scholarly journals Potential Influence of Climate Change on the Acid-Sensitivity of High-Elevation Lakes in the Georgia Basin, British Columbia

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Donna Strang ◽  
Julian Aherne

Global climate models predict increased temperature and precipitation in the Georgia Basin, British Colmbia; however, little is known about the impacts on high-elevation regions. In the current study, fifty-four high-elevation lakes (754–2005 m a.s.l.) were studied to investigate the potential influence of climate change on surface water acid-sensitivity. Redundancy analysis indicated that the concentration of nitrate, dissolved organic carbon, and associated metals was significantly influenced by climate parameters. Furthermore, these components differed significantly between biogeoclimatic zones. Modelled soil base cation weathering for a subset of the study lakes(n=11)was predicted to increase by 9% per 1°C increase in temperature. Changes in temperature and precipitation may potentially decrease the pH of surface waters owing to changes in anthropogenic deposition and organic acid production. In contrast, increased soil base cation weathering may increase the critical load (of acidity) of high-elevation lakes. Ultimately, the determining factor will be whether enhanced base cation weathering is sufficient to buffer changes in natural and anthropogenic acidity. Mountain and high-elevation regions are considered early warning systems to climate change; as such, future monitoring is imperative to assess the potential ramifications of climate change on the hydrochemistry and acid-sensitivity of these surface waters.

2021 ◽  
Vol 26 (2) ◽  
pp. 99-109
Author(s):  
Binod Dawadi ◽  
Shankar Sharma ◽  
Kalpana Hamal ◽  
Nitesh Khadka ◽  
Yam Prasad Dhital ◽  
...  

Climate change studies of the high mountain areas of the central Himalayan region are mostly represented by the meteorological stations of the lower elevation. Therefore, to validate the climatic linkages, daily observational climate data from five automated weather stations (AWS) at elevations ranging from 2660 m to 5600 m on the southern slope of Mt. Everest were examined. Despite variations in the means and distribution of daily, 5-day, 10-day, and monthly temperature and precipitation between stations located at a higher elevation and their corresponding lower elevation, temperature records in the different elevations are highly correlated. In contrast, the precipitation data shows a comparatively weaker correlation. The slopes of the regression model (0.82–1.13) with (R2>0.74) for higher altitude (5050 m and 5600 m) throughout the year, 0.83–1.12 (R2>0.68) except late monsoon season for the station at 4260 m and 5050 m asl indicated the similar variability of the temperature between those stations. Similarly, Namche (3570 m) temperature changes by 0.81–1.32°C per degree change in corresponding lower elevation Lukla station (2660 m), except for monsoon season. However, inconsistent variation was observed between the station with a large altitudinal difference (2940 m) at Lukla and Kala Patthar (5600 m). In general, climate records from corresponding lower elevation can be used to quantitatively assess climatic information of the high elevation areas on the southern slope of Mt. Everest. However, corrections are necessary when absolute values of climatic factors are considered, especially in snow cover and snow-free areas. This study will be beneficial for understanding the high-altitude climate change and impact studies.


2021 ◽  
Vol 118 (2) ◽  
pp. e2002543117 ◽  
Author(s):  
Christopher A. Halsch ◽  
Arthur M. Shapiro ◽  
James A. Fordyce ◽  
Chris C. Nice ◽  
James H. Thorne ◽  
...  

Insects have diversified through more than 450 million y of Earth’s changeable climate, yet rapidly shifting patterns of temperature and precipitation now pose novel challenges as they combine with decades of other anthropogenic stressors including the conversion and degradation of land. Here, we consider how insects are responding to recent climate change while summarizing the literature on long-term monitoring of insect populations in the context of climatic fluctuations. Results to date suggest that climate change impacts on insects have the potential to be considerable, even when compared with changes in land use. The importance of climate is illustrated with a case study from the butterflies of Northern California, where we find that population declines have been severe in high-elevation areas removed from the most immediate effects of habitat loss. These results shed light on the complexity of montane-adapted insects responding to changing abiotic conditions. We also consider methodological issues that would improve syntheses of results across long-term insect datasets and highlight directions for future empirical work.


2020 ◽  
Author(s):  
Enrico Arnone ◽  
Nick Pepin ◽  
Elisa Palazzi ◽  
Sven Kotlarski ◽  
Silvia Terzago ◽  
...  

