scholarly journals Climate change and Saharan dust drive recent cladoceran and primary production changes in remote alpine lakes of Sierra Nevada, Spain

2017 ◽  
Vol 24 (1) ◽  
pp. e139-e158 ◽  
Author(s):  
Laura Jiménez ◽  
Kathleen M. Rühland ◽  
Adam Jeziorski ◽  
John P. Smol ◽  
Carmen Pérez-Martínez
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Sierra Nevada ◽  
Alpine Lakes ◽  
Saharan Dust

scholarly journals Effects of oligotrophication on primary production in peri-alpine lakes

2013 ◽  
Vol 49 (8) ◽  
pp. 4700-4710 ◽  
Author(s):  
David Finger ◽  
Alfred Wüest ◽  
Peter Bossard
Keyword(s):  
Primary Production ◽  
Alpine Lakes

scholarly journals Carbon Fixation Trends in Eleven of the World’s Largest Lakes: 2003–2018

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3500
Author(s):  
Michael Sayers ◽  
Karl Bosse ◽  
Gary Fahnenstiel ◽  
Robert Shuchman
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Great Lakes ◽  
Satellite Remote Sensing ◽  
Carbon Fixation ◽  
African Great Lakes ◽  
Wind Speeds ◽  
Bear Lake ◽  
Great Slave Lake ◽  
Significant Production

Large freshwater lakes provide immense value to the surrounding populations, yet there is limited understanding of how these lakes will respond to climate change and other factors. This study uses satellite remote sensing to estimate annual, lake-wide primary production in 11 of the world’s largest lakes from 2003–2018. These lakes include the five Laurentian Great Lakes, the three African Great Lakes, Lake Baikal, and Great Bear and Great Slave Lakes. Mean annual production in these lakes ranged from under 200 mgC/m2/day to over 1100 mgC/m2/day, and the lakes were placed into one of three distinct groups (oligotrophic, mesotrophic, or eutrophic) based on their level of production. The analysis revealed only three lakes with significant production trends over the study period, with increases in Great Bear Lake (24% increase over the study period) and Great Slave Lake (27%) and a decline in Lake Tanganyika (−16%). These changes appear to be related to climate change, including increasing temperatures and solar radiation and decreasing wind speeds. This study is the first to use consistent methodology to study primary production in the world’s largest lakes, allowing for these novel between-lake comparisons and assessment of inter-annual trends.

scholarly journals Regional variability of acidification in the Arctic: a sea of contrasts

2014 ◽  
Vol 11 (2) ◽  
pp. 293-308 ◽  
Author(s):  
E. E. Popova ◽  
A. Yool ◽  
Y. Aksenov ◽  
A. C. Coward ◽  
T. R. Anderson
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Arctic Ocean ◽  
Canadian Arctic ◽  
Atmospheric Co2 ◽  
The Arctic ◽  
Canadian Arctic Archipelago ◽  
Regional Variability ◽  
The Arctic Ocean ◽  
The Impact

Abstract. The Arctic Ocean is a region that is particularly vulnerable to the impact of ocean acidification driven by rising atmospheric CO2, with potentially negative consequences for calcifying organisms such as coccolithophorids and foraminiferans. In this study, we use an ocean-only general circulation model, with embedded biogeochemistry and a comprehensive description of the ocean carbon cycle, to study the response of pH and saturation states of calcite and aragonite to rising atmospheric pCO2 and changing climate in the Arctic Ocean. Particular attention is paid to the strong regional variability within the Arctic, and, for comparison, simulation results are contrasted with those for the global ocean. Simulations were run to year 2099 using the RCP8.5 (an Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) scenario with the highest concentrations of atmospheric CO2). The separate impacts of the direct increase in atmospheric CO2 and indirect effects via impact of climate change (changing temperature, stratification, primary production and freshwater fluxes) were examined by undertaking two simulations, one with the full system and the other in which atmospheric CO2 was prevented from increasing beyond its preindustrial level (year 1860). Results indicate that the impact of climate change, and spatial heterogeneity thereof, plays a strong role in the declines in pH and carbonate saturation (Ω) seen in the Arctic. The central Arctic, Canadian Arctic Archipelago and Baffin Bay show greatest rates of acidification and Ω decline as a result of melting sea ice. In contrast, areas affected by Atlantic inflow including the Greenland Sea and outer shelves of the Barents, Kara and Laptev seas, had minimal decreases in pH and Ω because diminishing ice cover led to greater vertical mixing and primary production. As a consequence, the projected onset of undersaturation in respect to aragonite is highly variable regionally within the Arctic, occurring during the decade of 2000–2010 in the Siberian shelves and Canadian Arctic Archipelago, but as late as the 2080s in the Barents and Norwegian seas. We conclude that, for future projections of acidification and carbonate saturation state in the Arctic, regional variability is significant and needs to be adequately resolved, with particular emphasis on reliable projections of the rates of retreat of the sea ice, which are a major source of uncertainty.

scholarly journals Saharan Dust Impacts and Climate Change

Oceanography ◽  
2006 ◽  
Vol 19 (2) ◽  
pp. 60-61 ◽  
Author(s):  
Joseph Prospero
Keyword(s):  
Climate Change ◽  
Saharan Dust

scholarly journals Hydrologic sensitivity of the Upper San Joaquin River Watershed in California to climate change scenarios

