Linking species traits and demography to explain complex temperature responses across levels of organization

2021 ◽  
Vol 118 (42) ◽  
pp. e2104863118
Author(s):  
Daniel J. Wieczynski ◽  
Pranav Singla ◽  
Adrian Doan ◽  
Alexandra Singleton ◽  
Ze-Yi Han ◽  
...  
Keyword(s):  
Climate Change ◽  
Scale Up ◽  
Species Traits ◽  
Individual Performance ◽  
Community Respiration ◽  
Ecosystem Responses ◽  
Cascading Effects ◽  
Levels Of Organization ◽  
Environmental Responses ◽  
Temperature Responses

Microbial communities regulate ecosystem responses to climate change. However, predicting these responses is challenging because of complex interactions among processes at multiple levels of organization. Organismal traits that determine individual performance and ecological interactions are essential for scaling up environmental responses from individuals to ecosystems. We combine protist microcosm experiments and mathematical models to show that key traits—cell size, shape, and contents—each explain different aspects of species’ demographic responses to changes in temperature. These differences in species’ temperature responses have complex cascading effects across levels of organization—causing nonlinear shifts in total community respiration rates across temperatures via coordinated changes in community composition, equilibrium densities, and community–mean species mass in experimental protist communities that tightly match theoretical predictions. Our results suggest that traits explain variation in population growth, and together, these two factors scale up to influence community- and ecosystem-level processes across temperatures. Connecting the multilevel microbial processes that ultimately influence climate in this way will help refine predictions about complex ecosystem–climate feedbacks and the pace of climate change itself.

scholarly journals Simple traits predict complex temperature responses across scales

2021 ◽  
Author(s):  
Daniel Wieczynski ◽  
Pranav Singla ◽  
Adrian Doan ◽  
Alexandra Singleton ◽  
Zeyi Han ◽  
...  
Keyword(s):  
Climate Change ◽  
Microbial Community Composition ◽  
Scale Up ◽  
Individual Performance ◽  
Ecosystem Responses ◽  
Cascading Effects ◽  
Complex Interactions ◽  
Environmental Responses ◽  
Complex Temperature ◽  
Temperature Responses

Abstract Microbial communities regulate ecosystem responses to climate change. But predicting these responses is challenging due to complex interactions among processes at multiple ecological scales. Organismal traits that determine individual performance and ecological interactions are essential for scaling up predictions of environmental responses from individuals to ecosystems. We combine experiments and mathematical models to show that key microbial traits—cell size, shape, and cell contents—independently drive shifts in demographic rates across temperatures, having cascading effects on community structure, dynamics, and ecosystem function. Moreover, intra- and interspecific trait variation play distinct, trait-specific roles in temperature responses. These species-level responses scale up to cause predictable, nonlinear shifts in microbial community composition and respiration rates, with direct implications for the effects of warming on the global carbon cycle. Mechanistically linking microbes with climate using traits will help refine predictions about complex ecosystem-climate feedbacks and the pace of climate change.

scholarly journals Detecting Climate Driven Changes in Chlorophyll-a in Deep Subalpine Lakes Using Long Term Satellite Data

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 866
Author(s):  
Gary Free ◽  
Mariano Bresciani ◽  
Monica Pinardi ◽  
Nicola Ghirardi ◽  
Giulia Luciani ◽  
...  
Keyword(s):  
Climate Change ◽  
Chlorophyll A ◽  
Nutrient Dynamics ◽  
Cascading Effects ◽  
The North ◽  
Subalpine Lakes ◽  
Winter Temperatures ◽  
Decadal Climate ◽  
The North Atlantic Oscillation ◽  
Traditional Pattern

Climate change has increased the temperature and altered the mixing regime of high-value lakes in the subalpine region of Northern Italy. Remote sensing of chlorophyll-a can help provide a time series to allow an assessment of the ecological implications of this. Non-parametric multiplicative regression (NPMR) was used to visualize and understand the changes that have occurred between 2003–2018 in Lakes Garda, Como, Iseo, and Maggiore. In all four deep subalpine lakes, there has been a disruption from a traditional pattern of a significant spring chlorophyll-a peak followed by a clear water phase and summer/autumn peaks. This was replaced after 2010–2012, with lower spring peaks and a tendency for annual maxima to occur in summer. There was a tendency for this switch to be interspersed by a two-year period of low chlorophyll-a. Variables that were significant in NPMR included time, air temperature, total phosphorus, winter temperature, and winter values for the North Atlantic Oscillation. The change from spring to summer chlorophyll-a maxima, relatively sudden in an ecological context, could be interpreted as a regime shift. The cause was probably cascading effects from increased winter temperatures, reduced winter mixing, and altered nutrient dynamics. Future trends will depend on climate change and inter-decadal climate drivers.