<p>Mountain and high elevation regions often show distinct climate trends in temperature and precipitation, which can contrast those of adjacent lowland regions. In the context of temperature, this phenomenon is known as elevation-dependent warming (EDW). Past temperature trends can increase with elevation, but this is not always so, and they may peak in a critical elevation band, or show more complex elevation profiles. This is controlled by a variety of mechanisms which may be responsible for the observed patterns, including snow albedo feedback, vegetation change, cloud and moisture patterns, aerosol forcing and their interactions.</p><p>We here present a literature-based meta-analysis of elevation profiles in recent warming rates and, in a more general context, temperature change in mountain regions around the globe. For the recent historical period (~1960-2010) we find that when comparing like with like (i.e. high elevation regions with adjacent low elevation regions) warming rates are mostly stronger at higher elevations. Warming rates have also increased over time, with more recent decades showing stronger warming.<span> </span>On a global scale there is no significant difference between mean warming rates in mountains and in other areas. Thus, elevation-dependency within regions can be masked by differences in geographical location in global meta-analyses. Although there have been far fewer studies on vertical profiles of precipitation changes, we extend our meta-analysis to consider this parameter,<span>  </span>where information is available.</p><p>In addition to the meta-analysis, we compare past temperature and precipitation changes in mountain and lowland regions using global gridded observation-based and reanalysis datasets (e.g. CRU, ERA5, NCEP2) and global climate model simulations (CMIP5). Despite the uncertainties of these datasets (e.g. inhomogeneous underlying station coverage and related interpolation errors, biases, coarse spatial resolution), they allow us to compare different mountain regions globally with the same level of accuracy. There are only a few mountain areas that show distinct differences when their temperature trends are compared with lowland surroundings, but patterns vary by dataset and region. We also explore different extensions of adjacent lowlands, which may influence the quantification of differences in temperature and precipitation trends at high and low elevation.</p><p>This historical assessment is completed by an analysis of model projections (CMIP5) for studying the expected future evolution of climate change in mountains and contrasts to adjacent lowlands</p>


2017 ◽  
Vol 56 (6) ◽  
pp. 1625-1641 ◽  
Author(s):  
Stephen R. Sobie ◽  
Trevor Q. Murdock

AbstractKnowledge from high-resolution daily climatological parameters is frequently sought after for increasingly local climate change assessments. This research investigates whether applying a simple postprocessing methodology to existing statistically downscaled temperature and precipitation fields can result in improved downscaled simulations useful at the local scale. Initial downscaled daily simulations of temperature and precipitation at 10-km resolution are produced using bias correction constructed analogs with quantile mapping (BCCAQ). Higher-resolution (800 m) values are then generated using the simpler climate imprint technique in conjunction with temperature and precipitation climatologies from the Parameter-Elevation Regression on Independent Slopes Model (PRISM). The potential benefit of additional downscaling to 800 m is evaluated using the “Climdex” set of 27 indices of extremes established by the Expert Team on Climate Change Detection and Indices (ETCCDI). These indices are also calculated from weather station observations recorded at 22 locations within southwestern British Columbia, Canada, to evaluate the performance of both the 10-km and 800-m datasets in replicating the observed quantities. In a 30-yr historical evaluation period, Climdex indices computed from 800-m simulated values display reduced error relative to local station observations than those from the 10-km dataset, with the greatest reduction in error occurring at high-elevation sites for precipitation-based indices.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yong Zhang ◽  
Lu-yu Liu ◽  
Yi Liu ◽  
Man Zhang ◽  
Cheng-bang An

AbstractWithin the mountain altitudinal vegetation belts, the shift of forest tree lines and subalpine steppe belts to high altitudes constitutes an obvious response to global climate change. However, whether or not similar changes occur in steppe belts (low altitude) and nival belts in different areas within mountain systems remain undetermined. It is also unknown if these, responses to climate change are consistent. Here, using Landsat remote sensing images from 1989 to 2015, we obtained the spatial distribution of altitudinal vegetation belts in different periods of the Tianshan Mountains in Northwestern China. We suggest that the responses from different altitudinal vegetation belts to global climate change are different. The changes in the vegetation belts at low altitudes are spatially different. In high-altitude regions (higher than the forest belts), however, the trend of different altitudinal belts is consistent. Specifically, we focused on analyses of the impact of changes in temperature and precipitation on the nival belts, desert steppe belts, and montane steppe belts. The results demonstrated that the temperature in the study area exhibited an increasing trend, and is the main factor of altitudinal vegetation belts change in the Tianshan Mountains. In the context of a significant increase in temperature, the upper limit of the montane steppe in the eastern and central parts will shift to lower altitudes, which may limit the development of local animal husbandry. The montane steppe in the west, however, exhibits the opposite trend, which may augment the carrying capacity of pastures and promote the development of local animal husbandry. The lower limit of the nival belt will further increase in all studied areas, which may lead to an increase in surface runoff in the central and western regions.


Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 119
Author(s):  
Antonio Fidel Santos-Hernández ◽  
Alejandro Ismael Monterroso-Rivas ◽  
Diódoro Granados-Sánchez ◽  
Antonio Villanueva-Morales ◽  
Malinali Santacruz-Carrillo

The tropical rainforest is one of the lushest and most important plant communities in Mexico’s tropical regions, yet its potential distribution has not been studied in current and future climate conditions. The aim of this paper was to propose priority areas for conservation based on ecological niche and species distribution modeling of 22 species with the greatest ecological importance at the climax stage. Geographic records were correlated with bioclimatic temperature and precipitation variables using Maxent and Kuenm software for each species. The best Maxent models were chosen based on statistical significance, complexity and predictive power, and current potential distributions were obtained from these models. Future potential distributions were projected with two climate change scenarios: HADGEM2_ES and GFDL_CM3 models and RCP 8.5 W/m2 by 2075–2099. All potential distributions for each scenario were then assembled for further analysis. We found that 14 tropical rainforest species have the potential for distribution in 97.4% of the landscape currently occupied by climax vegetation (0.6% of the country). Both climate change scenarios showed a 3.5% reduction in their potential distribution and possible displacement to higher elevation regions. Areas are proposed for tropical rainforest conservation where suitable bioclimatic conditions are expected to prevail.


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