The Effect of Climate Warming on Polar Bears (Ursus Maritimus) in the Canadian Arctic

Polar bears depend on sea ice for survival. According to the analysis of passive-microwave satellite imagery beginning in the late 1970s, the sea ice has been breaking up at earlier dates. Stirling and Parkinson (2006) explore five populations of polar bears and predict the effect of climate change on these populations. They hypothesize that the polar bears will become increasingly food-stressed, and their numbers will decrease significantly due to earlier ice break up. Clara Lyashevsky
Stirling, I., Parkinson, C., 2006. Possible effects of climate warming on selected populations of polar bears (Urus martimus) in the Canadian Arctic. Environmental Toxicology and Chemistry 59, 261–275.

In 2005, the Department of Environment of the Government of Nunavut, Canada announced an overall increase in polar bear quotas. The estimates of population size were determined from mark-recapture, survival rates, and reproductive rates. However in Western Hudon Bay, Foxe Basin, Baffin Bay, and Davis Strait, the population increase was based on traditional Inuit knowledge. They had reported seeing more bears in recent years around settlements, hunting camps, and in other locations where they had not been seen before. These observations lead to the conclusion that populations were growing. Although the Inuit population did not document the actual numbers of bears, the dates or locations, or the approximate age and sex of bears, their observations are generally regarded as accurate.
The authors analyzed the patterns of ice breakup in five regions. The boundaries were made using studies of movements of tagged bears of all ages and sexes, the annual movements of adult females wearing satellite radio collars, and genetic studies. Satellites have collected multichannel passive-microwave data on the Arctic sea-ice cover since late 1978. These data show the monitoring of the ice cover to a resolution of about 25 km. The data are collected day and night, in all seasons of the year, and under all weather conditions. The authors used two satellite passive-microwave data sets, one from NASA’s Nimbus 7 SMMR and the other from the DMSP Special Sensor Microwave Imager. They used the SSMI record every day through the end of 2004 and the SMMR every other day from October 1978 to August 1987. The SMMR and SSMI radioactive data were converted to sea-ice concentrations (percent areal coverages of sea ice) through a multichannel algorithm. Ice extents were calculated by summing the areas of all pixels with at least 15% ice concentration. Ice areas were calculated by summing the products of the area and ice concentration of all pixels with at least 15% ice concentration.
The authors calculated ice areas for the five polar bear regions and divided those ice areas by the area of the respective region, which gave them the daily percent ice coverage. For the SMMR years, the authors performed temporal interpolation to provide values for the days without data. This way, they were able to produce a complete daily data set. They determined the data in each year when the ice cover fell below 50% (break up), and then calculated the trend over the course of the 1979–2004 record.
Every fall, the authors measured the body length and axillary girth of 100–300 immobilized polar bears to estimate their weights and overall body condition. They used a Pearson product-moment correlation to test for statistical significance between the number of problem bears handled and the date of break up. They used a linear regression to test for significance between weights of pregnant females in fall and year.
The data showed an overall trend toward progressively earlier sea-ice breakup. On average, breakup occurred about 7–8 days earlier per decade. In Western Hudson Bay, all bears must fast for at least four months during the ice-free season whereas the pregnant females must fast for eight months because they give birth to cubs in dens at about the time the rest of the population can return to the ice. As a result of the earlier breakup, the polar bears are forced to come ashore earlier to begin fasting and for a longer period of time.
            Although the number of polar bears seen by people has increased, the results of their study show that this is not indicative of an increase in population, but in fact a decrease. The decline is due to earlier breakup of the sea ice, due to climate warming.

