Morón Lugo SC et al. (2020), Warming and temperature variability determine t...

ECB-ART-49858

Sci Rep 2020 Apr 22;101:6780. doi: 10.1038/s41598-020-63679-0.

Show Gene links Show Anatomy links

Warming and temperature variability determine the performance of two invertebrate predators.

Morón Lugo SC , Baumeister M , Nour OM , Wolf F , Stumpp M , Pansch C .

???displayArticle.abstract???
In a warming ocean, temperature variability imposes intensified peak stress, but offers periods of stress release. While field observations on organismic responses to heatwaves are emerging, experimental evidence is rare and almost lacking for shorter-scale environmental variability. For two major invertebrate predators, we simulated sinusoidal temperature variability (±3 °C) around todays' warm summer temperatures and around a future warming scenario (+4 °C) over two months, based on high-resolution 15-year temperature data that allowed implementation of realistic seasonal temperature shifts peaking midpoint. Warming decreased sea stars' (Asterias rubens) energy uptake (Mytilus edulis consumption) and overall growth. Variability around the warming scenario imposed additional stress onto Asterias leading to an earlier collapse in feeding under sinusoidal fluctuations. High-peak temperatures prevented feeding, which was not compensated during phases of stress release (low-temperature peaks). In contrast, increased temperatures increased feeding on Mytilus but not growth rates of the recent invader Hemigrapsus takanoi, irrespective of the scale at which temperature variability was imposed. This study highlights species-specific impacts of warming and identifies temperature variability at the scale of days to weeks/months as important driver of thermal responses. When species' thermal limits are exceeded, temperature variability represents an additional source of stress as seen from future warming scenarios.

???displayArticle.pubmedLink??? 32321937
???displayArticle.pmcLink??? PMC7176636
???displayArticle.link??? Sci Rep

???attribute.lit??? ???displayArticles.show???

	Figure 1. Experimental temperature regimes, experimental design and setup. Implemented temperatures for the four temperature treatments, Ambient (A), Ambient Sinusoidal (A-S), Warm (W) and Warm Sinusoidal (W-S; A). Energy uptake of individuals was summed at three different scales: (i) at the scale of short-term variability (2-day blocks in repeated 8-day sinusoidal temperature cycles, summed over the entire experiment: maximum temperature (1: Max), mean temperature after the maximum (2: Descending), minimum temperature (3: Min) and mean temperature after the minimum (4: Ascending); B), (ii) at the medium-term variability scale of seasonal summer temperature shifts (energy uptake as sum over 16-day blocks indicated by coloured bars in (A): Pre-heat, Heat and Post-heat), as well as (iii) at the scale of climate change impacts (identified by comparisons of ambient vs. warm treatments in ‘constant’ and sinusoidal fluctuating settings, using energy uptake as sum and growth over the entire ~2-months experimental duration; compare upper and lower diagrams in A). The treatments were realized within twelve indoor mesocosms, three mesocosms serving one temperature treatment (each mesocosm contained six 2 L experimental units, three of which contained single individuals of Asterias rubens (orange) and three of which contained single individuals of Hemigrapsus takanoi (yellow), N = 9; C).
	Figure 2. Energy uptake and change in wet weight of Asterias rubens. Energy uptake (A) and change in wet weight (B) during 72 days of experimentation, under ambient or warm and ‘constant’ or sinusoidal fluctuating temperature conditions (sum over the entire period, climate change in Fig. 1A). Data are presented as boxplots (median, upper and lower quartile (75th and 25th percentile), whiskers (1.5 times the interquartile range, outliers; N = 9). Significant differences between single treatment combinations were identified using a post hoc Tukey test at p < 0.05 and are indicated by lower-case letters.
	Figure 3. Phase dependent energy uptake of Asterias rubens. Energy uptake over 72 days of experimentation, summed for the four phases of the sinusoidal fluctuating cycle (short-term variability scale) for the ambient sinusoidal (A) and the warm sinusoidal (B) treatments, at maximum temperature (Max), mean temperature after the maximum (Descending), minimum temperature (Min) and mean temperature after the minimum (Ascending). All phases of a cycle are also illustrated in Fig. 1B. Data are presented as boxplots (median, upper and lower quartile (75th and 25th percentile), whiskers (1.5 times the interquartile range, outliers; N = 9). Significant differences between single treatment combinations were identified using a PERMANOVA pair-wise test at p < 0.05 and are indicated by lower-case letters.
	Figure 4. Period dependent energy uptake of Asterias rubens. Energy uptake under ambient (A), ambient sinusoidal (B), warm (C) and warm sinusoidal (D) temperature treatments (medium-term variability scale). Data were separated into three equally long 16-day time periods: Pre-heat (July 19th to August 4th), Heat (August 4th to August 20th) and Post-heat (August 20th to September 5th). Data are presented as boxplots (median, upper and lower quartile (75th and 25th percentile), whiskers (1.5 times the interquartile range, outliers; N = 9). Significant differences between single treatment combinations were identified using a post hoc Tukey test at p < 0.05 and are indicated by lower-case letters.
	Figure 5. Energy uptake and change in wet weight of Hemigrapsus takanoi. Energy uptake (A) and change in wet weight (B) during 64 days of experimentation, under ambient or wa rm and ‘constant’ or sinusoidal fluctuating temperature conditions (sum over the entire period, climate change in Fig. 1B). Data are presented as boxplots (median, upper and lower quartile (75th and 25th percentile), whiskers (1.5 times the interquartile range, outliers; N = 9). Significant differences between single treatment combinations were identified using a post hoc Tukey test at p < 0.05 and are indicated by lower-case letters.
	Figure 6. Phase dependent energy uptake of Hemigrapsus takanoi. Energy uptake over 64 days of experimentation, summed for the four phases of the sinusoidal fluctuating cycle (short-term variability scale) for the ambient sinusoidal (A) and the warm sinusoidal (B) treatments, at maximum temperature (Max), mean temperature after the maximum (Descending), minimum temperature (Min) and mean temperature after the minimum (Ascending). All phases of a cycle are illustrated in Fig. 1B. Data are presented as boxplots (median, upper and lower quartile (75th and 25th percentile), whiskers (1.5 times the interquartile range, outliers; N = 9). Significant differences between single treatment combinations were identified using a post hoc Tukey test at p < 0.05 and are indicated by lower-case letters.
	Figure 7. Period dependent energy uptake of Hemigrapsus takanoi. Energy uptake under ambient (A), ambient sinusoidal (B), warm (C) and warm sinusoidal (D) temperature treatments (medium-term variability scale). Data were separated into three equally long 16-day time periods: Pre-heat (July 19th to August 4th), Heat (August 4th to August 20th) and Post-heat (August 20th to September 5th). Data are presented as boxplots (median, upper and lower quartile (75th and 25th percentile), whiskers (1.5 times the interquartile range, outliers; N = 9).