scholarly journals Impact Assessment Analysis of Sea Level Rise in Denmark: A Case Study of Falster Island, Guldborgsund

2021 ◽  
Vol 13 (13) ◽  
pp. 7503
Author(s):  
Alexander Boest-Petersen ◽  
Piotr Michalak ◽  
Jamal Jokar Arsanjani
Keyword(s):  
Climate Change ◽  
Impact Assessment ◽  
Sea Level Rise ◽  
Sea Level ◽  
Alternative Methods ◽  
Projection Data ◽  
Storm Events ◽  
Cascading Effects ◽  
Local Levels

Anthropogenically-induced climate change is expected to be the contributing cause of sea level rise and severe storm events in the immediate future. While Danish authorities have downscaled the future oscillation of sea level rise across Danish coast lines in order to empower the coastal municipalities, there is a need to project the local cascading effects on different sectors. Using geospatial analysis and climate change projection data, we developed a proposed workflow to analyze the impacts of sea level rise in the coastal municipalities of Guldborgsund, located in Southeastern Denmark as a case study. With current estimates of sea level rise and storm surge events, the island of Falster can expect to have up to 19% of its landmass inundated, with approximately 39% of the population experiencing sea level rise directly. Developing an analytical workflow can allow stakeholders to understand the extent of expected sea level rise and consider alternative methods of prevention at the national and local levels. The proposed approach along with the choice of data and open source tools can empower other communities at risk of sea level rise to plan their adaptation.

scholarly journals Climate pattern-scaling set for an ensemble of 22 GCMs – adding uncertainty to the IMOGEN version 2.0 impact system

2018 ◽  
Vol 11 (2) ◽  
pp. 541-560 ◽  
Author(s):  
Przemyslaw Zelazowski ◽  
Chris Huntingford ◽  
Lina M. Mercado ◽  
Nathalie Schaller
Keyword(s):  
Climate Change ◽  
Relative Humidity ◽  
Land Surface ◽  
Land Surface Model ◽  
Individual Performance ◽  
Balance Model ◽  
Surface Model ◽  
Near Surface ◽  
Global Circulation Models ◽  
Version 2.0

Abstract. Global circulation models (GCMs) are the best tool to understand climate change, as they attempt to represent all the important Earth system processes, including anthropogenic perturbation through fossil fuel burning. However, GCMs are computationally very expensive, which limits the number of simulations that can be made. Pattern scaling is an emulation technique that takes advantage of the fact that local and seasonal changes in surface climate are often approximately linear in the rate of warming over land and across the globe. This allows interpolation away from a limited number of available GCM simulations, to assess alternative future emissions scenarios. In this paper, we present a climate pattern-scaling set consisting of spatial climate change patterns along with parameters for an energy-balance model that calculates the amount of global warming. The set, available for download, is derived from 22 GCMs of the WCRP CMIP3 database, setting the basis for similar eventual pattern development for the CMIP5 and forthcoming CMIP6 ensemble. Critically, it extends the use of the IMOGEN (Integrated Model Of Global Effects of climatic aNomalies) framework to enable scanning across full uncertainty in GCMs for impact studies. Across models, the presented climate patterns represent consistent global mean trends, with a maximum of 4 (out of 22) GCMs exhibiting the opposite sign to the global trend per variable (relative humidity). The described new climate regimes are generally warmer, wetter (but with less snowfall), cloudier and windier, and have decreased relative humidity. Overall, when averaging individual performance across all variables, and without considering co-variance, the patterns explain one-third of regional change in decadal averages (mean percentage variance explained, PVE, 34.25±5.21), but the signal in some models exhibits much more linearity (e.g. MIROC3.2(hires): 41.53) than in others (GISS_ER: 22.67). The two most often considered variables, near-surface temperature and precipitation, have a PVE of 85.44±4.37 and 14.98±4.61, respectively. We also provide an example assessment of a terrestrial impact (changes in mean runoff) and compare projections by the IMOGEN system, which has one land surface model, against direct GCM outputs, which all have alternative representations of land functioning. The latter is noted as an additional source of uncertainty. Finally, current and potential future applications of the IMOGEN version 2.0 modelling system in the areas of ecosystem modelling and climate change impact assessment are presented and discussed.