The Effect of Climate Change at Different Tem-poral Scales on Vaccinium Myrtillus

The Arctic’s plant growth, soil temperatures, and season length are dependent on snow cover. Snow characteristics and snowmelt timing will change with a warmer climate. In warmer winters, a lot of the precipitation falls as rain resulting in earlier spring. Rixen et al. (2010) observed year rings and shoot growth of the dwarf shrub bilberry (Vaccinium myrtillus) in response to early or late snowmelt in the Central Alps. With a temperature rise of 1.3 oC in the 20th century, changes in ecosystem structure and function that are attributed to snow cover have already become apparent in tundra ecosystems. The authors measured radial and shoot growth increments of the bilberry and the species abundances of the vegetation in response to different types of snow cover. The comparison of ramet age and ring widths from different sites allows for a comparison of growing conditions under different snow regimes over as much as two decades. Clara Lyashevsky
 Rixen, C., Schwoerer, C., Wipf, S., 2010. Winter climate change at different temporal scales in Vaccinium myrtillus, an Arctic and alpine dwarf shrub. Ecological Monographs 29, 85–94.

The experiments were done at the Central Alps in Switzerland, where the mean temperature in winter is 2.0 oC, the snow cover lasts on average from 18 October to 26 May, and the main vegitation type is dwarf shrub heath (Empetro-Vaccinietum cetrarietosum).
Plots of vegetation were established in four different subsets varying in timescale of the snow manipulations, in order to assess the impact of the snowmelt date on the vegetation. The first subset consisted of plots on an ongoing snow manipulation experiment, the second had plots that were chosen along snow fences that were built 30 years ago, the third subset had plots that were established along a natural snow gradient, and the fourth subset had plots at two different altitudes in order to identify the effect of snowmelt date on the growth performance of vegetation at different elevations. The data were collected between June and October.
Advanced snowmelt was simulated in nine plots by removing most of the snow in Spring, nine other plots were used as controls. The vegetation along the natural snowmelt gradient was analyzed by plots established at nine sites in close vicinity to the experimental plots; eighteen additional plots were established at two different elevations. The authors analyzed xylem ring width, shoot length, and species abundance of the vegitation. The differences in age distribution between plots were tested with chi-square tests to see whether treatments affected the age structure of ramet populations. The xylem ring widths were analyzed separately for each year. The relationships of xylem ring width with climate variables were tested with single and multiple linear regression techniques. Subtracting the mean xylem ring widths of late melting plots from the mean xylem ring widths of the early melting plots identified the effect of temperature on the plots.
In very warm summers, plants at high elevation produced larger rings than plants at lower elevation, indicating more favorable conditions. Year rings were generally wider at sites with late snowmelt at the natural snow gradient. Comparing snow fences and natural snow gradients that did not differ in altitude, colder summers had small year ring width whereas warmer summers year ring growth was enhanced by early snowmelt. The shoot length in 2006 was greater after early snowmelt in all plot types. Shoot length was greater after early snowmelt in the natural snow gradient, along the snow fences, and in the snow manipulation experiment.

Analysis of xylem ring width is a valuable tool in investigating growth across elevation and snow gradients. Xylem ring width was greater in plots with late snowmelt than in plots with early snowmelt along the natural snowmelt gradient, which is true in years with relatively cold summers. Climate change can be detrimental to the age of vegetation because of the potential for colder summers. In years with colder summers, growth rings were larger at lower elevation than at higher elevation. Climate change also caused species abundance to change because of higher temperatures

Anticipating, Preventing, and Mitigating Climate Change Impacts on Host-Parasite Interactions by using the Arctic as a Model

Increase in global temperature has strongly affected the Arctic. It has shrunk the sea ice extent, decreased the size of mountain glaciers and amount of snowmelt, as well as reduced the maximum areal extent of seasonally frozen ground. This temperature change will also have profound effects on pathogens. Climate is an important factor in determining the diversity and abundance of pathogens as well as the patterns of disease they cause. The prediction for pathogens in a warmer climate is for increased transmission rates, longer periods for transmission, and shifts in spatial and temporal patterns of pathogen diversity and associated disease. Kut et al. (2009) use the findings and developments of previous case studies to promote wildlife conservation, ecosystem health, and human health. To do so they identify and address knowledge gaps, develop conceptual and predictive tools, establish efficient monitoring and early detection programs, and focus on evidence-based approaches to prevention and mitigation. Clara Lyashevsky
Kutz, S., Jenkins, E., Veitch, A., Ducrocq, J., Polley, L., Elkin, B., Liar, S., 2009. The Arctic as a model for anticipating, preventing, and mitigating climate change impacts on host—parasite interactions. Vet. Parasitology 163, 217–228.

