Proxy For Productivity Research Articles

Where Do Fires Burn More Intensely? Modeling and Mapping Maximum MODIS Fire Radiative Power from Aboveground Biomass by Fuel Type in Mexico

Mapping potential fire intensity is a fundamental tool for fire management planning. Despite the wide use of Fire Radiative Power (FRP) as an indicator of expected fire intensity and fire emissions, very few studies have spatially analyzed the role of remotely sensed proxies of vegetation productivity to explain FRP. The current study aimed at modeling and mapping the relationships between aboveground biomass and Moderate Resolution Imaging Spectroradiometer (MODIS) maximum FRP, at 1 km pixel, in 2011–2020, for each of 46 fuel regions in the entirety of Mexico. Maximum FRP–biomass relationships supported a novel hypothesis of varying constraints of fire intensity. In lower-productivity areas, such as semiarid shrub- and grass-dominated ecosystems, fine fuel loads limited fire occurrence and FRP was positively related to biomass. In the more productive areas, such as temperate or tropical forests, a humped relationship of FRP against biomass was observed, suggesting an intermediate-productivity hypothesis of maximum fire intensity within those regions. In those areas, the highest fire intensity was observed in the intermediate biomass areas, where surface (timber understory) and crown fuel availability, together with higher wind penetration, can result in crown fires. On the contrary, within the most productive areas, the lowest intensity occurred, likely due to weather and fuel (timber litter) limitations.

Unveiling the Role of Spatial Functional Trait Variations on Grassland Primary Productivity at France Scale

ABSTRACTAimLand surface models (LSMs) currently represent each plant functional type (PFT) as an average phenotype, characterised by a set of fixed parameters. This rigid and constant representation is a limit in understanding the dynamics of highly diverse ecosystems, such as permanent grasslands, and their response to global change.LocationFrance.Time Period2001–2019.Major TaxaGrassland plant species.MethodsWe incorporated spatially explicit trait variability at the France scale in the ORCHIDEE land surface model to assess how the net primary productivity (NPP) will spatially vary over the years. More precisely, we focused on three key functional traits that govern the NPP of grassland ecosystems: specific leaf area (SLA) and leaf nitrogen content (LNC), as measured traits, and leaf lifespan (LLS) as an estimated trait. Community‐weighted means (CWM) were implemented in various combinations with prescribed and spatially varying traits. We compared the outcomes of each NPP simulation to remotely sensed proxies of productivity by using the MODIS satellite‐driven NPP products.ResultsThe sensitivity of NPP to traits depends on climate conditions, such as temperature and water limitation. Considering trait variability decreases the NPP in the most productive regions (plains) and increases the NPP in the less productive regions (mountains) compared to the case with constant trait values. This leads to a more homogenous NPP across France. Compared to the observed MODIS NPP and FLUXCOM GPP, the simulation using varying traits improves the spatial NPP and GPP variations in several regions and most climate conditions.Main ConclusionsBased on the existing trait data, we revealed that incorporating the CWM of traits in an LSM such as ORCHIDEE can be effectively performed. Improving the modelling and predictions by considering the relationships between biodiversity, functional biogeography, and ecosystem functioning is essential in current and future ecological research.

Oceanic Tunnel Controls of Eastern Equatorial Pacific Surface Temperature and Productivity Over the Past 3.6 Myr

AbstractRobust modern gradients in sea surface temperature (SST) and biological productivity across the eastern equatorial Pacific (EEP) Ocean between 80° and 140°W derive from vigorous upwelling of cold and nutrient‐rich waters. However, during the mid‐Pliocene warm period (3.0–3.3 Ma), the zonal SST gradient within the EEP was reduced to <0.5°C while the productivity gradient remained as strong if not stronger than modern. We consider the oceanographic mechanisms and external climate forcings responsible for the evolution of the SST‐productivity coupling. We synthesize existing records and present new reconstructions of alkenone biomarker SST and productivity from four EEP sites. The progressive SST gradient strengthening over the Plio‐Pleistocene contrasted with the stronger Late Pliocene surface productivity gradient relative to modern. Dominance of the oceanic tunnel over surface forcings best explains these observations: SST changes reflect extratropical water masses cooling toward the present while productivity proxies suggest these waters became less nutrient‐rich.

