Dinophysis spp. abundance and toxicity events in South Cornwall, U.K.: Interannual variability and environmental drivers at three coastal sites

Abstract. Understanding the response of forest net ecosystem productivity (NEP) to environmental drivers under climate change is highly relevant for predictions of annual forest carbon (C) flux budgets. Modeling annual forest NEP with soil–vegetation–atmosphere transfer models (SVATs), however, remains challenging due to unknown delayed responses to weather of the previous year. In this study, we addressed the influence of previous year's weather on the interannual variability of NEP for a subalpine spruce forest in Switzerland. Analysis of long-term (1997–2011) eddy covariance measurements showed that the Norway spruce forest Davos Seehornwald was a consistent sink for atmospheric CO2, sequestering 210 ± 88 g C m−2 yr−1 on average. Previous year's weather strongly affected interannual variability of NEP, increasing the explained variance in linear models to 53% compared to 20% without accounting for previous year's weather. Thus, our results highlight the need to consider previous year's weather in modeling annual C budgets of forests. Furthermore, soil temperature in the current year's spring played a major role controlling annual NEP, mainly by influencing gross primary productivity early in the year, with spring NEP accounting for 56% of annual NEP. Consequently, we expect an increase in net CO2 uptake with future climate warming, as long as no other resources become limiting.

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Process-based analysis of land carbon flux predictability

10.5194/egusphere-egu21-2093 ◽

2021 ◽

Author(s):

István Dunkl ◽

Aaron Spring ◽

Victor Brovkin

Keyword(s):

Soil Moisture ◽

Organic Carbon ◽

Soil Organic Carbon ◽

Interannual Variability ◽

Carbon Flux ◽

Carbon Fluxes ◽

Ecosystem Processes ◽

Environmental Drivers ◽

Terrestrial Carbon ◽

State Dependency

The land-atmosphere CO2 exchange exhibits a very high interannual variability which dominates variability in atmospheric CO2 concentration. Despite efforts to decrease the discrepancy between simulated and observed terrestrial carbon fluxes, the uncertainty in trends and patterns of the land carbon fluxes remains high. This difficulty raises the question to what extent the terrestrial carbon cycle is even predictable, and which processes explain the predictability. In this study, the perfect model approach is used to assess the potential predictability of net primary production (NPP) and heterotrophic respiration (Rh) by using initialized ensemble experiments simulated with the Max Planck Institute Earth System Model. In order to determine which processes are causing the derived predictability patterns, carbon flux predictability was decomposed into individual drivers. Regression analysis was used to determine the contribution of the predictability of different environmental drivers to the predictability of NPP and Rh (Soil moisture, temperature and radiation for NPP and soil organic carbon, temperature and precipitation for Rh). The main drivers of NPP predictability are soil moisture and temperature, while the predictability signal from radiation is lost after the first month of simulation. Rh predictability is predominantly driven by soil organic carbon, temperature and locally by precipitation. This decomposition of predictability shows that the relatively high Rh predictability is due to the generally high predictability of soil organic carbon. The assessed seasonality in predictability patterns can be explained by the change in limiting factors of NPP and Rh over the wet and dry months. This leads to the adjustment of carbon flux predictability to the predictability of the currently limiting environmental factor. Differences in the predictability between initializations can be attributed to the interannual variability in soil moisture and temperature predictability. This variability is caused by the state dependency of nonlinear ecosystem processes. These results reveal the crucial regions and ecosystem processes to be considered when initializing a carbon prediction system.

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Lingering Chukchi Sea sea ice and Chukchi Sea mean winds influence population age structure of euphausiids (krill) found in the bowhead whale feeding hotspot near Pt. Barrow, Alaska

PLoS ONE ◽

10.1371/journal.pone.0254418 ◽

2021 ◽

Vol 16 (7) ◽

pp. e0254418

Author(s):

Carin J. Ashjian ◽

Stephen R. Okkonen ◽

Robert G. Campbell ◽

Philip Alatalo

Keyword(s):

Population Structure ◽

Sea Ice ◽

Interannual Variability ◽

Chukchi Sea ◽

Late Spring ◽

Bowhead Whale ◽

Environmental Drivers ◽

Sea Ice Extent ◽

Krill Abundance ◽

Spring Sea Ice

Interannual variability in euphausiid (krill) abundance and population structure and associations of those measures with environmental drivers were investigated in an 11-year study conducted in late August–early September 2005–2015 in offshelf waters (bottom depth > 40 m) in Barrow Canyon and the Beaufort Sea just downstream of Distributed Biological Observatory site 5 (DBO5) near Pt. Barrow, Alaska. Statistically-significant positive correlations were observed among krill population structure (proportion of juveniles and adults), the volume of Late Season Melt Water (LMW), and late-spring Chukchi Sea sea ice extent. High proportions of juvenile and adult krill were seen in years with larger volumes of LMW and greater spring sea ice extents (2006, 2009, 2012–2014) while the converse, high proportions of furcilia, were seen in years with smaller volumes of LMW and lower spring sea ice extent (2005, 2007, 2010, 2011, 2015). These different life stage, sea ice and water mass regimes represent integrated advective responses to mean fall and/or spring Chukchi Sea winds, driven by prevailing atmospheric pressure distributions in the two sets of years. In years with high proportions of juveniles and adults, late-spring and preceding-fall winds were weak and variable while in years with high proportions of furcilia, late-spring and preceding-fall winds were strong, easterly and consistent. The interaction of krill life history with yearly differences in the northward transports of krill and water masses along with sea ice retreat determines the population structure of late-summer krill populations in the DBO5 region near Pt. Barrow. Years with higher proportions of mature krill may provide larger prey to the Pt. Barrow area bowhead whale prey hotspot. The characteristics of prey near Pt. Barrow is dependent on krill abundance and size, large-scale environmental forcing, and interannual variability in recruitment success of krill in the Bering Sea.

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