The Arctic is a relatively simple system for examining the effects of climate change on infectious disease in wildlife. Climate change is occurring at an unprecedented rate in the North and observable physical and biological responses are happening in real time. The Arctic also has low biological diversity and, consequently, is vulnerable to invasions and as a result, it will respond rapidly and measurably to environmental disturbances.
Parasites and other pathogens are known to influence wildlife at the individual and population levels. Hunters in the Canadian Arctic and Subarctic informed researchers of the unusual numbersof sick caribou with poor coats and ulcerated limbs, which catalyzed research on Umingmakstrongylus pallikuukensis, a protostrongylid lungworm of muskoxen. The adult nematodes of this lungworm reside in cysts in the lungs of muskoxen and deposit their eggs into them. The eggs then hatch to first stage larvae, move up the airways, they are then swallowed and passed through the gastrointestinal tract, and deposited in feces. The larvae then invade gastropod intermediate hosts (IHs) and develop into the infective third stage.
Empirical field and laboratory data were used to construct predictive models for the development rates of larvae of U. pallikuukensis in IHs. The models are based on degree day calculations and incorporate soil surface temperatures as well as the behavior of the gastropod intermediate hosts. An upper threshold of 21 oC is incorporated into the model; it is assumed that the parasite is maintained at that temperature. U. pallikuukenis take 2 years to develop into the infective third stage, meaning that the developing larvae and the IHs would have to survive winter in order to complete the parasite’s lifecycle. The model suggests that the increase in temperatures hastens larval development, and the infective stage is reached within a single summer. Increases in temperature and a longer summer transmission window could potentially result in the increase of infective larvae available to the muskoxen. As a result, climate change is expected to lead to a net increase in infective larvae, increase infection, and to expand the area in which temperatures are sufficient for larval development.
It was also found that the winter tick, Dermacentor albipictus, is expanding its geographic range in the Canadian North. Winter ticks are host ticks that moult from larvae to adults on a single infected host throughout the winter. Adult ticks mate on the host and lay eggs in the spring. The eggs hatch during the summer and then larval ticks look for a new host that autumn. Therefore the climates of spring, summer, and autumn are critical for the development of the tick. Any change in climate alters their maturation.
There are no baseline data on parasite diversity, life cycles, and effects, which makes understanding the effect of climate difficult. Molecular tools can be applied to fecal stages for noninvasive sampling and accurate identifications to simplify these investigations. How the parasite affects the host helps evaluate the importance of potential changes in a specific host-parasite interaction. In order to better understand host-parasite interactions, researchers use cross-sectional studies. Experimental infections can be critical in defining the susceptibility of host species at risk of infection with a ‘new’ parasite.
The authors concluded that the effects of climate change are not uniform across host or parasite. Increase in temperature will facilitate invasion of new parasites. For example, parasites that previously could not develop in northern ecosystems may soon be able to with climate warming. Also, the invasion of new hosts may alter ecosystems by introduction of new parasites as well as by changing the abundance and distribution of endemic parasite species.

The Effect of Climate Change on an Arctic Marine Food Web

Climate change in the Arctic affects the distribution of organic contaminants and their bioaccumulation (the net result of contaminant uptake and purging by an organism). Borga et al. (2009) investigate the effect of increased temperature and primary production on bioaccumulation of organic contaminants at various trophic levels. The authors base their investigation on the idea that temperature can alter partitioning of organic compounds, which can affect the bioavailability of contaminants for direct uptake by aquatic organisms. Similarly, climate change can also affect the transport of contaminants in Polar Regions, as well as an increase in new species due to overall temperature gain. Clara Lyashevsky
Borga, K., Saloranta, T., and Ruus, A., 2010. Simulating climate changeinduced alterations in bioaccumulation of organic contaminants in an arctic marine food web. Environmental Toxicology and Chemistry 29, 1349–1357.