Ecosystem responses to climate change in a large on-river reservoir, Lake Paldang, Korea

2013 ◽  
Vol 120 (1-2) ◽  
pp. 477-489 ◽  
Author(s):  
Hae-Kyung Park ◽  
Kang-Hyun Cho ◽  
Doo Hee Won ◽  
Jangho Lee ◽  
Dong-Soo Kong ◽  
...  
Keyword(s):  
Climate Change ◽  
Ecosystem Responses ◽  
River Reservoir

scholarly journals A trait-based approach to assess climate change sensitivity of freshwater invertebrates across Swedish ecoregions

2014 ◽  
Vol 60 (2) ◽  
pp. 221-232 ◽  
Author(s):  
Leonard Sandin ◽  
Astrid Schmidt-Kloiber ◽  
Jens-Christian Svenning ◽  
Erik Jeppesen ◽  
Nikolai Friberg
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Large Scale ◽  
Global Climate ◽  
Species Traits ◽  
Freshwater Ecosystems ◽  
Biological Data ◽  
Conservation Strategies ◽  
Measured Temperature ◽  
Buffer Strips

Abstract Freshwater habitats and organisms are among the most threatened on Earth, and freshwater ecosystems have been subject to large biodiversity losses. We developed a Climate Change Sensitivity (CCS) indicator based on trait information for a selection of stream- and lake-dwelling Ephemeroptera, Plecoptera and Trichoptera taxa. We calculated the CCS scores based on ten species traits identified as sensitive to global climate change. We then assessed climate change sensitivity between the six main ecoregions of Sweden as well as the three Swedish regions based on Illies. This was done using biological data from 1, 382 stream and lake sites where we compared large-scale (ecoregional) patterns in climate change sensitivity with potential future exposure of these ecosystems to increased temperatures using ensemble-modelled future changes in air temperature. Current (1961~1990) measured temperature and ensemble-modelled future (2100) temperature showed an increase from the northernmost towards the southern ecoregions, whereas the predicted temperature change increased from south to north. The CCS indicator scores were highest in the two northernmost boreal ecoregions where we also can expect the largest global climate change-induced increase in temperature, indicating an unfortunate congruence of exposure and sensitivity to climate change. These results are of vital importance when planning and implementing management and conservation strategies in freshwater ecosystems, e.g., to mitigate increased temperatures using riparian buffer strips. We conclude that traits information on taxa specialization, e.g., in terms of feeding specialism or taxa having a preference for high altitudes as well as sensitivity to changes in temperature are important when assessing the risk from future global climate change to freshwater ecosystems.

A Cost Benefit Analysis for Distribution of Threatened Species Based on Climate Change

2021 ◽  
Author(s):  
R. Nandhi Kesavan ◽  
Latha K
Keyword(s):  
Climate Change ◽  
Endangered Species ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Species Traits ◽  
Ecological Traits ◽  
Species List ◽  
Critically Endangered Species ◽  
Reptile Species ◽  
The Cost

Abstract Among all the threats to global diversity, climate change is the most severe cause. According to the world’s biodiversity conservation organization, reptile species are affected mostly because the biological and ecological traits of the reptiles are strongly linked with climate. To prevent species extinction, we tried to develop a decision support system that incurs the costs and benefits of reintroducing a taxon from its origin to adapt environmental conditions to conserve it from its extinction. The model was developed by applying multiple linear regressions that take the climatic variables and species traits to determine the cost and benefits for the distribution of species. The effectiveness of the model was evaluated by applying it to the Indian Black Turtle, which is an endangered species list in India evaluated by the International Union for Conservation of Nature list. The model recommends moving the species, which is endangered, to the location where it can save itself from climate change. However, the framework demonstrates huge differences in the estimated significance of climate change, and the model strategy helps to recognize the probable risk of increased revelation to critically endangered species.

scholarly journals Peculiarly pleasant weather for US maize

2018 ◽  
Vol 115 (47) ◽  
pp. 11935-11940 ◽  
Author(s):  
Ethan E. Butler ◽  
Nathaniel D. Mueller ◽  
Peter Huybers
Keyword(s):  
Climate Change ◽  
Growing Season ◽  
Crop Model ◽  
World Population ◽  
Growth Phases ◽  
Climate Trends ◽  
Historical Trends ◽  
Yield Trends ◽  
The Relationship ◽  
Temperature Responses

Continuation of historical trends in crop yield are critical to meeting the demands of a growing and more affluent world population. Climate change may compromise our ability to meet these demands, but estimates vary widely, highlighting the importance of understanding historical interactions between yield and climate trends. The relationship between temperature and yield is nuanced, involving differential yield outcomes to warm (9−29 °C) and hot (>29 °C) temperatures and differing sensitivity across growth phases. Here, we use a crop model that resolves temperature responses according to magnitude and growth phase to show that US maize has benefited from weather shifts since 1981. Improvements are related to lengthening of the growing season and cooling of the hottest temperatures. Furthermore, current farmer cropping schedules are more beneficial in the climate of the last decade than they would have been in earlier decades, indicating statistically significant adaptation to a changing climate of 13 kg·ha−1· decade−1. All together, the better weather experienced by US maize accounts for 28% of the yield trends since 1981. Sustaining positive trends in yield depends on whether improvements in agricultural climate continue and the degree to which farmers adapt to future climates.

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