habitat to environmental changes can help assessing the actions needed for its conservation. Based on knowledge of the species and supported by observations, we proposed daily low and high streamflow event thresholds for the viability of C. arnoldi. We used the rainfall–runoff model PERSiST to simulate changes in the frequency and duration of these events, which were predicted under two climate and four vegetation cover scenarios for near‐future (2031–2050) and far‐future (2081–2100) periods in a reference catchment. All future scenarios projected a significant decrease in annual streamflow (from 21% to as much as 67%) with respect to the reference period. The frequency and length of low streamflow events will dramatically increase. In contrast, the risk of catastrophic drift linked to high streamflow events was predicted to decrease. The potential change in vegetation toward an expansion of holm oak forests will be more important than climate changes in determining threshold low flow conditions. We thus demonstrated that consideration of potential changes in vegetation and not only changes in climate variables is essential in simulating future streamflows. This study shows that future low streamflow conditions will pose a severe threat for the survival of C. arnoldi and may help taking management actions, including limiting the expansion of holm oak forest, for ameliorating the species habitat and help its conservation.     

A process‐based approach to modelling impacts of climate change on the damage niche of an agricultural weed

Predicting the impact of climate change on the damage niche of an agricultural weed at a local scale requires a process‐based modelling approach that integrates local environmental conditions and the differential responses of the crop and weed to change. A simulation model of the growth and population dynamics of winter wheat and a competing weed, Sirius 2010, was calibrated and validated for the most economically damaging weed in UK cereals, Alopecurus myosuroides. The model was run using local‐scale climatic scenarios generated by the LARS‐WG weather generator and based on the HadCM3 projections for the periods 2046–2065 and 2080–2099 to predict the impact of climate change on the population dynamics of the weed and its effect on wheat yields. Owing to rising CO₂ concentration and its effect on radiation use efficiency of wheat, weed‐free wheat yields were predicted to increase. The distribution of the weed was predicted to remain broadly similar with a possible northward shift in range. Local‐scale variation in the impact of climate change was apparent owing to variation in soil type and water holding capacity. The competitive balance was shifted in favour of the deeper rooted crop under climate change, particularly on sites with lighter soils, owing to more frequent and severe drought stress events. Although the damage niche of A. myosuroides was predicted to reduce under climate change, it is likely that weeds with contrasting physiology, such as C4 species, will be better adapted to future conditions and pose a more serious threat.     

The uncertainty of UTCI due to uncertainties in the determination of radiation fluxes derived from numerical weather prediction and regional climate model simulations

In this study we examine the determination accuracy of both the mean radiant temperature (Tmrt) and the Universal Thermal Climate Index (UTCI) within the scope of numerical weather prediction (NWP), and global (GCM) and regional (RCM) climate model simulations. First, Tmrt is determined and the so-called UTCI-Fiala model is then used for the calculation of UTCI. Taking into account the uncertainties of NWP model (among others the HIgh Resolution Limited Area Model HIRLAM) output (temperature, downwelling short-wave and long-wave radiation) stated in the literature, we simulate and discuss the uncertainties of Tmrt and UTCI at three stations in different climatic regions of Europe. The results show that highest negative (positive) differences to reference cases (under assumed clear-sky conditions) of up to ?21°C (9°C) for Tmrt and up to ?6°C (3.5°C) for UTCI occur in summer (winter) due to cloudiness. In a second step, the uncertainties of RCM simulations are analyzed: three RCMs, namely ALADIN (Aire Limitée Adaptation dynamique Développement InterNational), RegCM (REGional Climate Model) and REMO (REgional MOdel) are nested into GCMs and used for the prediction of temperature and radiation fluxes in order to estimate Tmrt and UTCI. The inter-comparison of RCM output for the three selected locations shows that biases between 0.0 and ±17.7°C (between 0.0 and ±13.3°C) for Tmrt (UTCI), and RMSE between ±0.5 and ±17.8°C (between ±0.8 and ±13.4°C) for Tmrt (UTCI) may be expected. In general the study shows that uncertainties of UTCI, due to uncertainties arising from calculations of radiation fluxes (based on NWP models) required for the prediction of Tmrt, are well below ±2°C for clear-sky cases. However, significant higher uncertainties in UTCI of up to ±6°C are found, especially when prediction of cloudiness is wrong.     

Assessing Climate Variability Impact on Thermotolerant Coliform Bacteria in Surface Water

This study investigated the impacts of climate variability on thermotolerant coliform bacteria (TCB) transport in the Upper Pearl River watershed (UPRW) in Mississippi. The Soil and Water Assessment Tool (SWAT) was applied using daily observed stream flows and TCB concentration data. The SWAT model was successfully calibrated and validated using both manual and automatic methods from February 2011 to June 2012 (NSE and R² up to 0.79). The Long Ashton Research Station Weather Generator (LARS-WG), a stochastic weather generator, with the global climate model, CCSM3, which was developed by the U.S. National Center for Atmospheric Research (NCAR) was used for future climate variability simulations. The Special Report on Emissions Scenarios (SRES) A1B of the Intergovernmental Panel on Climate Change (IPCC) was simulated for the mid (2046–2065) and late (2080–2099) 21st century. The SWAT model simulated TCB concentrations in surface water and demonstrated reasonable performances (R² up to 0.59 and NSE up to 0.58). During mid-century climate, average monthly TCB levels increase to 175%, while late-century average monthly TCB levels increase to 297% from the watershed. Although late-century climate variability impacts were determined more critical than mid-century climate impacts, appropriate watershed management practices are required to adapt to maintain and improve water quality.     