The study focused on the marine food web of the Arctic. This includes primary producers (phytoplankton), secondary producers (calanoid copepods and krill), predators (pelagic amphipods), and piscivorous seabirds (kittiwake, Rissa tridactyla). The model used in the study was based in spring because it is the most productive period of the year. The authors predicted the magnitude and direction of change in bioaccumulation of organic contaminants for three substances (HCH, PCB-52, PCB-153). These three substances were chosen due to their differences in molecular structure, solid-water partitioning properties, and persistence in fish and birds. The experiment was carried out at different trophic levels in an Arctic shelf sea food web (Barents Sea), in two different future climate change scenarios with increased temperature and amount of particulate organic carbon (POC).
The bioaccumulation model was used to estimate six different contaminant rate constants governing the intake and elimination of POPs in an organism; uptake (kI) and elimination (kO) to water or air via respiratory surfaces, dietary uptake (kD), and elimination due to excretion (kE), biotransformation (kM), and growth dilution (kG).
The simulation model was used to measure bioaccumulation and contaminant concentration changes in a projected future climate for each food web organism. The ratio of contaminant concentrations in a future climate scenario (cb_scen) and in the present state (cb_ctrl; control simulation) was introduced in order to create the model. The rate constants are linear, resulting in the total water concentration (cwat_tot) to be set to 1pg/L.
The control scenario measured HCH, PCB-52, and PCB-153 concentrations in the Barents Sea food web in May 1999. The model performance was based on the standardization of both simulated control scenario results and the measured data against the herbivorous copepod. This process permitted the bioaccumulation processes of the animals in the food web to be addressed independently from the total water and air concentrations. The standardized concentrations are referred to as biomagnification factors (BMFs).
Based on the projected increase in temperature in the Arctic, the authors defined two scenarios where temperature in water (Twater) and air (Tair) is increased by 2.0 oC in scenario 1, and by 4.0oC in scenario 2. The temperature in the control simulation (present state) is assumed to be at the point at which ice melts (0 oC) for both Twater and Tair. The body temperatures of all the food web organisms are assumed to be the same as Twater, except seabirds, which are assumed to have a constant body temperature of 40 oC. Temperature change directly affects the partitioning coefficients, which in turn affect the bioavailable POP concentrations in water and air. The temperature change in invertebrates and fish is anticipated to affect the feeding (GD) and ventilation (GV) rates as well as biotransformation and growth (kG) rate constants. The doubling of primary production in the Arctic shelf, due to the reduced sea ice cover and enhanced upwelling of nutrient-rich water, changed the water POC.
The control model agreed with the observed data. The PCB-52 showed a higher degree of biomagnification than the HCH in both modeled and measured values. The PCB-153 had higher modeled and measured BMF values than the PCB-52. In the seabird, the modeled BMF of HCH and PCB-52 were higher than measured. This suggests that the actual biotransformation rate for these compounds in kittiwake is faster than the conservative half-life values. The opposite was found for PCB-153, implying that biotransformation may be slower than assumed.
The factors of change (F) based on wet weight concentrations were below 1, implying that bioaccumulation decreased compared to the control scenario. The decline in bioaccumulation was seen in lipid weight based concentrations for the PCBS, while there was no change in bioaccumulation for that of HCH. CPOC had a much higher influence on the simulated future bioaccumulation of the PCBs, compared to HCH. The compounds would have more similar future bioaccumulation scenarios if CPOC stopped increasing.

The increase in temperature and POC would reduce the bioaccumulation of PCBs in the Arctic food web, due to reduced bioavailable fraction of PCBs. The PCBs showed the largest reduction in bioaccumulation based on the climate change simulations. The HCH, however, showed less or close to no reduction in bioaccumulation as well as less variability due to season and trophic levels.

