Back

Trait and Growth Responses to Sequential Environmental Change linked to Sensitivity in Synechococcus populations

Sikder, A.; Kremer, C. T.; Laender, F. D.

2025-06-17 ecology
10.1101/2025.06.11.659080 bioRxiv
Show abstract

O_LIEnvironmental change often occurs as a sequence of stressors rather than as isolated events. While the individual and combined effects of multiple stressors are well studied, the ecological consequences of sequential environmental change remain poorly understood. Such sequences, for example, a marine heatwave followed by seasonal herbicide runoff, are increasingly common under global change. C_LIO_LIWe investigated how legacy effects (the imprint of past environmental conditions) influence subsequent population performance and functional traits, and how these effects are mediated by strain-specific sensitivities. C_LIO_LIUsing a fully factorial design, we exposed six strains of the globally abundant pico-phytoplankton Synechococcus sp. to three environmental conditions: warming, herbicide exposure, and a control, under both chronic (same condition across time) and sequential (different conditions across time) regimes. We measured population performance (per-capita growth rate, maximum density) and key functional traits (cell size, chlorophyll content). C_LIO_LIPopulation responses diverged significantly between chronic and sequential exposures, revealing a strong legacy effect. Trait changes were often decoupled from growth metrics, suggesting independent response axes. Strain identity and its interaction with past conditions explained substantial variation in both growth and trait responses. C_LIO_LIWe identify and conceptualise four distinct mechanisms of legacy effects during sequential change: overcompensation, amplification, constraint and depression, each linked to strain-specific responses. Consequently, incorporating legacy effects into predictions of biodiversity dynamics and ecosystem function under global change is therefore both feasible and essential. C_LI

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Global Change Biology
69 papers in training set
Top 0.1%
40.2%
2
Nature Communications
4913 papers in training set
Top 32%
5.0%
3
Proceedings of the National Academy of Sciences
2130 papers in training set
Top 13%
5.0%
50% of probability mass above
4
Proceedings of the Royal Society B: Biological Sciences
341 papers in training set
Top 2%
4.4%
5
Ecology Letters
121 papers in training set
Top 0.5%
3.1%
6
Philosophical Transactions of the Royal Society B
51 papers in training set
Top 2%
2.7%
7
Ecology and Evolution
232 papers in training set
Top 2%
2.1%
8
Philosophical Transactions of the Royal Society B: Biological Sciences
53 papers in training set
Top 0.3%
1.9%
9
Ecological Applications
28 papers in training set
Top 0.2%
1.9%
10
Limnology and Oceanography
26 papers in training set
Top 0.1%
1.8%
11
Molecular Ecology
304 papers in training set
Top 3%
1.7%
12
Nature Microbiology
133 papers in training set
Top 2%
1.7%
13
eLife
5422 papers in training set
Top 42%
1.7%
14
Ecology
70 papers in training set
Top 0.5%
1.4%
15
Environmental Microbiology
119 papers in training set
Top 2%
1.3%
16
Global Ecology and Biogeography
41 papers in training set
Top 0.4%
1.3%
17
Ecography
50 papers in training set
Top 0.9%
1.1%
18
The ISME Journal
194 papers in training set
Top 2%
1.0%
19
Ecological Modelling
24 papers in training set
Top 0.4%
1.0%
20
Ecological Monographs
18 papers in training set
Top 0.1%
0.9%
21
PLOS Biology
408 papers in training set
Top 16%
0.9%
22
New Phytologist
309 papers in training set
Top 4%
0.8%
23
Evolution Letters
71 papers in training set
Top 2%
0.8%
24
ISME Communications
103 papers in training set
Top 2%
0.8%
25
Water Research
74 papers in training set
Top 1%
0.8%
26
Journal of Experimental Biology
249 papers in training set
Top 2%
0.8%
27
Frontiers in Marine Science
55 papers in training set
Top 1%
0.7%
28
Communications Biology
886 papers in training set
Top 28%
0.7%
29
PLOS Computational Biology
1633 papers in training set
Top 28%
0.5%
30
Frontiers in Ecology and Evolution
60 papers in training set
Top 5%
0.5%