2012 ◽  
Vol 44 (4) ◽  
pp. 723-736 ◽  
Author(s):  
Zili He ◽  
Zhi Wang ◽  
C. John Suen ◽  
Xiaoyi Ma
Keyword(s):  
Climate Change ◽  
Sierra Nevada ◽  
Climate Change Scenarios ◽  
Intergovernmental Panel ◽  
Hydrological Simulation ◽  
River Watershed ◽  
System Sensitivity ◽  
Hspf Model ◽  
San Joaquin River ◽  
San Joaquin River Watershed

To examine the hydrological system sensitivity of the southern Sierra Nevada Mountains of California to climate change scenarios (CCS), five headwater basins in the snow-dominated Upper San Joaquin River Watershed (USJRW) were selected for hydrologic simulations using the Hydrological Simulation Program-Fortran (HSPF) model. A pre-specified set of CCS as projected by the Intergovernmental Panel on Climate Change (IPCC) were adopted as inputs for the hydrologic analysis. These scenarios include temperature increases between 1.5 and 4.5 °C and precipitation variation between 80 and 120% of the baseline conditions. The HSPF model was calibrated and validated with measured historical data. It was then used to simulate the hydrologic responses of the watershed to the projected CCS. Results indicate that the streamflow of USJRW is sensitive to the projected climate change. The total volume of annual streamflow would vary between −41 and +16% compared to the baseline years (1970–1990). Even if the precipitation remains unchanged, the total annual flow would still decrease by 8–23% due to temperature increases. A larger portion of the streamflow would occur earlier in the water year by 15–46 days due to the temperature increases, causing higher seasonal variability of streamflow.

scholarly journals Desertification in Forest, Range and Desert Landuses of Tehran Province, Under the Impact of Climate Change

2016 ◽  
Author(s):  
Hadi Eskandari Dameneh ◽  
Moslem Borji ◽  
Hassan Khosravi ◽  
Ali Salajeghe
Keyword(s):  
Climate Change ◽  
Primary Production ◽  
Net Primary Production ◽  
Degradation Process ◽  
Early Warning Systems ◽  
Land Uses ◽  
Emission Scenarios ◽  
Desert Ecosystems ◽  
Tehran Province ◽  
The Impact

Abstract. Persistence of widespread degradation in arid and semi-arid region of Iran necessitates using of monitoring and evaluation systems with appropriate accuracy to determine the degradation process and adoption of early warning systems; because after transition from some thresholds, effective reversible function of ecosystems will not be very easy. This paper tries to monitor the degradation and desertification trends in three land uses including range, forest and desert lands affected by climate change in Tehran province for 2000s and 2030s. For assessing climate changes of Mehrabad synoptic stations the data of two emission scenarios including A2 and B2 were used using statistical downscaling techniques and data generated by SDSM model. The index of net primary production resulting from MODIS satellite images was employed as an indicator of destruction from 2001 to 2010. The results showed that temperature is the most effective driver force which alters the net primary production in rangeland, forest and desert ecosystems of Tehran province. On the basis of monitoring findings under real conditions, in the 2000s, over 60 % of rangelands and 80 % of the forests have been below the average production in the province. On the other hand, the long-term average changes of NPP in rangeland and forests indicated the presence of relatively large areas of these land uses with production rate lower than the desert. The results also showed that, assuming the existence of circumstances of each emission scenarios, the desertification status will not improve significantly in the rangelands and forests of Tehran province.

scholarly journals Gross Primary Production and False Spring: a spatio-temporal analysis

2020 ◽  
Author(s):  
Emma Izquierdo-Verdiguier ◽  
Raúl Zurita-Milla ◽  
Álvaro Moreno-Martinez ◽  
Gustau Camps-Valls ◽  
Anja Klisch ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Primary Production ◽  
Gross Primary Production ◽  
Damage Index ◽  
Temporal Analysis ◽  
Environmental Stressors ◽  
Impact Of Climate Change ◽  
False Spring ◽  
Spatial Temporal Analysis

<p>Phenological information can be obtained from different sources of data. For instance, from remote sensing data or products and from models driven by weather variables. The former typically allows analyzing land surface phenology whereas the latter provide plant phenological information. Analyzing relationships between both sources of data allows us to understand the impact of climate change on vegetation over space and time. For example, the onset of spring is advanced or delayed by changes in the climate. These alterations affect plant productivity and animal migrations.</p><p>Spring onset monitoring is supported by the Extended Spring Index (SI-x), which are a suite of regression-based models for key indicator plant species. These models (Schwartz et al. in 2013) are based on daily maximum and minimum temperature from the first day of the year (January 1<sup>st</sup>). The primary products of these models are the timing of first leaf and first bloom, but they also provide derivative products such as the timing of last freeze day and the risk of frost damage day (damage index) for each year. This information helps to understand if vegetation could have suffered from environmental stressors such as droughts or a late frost events. The effects of environmental stressors in vegetation could be captured by the false spring index, which relates the first leaf day and the last freeze day. Moreover, this information could be used to understand plant productivity as well as to evaluate the economic impact of climate change.</p><p>Previous works studied the relationship between remote sensing and plant level products by means of spatial-temporal analysis between Gross Primary Production (GPP) and a spring onset index. However, they did not consider the possible impact of false spring effect in these relationships. Here, we present a spatial-temporal analysis between GPP and the damage index to better understand the effect of false springs (in annual gross photosynthesis data). The analysis is done for the period 2000 to 2015 over the contiguous US and at spatial resolution of 1 km. We used the MODIS annual sum of GPP and the damage and false spring indices derived from the SI-x models.</p>

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