Carbon Cycle-Climate Model Predictions of Ocean Acidification in the Arctic

Acidity of oceans will increase with the increase of CO2 emission with the largest simulated pH changes occurring in Arctic surface waters. Decrease in Arctic surface mean saturation and pH is due to freshening and increased carbon uptake in response to depleting sea ice cover. Steinacher et al. (2009) used the Climate System Model to investigate the consequences of rising atmospheric CO2 and climate change on ocean chemistry and the ocean’s acid-base state. They focused on the Arctic where large changes in calcium carbonate saturation, freshwater balance, and sea ice are expected under rising CO2. They also analyzed how the ocean volume fraction of different saturation regimes changes with increasing CO2 and quantified seasonal and interannual variability worldwide.–Clara Lyashevsky
Steinacher, M., Joos, F., Frölicher, T., Plattner, G., Doney, S., 2009. Imminent ocean acidification in the Arctic projected with the NCAR global coupled carbon cycle-climate model. Biogeosicences 6, 515–533.

Ocean acidification has been found to have adverse consequences for many marine organisms because of a decrease in calcium carbonate saturation, calcification rates, and disturbance to acid-base physiology. The most vulnerable are organisms that build shells or other structures of calcium carbonate in the relatively soluble mineral form of aragonite. Some examples include pteropods, corals, and sea urchins. Although responses to acidification vary across species and life stages, some responses include, reduction in foraminifera shell mass, shell dissolution for pteropods, reduced calcification rates, reduced growth rates, reduced metabolism, and increased mortality in mollusks.
The ocean takes up about one fourth of the anthropogenic CO2 emitted into the atmosphere; the hydrolysis of CO2 lowers ocean pH decreasing the saturation levels of calcium carbonate, and undersaturated seawater is corrosive to calcium carbonate in the absence of protective mechanisms. The biogenic production and dissolution of calcium carbonate are mainly controlled by the ambient saturation state, rather than by pH, as observed in corals, coralline, algae, coccolithophorids, foraminifera, echinoderms, mesocosm coral reef communities, and natural coral reef ecosystems. Observations and model results show that surface waters in the Arctic will become undersaturated within decades. The authors use the NCAR CSM1.4-carbon model to investigate the evolution of aragonite saturation over the 21st century. They analyze the changes in the Arctic by quantifying underlying mechanisms, assessing the global evolution of the ocean volume for different saturation regimes, and analyzing spatio-temporal variability in saturation.
The climate-carbon cycle model NCAR CSM1.4-carbon consists of ocean, atmosphere, land, and sea ice physical components integrated via a flux coupler without flux adjustments. The model is known to simulate too much ice in the Northern Hemisphere. The simulated preindusrial ice covered area in the Arctic Ocean is about 10% higher in the summer and 5% higher in the winter than what is actually the case. The model incorporated CO2 emissions from fossil fuel and land use change, along with anthropogenic sulfur emissions. Non-CO2 greenhouse gases were translated to CO2—equivilant concentration.
Carbonate chemistry, pH, carbonate ion concentration, and the saturation state were calculated from modeled or observation-based quantities using the standard OCMIP carbonate chemistry routines. The observation-based carbonate variables were computed from monthly, seasonal, or annual means.
The model values and spatial patterns for the saturation of aragonite and carbonate were compared with the data-based estimates in all major ocean basins. The correlation coefficient for saturation of aragonite was between 0.90 and 0.95 for the Atlantic, Pacific, and Global Ocean. The correlation coefficients for carbonate were smaller (0.86 to 0.91). The results show that the nutrient and carbon rich water of the North Pacific is understaturated, while the relatively nutrient and carbon poor water of the North Atlantic is oversaturated. Observations in the Arctic Ocean suggest an oversaturation of around 5% in the top five hundred meters, around 25% at 1000 m depth, and undersaturation below 2000 m.
Projected global mean changes include anthropogenic carbon emission, atmospheric CO2, ocean surface DIC content, and surface temperature increase. Mean aragonite saturation of surface water and pH decrease. Saturation of aragonite of surface waters will continue to decrease rapidly in all regions and high latitude waters will become unsaturated. Arctic surface waters will become undersaturated with respect to aragonite within a few decades.
Saturation will decrease in the thermocline and the deep ocean as anthropogenic carbon continues to invade the ocean. The modeled carbonate concentrations will decrease rapidly over this century causing a separation between over- and undersaturated waters. Overall the volume occupied by water oversaturated with respect to aragonite decreases from 42% to 25% of the total ocean volume. Unsaturation occurs in small regions first and over short periods of the year. Its spatial and seasonal occurrence increases with rising atmospheric CO2.
Increase in melting of ice, precipitation, and reduced evaporation decreases ocean water pH. Reduced sea ice cover allows gas exchange to occur in a larger area and the availability of light is increased in the ocean surface layer. 