References [+] :

Bates, Geographical range, heat tolerance and invasion success in aquatic species. 2013, Pubmed

Bates, Geographical range, heat tolerance and invasion success in aquatic species. 2013, Pubmed
Bernhardt, Resilience to climate change in coastal marine ecosystems. 2013, Pubmed
Boyd, Experimental strategies to assess the biological ramifications of multiple drivers of global ocean change-A review. 2018, Pubmed
Campbell, Climate change influences on global distributions of dengue and chikungunya virus vectors. 2015, Pubmed
Deutsch, Impacts of climate warming on terrestrial ectotherms across latitude. 2008, Pubmed
Doney, Climate change impacts on marine ecosystems. 2012, Pubmed
Feely, Evidence for upwelling of corrosive "acidified" water onto the continental shelf. 2008, Pubmed
Gunderson, Multiple Stressors in a Changing World: The Need for an Improved Perspective on Physiological Responses to the Dynamic Marine Environment. 2016, Pubmed
Harley, The impacts of climate change in coastal marine systems. 2006, Pubmed
Harrison, A brief introduction to mixed effects modelling and multi-model inference in ecology. 2018, Pubmed
Harvey, Meta-analysis reveals complex marine biological responses to the interactive effects of ocean acidification and warming. 2013, Pubmed
Havenhand, Ecological and functional consequences of coastal ocean acidification: Perspectives from the Baltic-Skagerrak System. 2019, Pubmed
Jensen, Temperature effects on aerobic scope and cardiac performance of European perch (Perca fluviatilis). 2017, Pubmed
Johannesson, Life on the margin: genetic isolation and diversity loss in a peripheral marine ecosystem, the Baltic Sea. 2006, Pubmed
King, Experimental evidence that human impacts drive fire ant invasions and ecological change. 2008, Pubmed
Koch, Climate change and ocean acidification effects on seagrasses and marine macroalgae. 2013, Pubmed
Kroeker, Impacts of ocean acidification on marine organisms: quantifying sensitivities and interaction with warming. 2013, Pubmed
Mat, Influence of temperature on daily locomotor activity in the crab Uca pugilator. 2017, Pubmed
Paaijmans, Temperature variation makes ectotherms more sensitive to climate change. 2013, Pubmed
Paganini, Temperature and acidification variability reduce physiological performance in the intertidal zone porcelain crab Petrolisthes cinctipes. 2014, Pubmed
Pansch, Heat waves and their significance for a temperate benthic community: A near-natural experimental approach. 2018, Pubmed
Pörtner, Climate variations and the physiological basis of temperature dependent biogeography: systemic to molecular hierarchy of thermal tolerance in animals. 2002, Pubmed
Pörtner, Ecology. Physiology and climate change. 2008, Pubmed
Reusch, The Baltic Sea as a time machine for the future coastal ocean. 2018, Pubmed
Ruel, Jensen's inequality predicts effects of environmental variation. 1999, Pubmed
Sampaio, Interaction strength between different grazers and macroalgae mediated by ocean acidification over warming gradients. 2017, Pubmed
Stillman, Adaptation to temperature stress and aerial exposure in congeneric species of intertidal porcelain crabs (genus Petrolisthes): correlation of physiology, biochemistry and morphology with vertical distribution. 1996, Pubmed
Tattersall, Coping with thermal challenges: physiological adaptations to environmental temperatures. 2012, Pubmed
Thomsen, Food availability outweighs ocean acidification effects in juvenile Mytilus edulis: laboratory and field experiments. 2013, Pubmed
Vasseur, Increased temperature variation poses a greater risk to species than climate warming. 2014, Pubmed
Waldbusser, Ocean acidification in the coastal zone from an organism's perspective: multiple system parameters, frequency domains, and habitats. 2014, Pubmed
Zhan, The Impact of Chronic Heat Stress on the Growth, Survival, Feeding, and Differential Gene Expression in the Sea Urchin Strongylocentrotus intermedius. 2019, Pubmed , Echinobase