Strengthening forecasts of climate change impacts with multi‐model ensemble averaged projections using MAGICC/SCENGEN 5.3

Climate output from general circulation models (GCMs) is being used with increasing frequency to explore potential climate change impacts on species’ distributional range shifts and extinction probability. However, different GCMs do not perform equally well in their ability to hindcast the key climatic factors that potentially influence species distributions. Previous research has demonstrated that multi‐model ensemble forecasts perform better than any single GCM in simulating observed conditions at a global scale. MAGICC/SCENGEN 5.3 is a freeware climate model ‘emulator’ that generates multi‐model ensemble forecasts, conditional on regional and/or global performance, for up to twenty GCMs. In combination with a new application ‘M/SGridder’, this software can be used to produce down‐scaled ensemble forecasts, which minimize climate‐model‐related uncertainty, for a range of ecological problems.     

Migrate or stay: terrestrial primary productivity and climate drive anadromy in Arctic char

A shift in the magnitude and timing of animal migrations is one of the most documented ecological effects of climate change. Although migrations are largely driven by spatial variation in resource gradients, few studies connect expected changes in primary production with geographic patterns in migratory behavior. Here, we link lake primary production to the occurrence of sea migrations in the partially anadromous salmonid Arctic char (Salvelinus alpinus L.). We compiled presence/absence records of anadromous char populations spanning productivity and temperature gradients along the Norwegian coast. The probability of anadromy decreased with increasing migration distance, maximum slope of the migration route and lake productivity. There was a significant interaction between lake productivity and migration distance. The negative effect of longer migration distances was more severe in lakes with higher productivity, indicating reduced relative profitability of migration with increased feeding opportunities in freshwater. Lake productivity was mainly driven by terrestrial primary production in the catchment. We predicted future distributions of anadromous char given downscaled temperature and precipitation changes projected by two different emission scenarios and global climate models (GCMs). Projected increases in temperature and precipitation in 2071–2100 increased terrestrial primary production and, compared to the control scenario (1961–1990), decreased the range of anadromous populations. The prevalence of anadromy decreased by 53% in the HadAm3H GCM with the A2 emission scenario, 61% in HadAm3H with the B2 scenario and 22% in ECHAM4 with the B2 scenario. Cross‐ecosystem studies (e.g., terrestrial to freshwater) are critical for understanding ecological impacts of climate change. In this case, climate‐driven increases in terrestrial primary production are expected to increase primary production in lakes and ultimately reduce the prevalence of anadromy in Arctic char populations.     

Predicting urban outdoor thermal comfort by the Universal Thermal Climate Index UTCI—a case study in Southern Brazil

Recognising that modifications to the physical attributes of urban space are able to promote improved thermal outdoor conditions and thus positively influence the use of open spaces, a survey to define optimal thermal comfort ranges for passers-by in pedestrian streets was conducted in Curitiba, Brazil. We applied general additive models to study the impact of temperature, humidity, and wind, as well as long-wave and short-wave radiant heat fluxes as summarised by the recently developed Universal Thermal Climate Index (UTCI) on the choice of clothing insulation by fitting LOESS smoothers to observations from 944 males and 710 females aged from 13 to 91 years. We further analysed votes of thermal sensation compared to predictions of UTCI. The results showed that females chose less insulating clothing in warm conditions compared to males and that observed values of clothing insulation depended on temperature, but also on season and potentially on solar radiation. The overall pattern of clothing choice was well reflected by UTCI, which also provided for good predictions of thermal sensation votes depending on the meteorological conditions. Analysing subgroups indicated that the goodness-of-fit of the UTCI was independent of gender and age, and with only limited influence of season and body composition as assessed by body mass index. This suggests that UTCI can serve as a suitable planning tool for urban thermal comfort in sub-tropical regions.     

The impacts of climate change on thermal stratification and dissolved oxygen in the temperate,dimictic Mississippi Lake,Ontario

This study investigates and reports the climate change's effects on the Mississippi Lake thermal structure and dissolved oxygen (DO) for baseline (1986–2005) and future (2081–2100) periods. Future meteorological variables were derived from the second-generation Canadian Earth System Model (CanESM2) under three emission scenarios (RCP2.6, RCP4.5, and RCP8.5). The long-term lake inflow was modelled using the Thornthwaite monthly water balance model (TMWB) coupled with an Artificial Neural Network (ANN) to simulate the water level in the lake. Several methods were analyzed to assure the above is the best for estimating the water budget in this region. The water quality of Mississippi Lake was analyzed using a calibrated CE-QUAL-W2 model for the years 2017 and 2018. A major challenge in setting up the model was limitations in some essential water quality indicator inputs, which were estimated using reliable experimental relationships. Our results show that the baseline average surface water temperature of 14.6 °C would increase by 1.31 °C, 1.34 °C, and 2.69 °C under RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. In contrast, the baseline average hypolimnetic DO of 7.1 mg/L would decrease by 1.4%, 6.2%, and 14.3% in RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. Such a rise in water temperature and the consequent diminishment of DO in deep waters would threaten the future sustainable growth of warm-water fish species in Mississippi lake.