The effect of climate change on the size of an Arctic spider

The Arctic environment is changing rapidly and the effects of climate on phenotypic variation are largely unknown, particularly in ectotherms. Hoye et al. (2009) present data on 10 successive cohorts of the wolf spider, Paradosa glacialis, located in Zackenberg in the Arctic. They found inter-annual variation in adult body size (carapace width). The variation was greater in females than in males, and was increased by increase in temperature and the resulting earlier snowmelt. These spiders take two years to mature and the increased temperatures resulted in larger adult body sizes and a skew towards positive sexual size dimorphism with females bigger than males. Thus, the authors conclude that it is important that male and female responses to climate change should be investigated separately. Clara Lyashevsky
Hoye, T., Hammel, J., Fuchs, T., Toft, S., 2009. Climate change and sexual size dimorphism in an Arctic spide. Biol. Lett. 5, 542–544.

The spiders were monitored for 10 years in Zackenberg at six pitfall trap plots that were collected weekly during the summer months. Spiders were trapped at the beginning of June when the snow at each trap had melted. The authors measured the width of the carapace of 5000 specimens; 500 from each year.
The statistical model was a linear graph that tested the effect of time on variation in carapace width among all adult individuals. The timing of snowmelt was separated into current and previous year. The sex of the spider and the year captured were fixed factors. The authors averaged the carapace width of males, females, and large juveniles, with a carapace width greater than 1.7 mm. They also averaged the timing of snowmelt for the pitfall trap plots to find an overall timing of snowmelt.
The annual average carapace width of juveniles and adults increased with early snowmelt. Sexual size dimorphism was not significantly different between plots but females were found to be bigger than males. Sexual size dimorphism is significantly related to the current amount of snow.
The annual average body size of males, females and large juveniles fluctuated together. The size of the adult spiders was dependent on the snowmelt of the year of maturation as well as on the previous year. The size of the juvenile spiders was only dependent on the snowmelt in the year they were trapped. Size difference was probably caused by higher growth ratios (size after moult versus size before moult) in years of early snowmelt. The authors conclude that the timing of snowmelt also explains the variation in sexual size dimorphism among cohorts of males and females. Size is a more important predictor of reproductive success in females than in males, probably because larger females produce more or larger eggs. A major determinant of reproductive success in males is in the timing of their final moult. Early moulting males can mate with more females than late moulting males. Continual temperature increwas is likely to increase sexual size dimorphism. 

The effect of climate change on predator prey dynamics and Arctic ecosystems.

A species’ response to climate change is due to the direct effect of climate change as well as the indirect effect of other factors such as predator-prey interactions. Gilg et al. (2009) chose to observe the terrestrial vertebrate predator-prey community of the high Arctic to see if it exemplifies these effects. This community is made of one prey (the collard lemming) and four predators (the snowy owl, the Arctic fox, the long tailed skua, and the stoat). The authors found that climate change will indirectly reduce the predator’s reproductive success and population densities, and may ultimately lead to local extinction of some of the predator species. — Clara Lyashevsky
Gilg, O., Sittler, B., and Hanski, I., 2009. Climate change and cyclic predator—prey population dynamics in the high Arctic. Global Change Biology 15, 2634–2652.

