» Articles » PMID: 36037344

Environmental Context Dependency in Species Interactions

Overview
Specialty Science
Date 2022 Aug 29
PMID 36037344
Authors
Affiliations
Soon will be listed here.
Abstract

Ecological interactions are not uniform across time and can vary with environmental conditions. Yet, interactions among species are often measured with short-term controlled experiments whose outcomes can depend greatly on the particular environmental conditions under which they are performed. As an alternative, we use empirical dynamic modeling to estimate species interactions across a wide range of environmental conditions directly from existing long-term monitoring data. In our case study from a southern California kelp forest, we test whether interactions between multiple kelp and sea urchin species can be reliably reconstructed from time-series data and whether those interactions vary predictably in strength and direction across observed fluctuations in temperature, disturbance, and low-frequency oceanographic regimes. We show that environmental context greatly alters the strength and direction of species interactions. In particular, the state of the North Pacific Gyre Oscillation seems to drive the competitive balance between kelp species, asserting bottom-up control on kelp ecosystem dynamics. We show the importance of specifically studying variation in interaction strength, rather than mean interaction outcomes, when trying to understand the dynamics of complex ecosystems. The significant context dependency in species interactions found in this study argues for a greater utilization of long-term data and empirical dynamic modeling in studies of the dynamics of other ecosystems.

Citing Articles

Abrupt changes in algal biomass of thousands of US lakes are related to climate and are more likely in low-disturbance watersheds.

Soranno P, Hanly P, Webster K, Wagner T, McDonald A, Shuvo A Proc Natl Acad Sci U S A. 2025; 122(9):e2416172122.

PMID: 39993195 PMC: 11892623. DOI: 10.1073/pnas.2416172122.


Environment-Organism Feedbacks Drive Changes in Ecological Interactions.

Meacock O, Mitri S Ecol Lett. 2024; 28(1):e70027.

PMID: 39737705 PMC: 11687356. DOI: 10.1111/ele.70027.


The impact of data resolution on dynamic causal inference in multiscale ecological networks.

Saberski E, Lorimer T, Carpenter D, Deyle E, Merz E, Park J Commun Biol. 2024; 7(1):1442.

PMID: 39500991 PMC: 11538442. DOI: 10.1038/s42003-024-07054-z.


Multiple resiliency metrics reveal complementary drivers of ecosystem persistence: An application to kelp forest systems.

Arroyo-Esquivel J, Adams R, Gravem S, Whippo R, Randell Z, Hodin J Ecology. 2024; 105(12):e4453.

PMID: 39462824 PMC: 11610656. DOI: 10.1002/ecy.4453.


Multifaceted effects of variable biotic interactions on population stability in complex interaction webs.

Hashimoto K, Hayasaka D, Eguchi Y, Seko Y, Cai J, Suzuki K Commun Biol. 2024; 7(1):1309.

PMID: 39438612 PMC: 11496648. DOI: 10.1038/s42003-024-06948-2.


References
1.
Deyle E, May R, Munch S, Sugihara G . Tracking and forecasting ecosystem interactions in real time. Proc Biol Sci. 2016; 283(1822). PMC: 4721089. DOI: 10.1098/rspb.2015.2258. View

2.
Reed D, Washburn L, Rassweiler A, Miller R, Bell T, Harrer S . Extreme warming challenges sentinel status of kelp forests as indicators of climate change. Nat Commun. 2016; 7:13757. PMC: 5159872. DOI: 10.1038/ncomms13757. View

3.
McCracken J, Weigel R . Convergent cross-mapping and pairwise asymmetric inference. Phys Rev E Stat Nonlin Soft Matter Phys. 2015; 90(6):062903. DOI: 10.1103/PhysRevE.90.062903. View

4.
Arkema K, Reed D, Schroeter S . Direct and indirect effects of giant kelp determine benthic community structure and dynamics. Ecology. 2009; 90(11):3126-37. DOI: 10.1890/08-1213.1. View

5.
Liu O, Gaines S . Environmental context dependency in species interactions. Proc Natl Acad Sci U S A. 2022; 119(36):e2118539119. PMC: 9457591. DOI: 10.1073/pnas.2118539119. View