Global ensemble projections reveal trophic amplification of ocean biomass declines with climate change.

While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends.

Biogeochemical validation of an interannual simulation of the ROMS-PISCES coupled model in the Southeast Pacific / Validación biogeoquímica de una simulación interanual del modelo acoplado ROMS-PISCES en el Pacífico Sudeste

Currently biogeochemical models are used to understand and quantify key biogeochemical processes in the ocean. The objective of the present study was to validate predictive ability of a regional configuration of the PISCES biogeochemical model on main biogeochemical variables in Humboldt Current Large Marine Ecosystem (HCLME). The statistical indicators used to evaluate the model were the bias, root-mean-square error, correlation coefficient and, graphically, the Taylor’s diagram. The results showed that the model reproduces the dynamics of the main biogeochemical variables (chlorophyll, dissolved oxygen and nutrients); in particular, the impact of El Niño 1997-1998 in the chlorophyll (decrease) and oxygen minimum zone depth (increase). However, it is necessary to carry out sensitivity studies of the PISCES model with different key parameters values to obtain a more accurate representation of the properties of the Ocean.

Los modelos biogeoquímicos en la actualidad son utilizados para entender y cuantificar los principales procesos biogeoquímicos que suceden en el océano. El objetivo del presente estudio es validar estadísticamente la habilidad predictiva de una simulación del modelo biogeoquímico PISCES en reproducir la dinámica de las principales variables biogeoquímicas del Ecosistema de la Corriente de Humboldt (ECH). Para evaluar el modelo se utilizaron indicadores estadísticos: sesgo, error de la raíz del cuadrado medio, coeficiente de correlación y gráficamente el diagrama de Taylor. Los resultados muestran que el modelo es capaz de reproducir la dinámica de las principales variables biogeoquímicas (clorofila, oxígeno disuelto y nutriente), captando bien el impacto que tiene El Niño 1997-1998 en la clorofila (disminución) y profundidad de la zona mínima de oxígeno (incremento). Es necesario llevar a cabo estudios de sensibilidad del modelo PISCES usando diferentes valores de los principales parámetros para obtener una mejor representación de las propiedades biogeoquímicas del océano.