The average temperature in the Arctic is expected to increase by 47oC in the next 100 years. This increase in temperature will strongly influence the snow regime, duration of snow cover, snow depth, and snow quality. Because snow is a key environmental factor in high Arctic ecosystems these changes will influence the terrestrial Arctic populations and communities. Previous studies have predicted changes in phylogenies, geographical ranges, and population sizes due to climate change. The authors interpret the results of a study that assesses the impact of climate change on high Arctic terrestrial vertebrate community and they found that climate change affects changes in snow depth and duration as well as increased ice crusting in winter and spring. These instances impact the dynamics of terrestrial Arctic vertebrates.
Using data collected since 1988 in the Karupelv valley in eastern Greenland, the authors constructed a model to run likely scenarios of how climate change would influence the phenology and demography of the species involved, in particular the dynamics of the lemming-predator community under altered environmental conditions.
In northeast Greenland, the collard lemming reproduces mostly in winter and exhibits regular cyclic dynamics. During this time, only the stoat remains a significant predator of the lemming. In the summers, when the lemmings are abundant, the Arctic fox, the long-tailed skua, and the snowy owl are all common and feed on lemming. Although the different predators prey on the same animal, they differ in their functional and numerical responses. For example, Arctic foxes and long-tailed skuas maintain a stable density of adults, fox litters can be large while skuas only lay a maximum of two eggs a year.
The Karupelv valley is a large Tundra area. The Zackenberg valley is a smaller one and was established as an ecological research and monitoring site in 1995 using the same methods as at Karupelv. In order to create a logical model, the authors took into account the fact that the lemming winter nests were counted within a small area at Zackenberg where the habitat is more favorable for the lemming than in the entire Zackenberg study area used for monitoring the predator populations. The authors adjusted this by making the reasonable assumption that the numerical response of young skaus to lemming density is the same at both sites. As a consequence, they used a maximum likelihood function to force the Zackenberg response to fit the response previously published for Karupelv.
The model created by the authors is defined by two differential equations for the lemming and the stoat and by nondynamic equations that give the numerical responses of the remaining predators. They used N to denote the size of the lemming populations, P the size of the stoat population, and Pi and Piyoung the numbers of adult and young individuals in the remaining predators (i = 1–3, for snowy owl, long-tailed skua, and Arctic fox). All of the predators have type III functional responses, with W being the maximum predation rate (in lemmings per year) and D the slope of the functional response.
Snow conditions affect the ecology of the collard lemmings in the high Arctic because they reproduce primarily in the winter and spend most of the year under the cover of snow. Any change in snow conditions in the spring will influence the lemming dynamics directly. There are three main changes that are expected to occur in the snow regime in eastern Greenland. First, as warming climate increases, the length of the snow-free period will increase. Second, increase in temperature and precipitation effects snow quality. Third, warmer climates will increase the average snow depth, which could lead to more solid winter precipitation. The authors suggest that this is the first sign of a severe impact of climate change on the lemming-predator communities in northeast Greenland.
The authors came up with four plausible scenarios of how climate change may influence the dynamics of the lemming-predator community. The first scenario (A) is the control for the rest. The second scenario (B) predicts what would happen if there was an increase in availability of alternative food sources for the stoat and the fox. The third scenario (C) changes the numerical responses of the two mammalian predators, reducing the maximum rate of mortality of the stoat and increasing the minimum density of adult foxes. The fourth scenario (D) changed both the functional and numerical responses of the stoat and leaves the responses of the Arctic fox unchanged.
Scenario A, increasing the length of the snow-free period, greatly increases cycle length and reduces the amplitude and peak density. Scenario B leads to very contrasting results depending on which predator species is affected. Changing the functional response of the Arctic fox has practically no impact on lemming dynamics while increasing the half-saturation constant of the stoat reduces lemming peak density and amplitude. However, cycle length is not affected. Scenario C, increasing fox density, does not significantly change the lemming dynamics; it increases the cycle length slightly. Improving stoat survival slightly increases the amplitude and cycle length and reduces peak densities. Scenario D resulted in all the major expected changes: increase in the length of the snow-free period with related changes in the phonologies of the four predators, increase in stochastic lemming mortality in the spring due to altered snow quality, and improved functional and numerical responses of the stoat due to additional food sources. In conclusion, the authors predict that climate change can lead to smaller cycles and peak densities of lemmings.
From the data calculated by the authors’ model, the effect of climate change is much greater for Zackenberg than for Karupelv. The lemmings in Karupelv valley seem to decrease in density as a result of climate change but the effect is greater on those in Zackenberg valley. There is a large contrast between the two study sites, Zackenberg and Karupelv, suggesting that some seemingly minor environmental differences may lead to substantially different population dynamic consequences. 
Reduced maximum density of lemmings is detrimental to the populations of the predators. From the experimental data, the authors conclude that climate change will indirectly induce a decline in the predators’ reproductive success and population densities and may ultimately lead to local extinctions of some predator species. 

Climate change and the role of temperature in polar oceans

Heterotrophic bacteria are crucial components of marine food webs and have key roles in controlling carbon fluxes in the oceans. Kichman et al. (2009) illuminate the role of temperature in polar waters by comparing microbial growth in polar waters and low-latitude oceans. The results could predict the response of the Arctic Ocean and Antarctic coastal waters as ice coverage depletes and the waters warm. – Clara Lyashevsky
Kirchman, David L., Xose G. Moran, and Hugh Ducklow, 2009. Microbial Growth in the Polar Oceans — Role of Temperature and Potential Impact of Climate Change. Nat Rev Micro 7.6, 451-59.

Heterotrophic bacteria are a part of the microbial loop. The microbial loop consists of the production of dissolved organic material (DOM), uptake of DOM, and consumption of bacteria. As a result, the microbial loop determines the response of oceanic ecosystems and the carbon cycle to climate change, hence the importance of heterotrophic bacteria.
The authors compared the western Arctic Ocean and the Ross Sea with four lower-latitude oceans and they found that the abiotic properties in all six oceans are distinct. However, primary production in the western Arctic Ocean and Ross Sea was significantly lower than in the low-latitude oceans. Bacterial production in the polar waters was also significantly lower than that in low-latitude waters, but the highest production in the polar oceans overlaps the lowest production of the low-latitude waters. These results provide evidence that factors other than temperature alone may control bacterial growth.
In order to find how much of the primary production is due to the microbial loop, the authors measured the ratio of bacterial production to primary production. The reason they focus on this ratio is because it reveals more about the structure of marine food webs and carbon cycling than the bacterial production alone. A large ratio would indicate that a large amount of primary production is due to the microbial loop. The results showed that the ratio increases with temperature below 4oC; the bacteria become more active.
The authors found the activation energies of bacteria in each body of water in order to compare the minimum energy that the bacteria had to produce in order to work in the microbial group. The activation energy for a temperature below 4oC was found to be much larger than the values estimated by controlled experiments in Arctic and Antarctic waters, suggesting that the growth rates vary less with temperature than was actually observed. Therefore, the authors explored a factor that co-varies with temperature and could cause this discrepancy: labile DOM. However, because there is no integrating measurement of DOM supply, the authors were forced to use the rate of primary production as a proxy. Bacterial growth and primary production are highly correlated in all six marine systems, which is consistent with the idea that DOM supply is important.
These comparisons were done in order to compare the amount of bacterial growth in the polar oceans versus that in the low-latitude water. First the authors found the correlation between temperature increase and bacterial production. Then they compared bacterial production and primary production and found that bacterial production is dependent on both temperature and primary production, but mostly on primary production or DOM supply. Then they found that bacterial production is also dependent on biomass levels. The bacterial biomass is significantly lower in the Ross Sea and western Arctic Ocean than the other oceanic regions, due to the lower production rates.
Based on the comparison of primary production and bacterial production against temperature, the warming of Arctic surface waters could lead to more carbon production. However, based on the experimental work, the direct effect of temperature is minimal. Climate change affects many aspects of the ocean besides temperature. It can impact polar marine food webs, microbial community structure, and cell size, which would affect production rates and the relationship between primary production and heterotrophic microorganisms. The authors conclude that there is a fundamental difference between the two polar systems and the rest of the oceanic regions based on bacterial growth and microbial loop activity. These two factors are due to the cold temperatures in the polar waters and the low DOM inputs, but mostly the latter. Consequently, microbial processes in polar systems are sensitive to small changes in their environment, which means that dramatic climate changes will result in large impacts on carbon flows and other ecosystem functions.