Effect of the 2022 summer drought across forest types in Europe

Abstract. Forests in Europe experienced record-breaking dry conditions during the summer of 2022. The direction in which various forest types respond to climate extremes during their growing season is contingent upon an array of internal and external factors. These factors include the extent and severity of the extreme conditions and the tree ecophysiological characteristics adapted to environmental cues, which exhibit significant regional variations. In this study, we aimed to (1) quantify the extent and severity of the extreme soil and atmospheric dryness in 2022 in comparison to the two most extreme years in the past (2003 and 2018), (2) quantify the response of different forest types to atmospheric and soil dryness in terms of canopy browning and photosynthesis, and (3) relate the functional characteristics of the forests to the emerging responses observed remotely at the canopy level. For this purpose, we used spatial meteorological datasets between 2000 and 2022 to identify conditions with extreme soil and atmospheric dryness. We used the near-infrared reflectance of vegetation (NIRv), derived from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the global OCO-2 solar-induced fluorescence (GOSIF) as an observational proxy for ecosystem gross productivity to quantify the response of forests at the canopy level. In summer 2022, southern regions of Europe experienced exceptionally pronounced atmospheric and soil dryness. These extreme conditions resulted in a 30 % more widespread decline in GOSIF across forests compared to the drought of 2018 and 60 % more widespread decline compared to the drought of 2003. Although the atmospheric and soil drought scores were more extensive and severe (indicated by a larger observed maximum z score) in 2018 compared to 2022, the negative impact on forests, as indicated by declined GOSIF, was significantly larger in 2022. Different forest types were affected to varying degrees by the extreme conditions in 2022. Deciduous broadleaf forests were the most negatively impacted due to the extent and severity of the drought within their distribution range. In contrast, areas dominated by evergreen needleleaf forest (ENF) in northern Europe experienced a positive soil moisture (SM) anomaly and minimal negative vapour pressure deficit (VPD) in 2022. These conditions led to enhanced canopy greening and stronger solar-induced fluorescence (SIF) signals, benefiting from the warming. The higher degree of canopy damage in 2022, despite less extreme conditions, highlights the evident vulnerability of European forests to future droughts.

Reliable individual differences in researcher performance capacity estimates: evaluating productivity as explanatory variable

Are latent variables of researcher performance capacity merely elaborate proxies of productivity? To investigate this research question, we propose extensions of recently used item-response theory models for the estimation of researcher performance capacity. We argue that productivity should be considered as a potential explanatory variable of reliable individual differences between researchers. Thus, we extend the Conway-Maxwell Poisson counts model and a negative binomial counts model by incorporating productivity as a person-covariate. We estimated six different models: a model without productivity as item and person-covariate, a model with raw productivity as person-covariate, a model with log-productivity as person covariate, a model that treats log-productivity as a known offset, a model with item-specific influences of productivity, and a model with item-specific influences of productivity as well as academic age as person-covariate. We found that the model with item-specific influences of productivity fitted two samples of social science researchers best. In the first dataset, reliable individual differences decreased substantially from excellent reliability when productivity is not modeled at all to inacceptable levels of reliability when productivity is controlled as a person-covariate, while in the second dataset reliability decreased only negligibly. This all emphasizes the critical role of productivity in researcher performance capacity estimation.

Earnings development among new immigrants in Finland: does a native-born partner enhance economic integration?

Abstract Many studies have analysed the role of individual characteristics on the labour market outcomes of immigrants. However, there is only limited evidence on how an immigrant’s partnership status and intermarriage with a native-born person are associated with earnings development. Partnerships in general can be considered a proxy for social capital, productivity, and characteristics valued in the labour market. A partnership with a native person is also indicative of sociocultural resources, accomplished integration, and an intention to remain in the country as well as a possible reason for migration. Our study contributes to understanding the link between intermarriage and earnings with evidence from a Nordic perspective and based on unique register data spanning from 2004 to 2018. We employ growth curve models and analyse earnings and employment development in the years following entry to Finland among seven different immigrant groups and separately for men and women. The results demonstrate that the role of having a native-born partner varies according to the country of origin and gender. In general, those with a native-born partner upon arrival in Finland have a more positive earnings development over time. Long observation period is necessary to reveal ineteresting differences between groups.

Site index determination using a time series of airborne laser scanning data

Site index (SI) is determined from the top height development and is a proxy for forest productivity, defined as the expected top height for a given species at a certain index age. In Norway, an index age of 40 years is used. By using bi-temporal airborne laser scanning (ALS) data, SI can be determined using models estimated from SI observed on field plots (the direct approach) or from predicted top heights at two points in time (the height differential approach). Time series of ALS data may enhance SI determination compared to conventional methods used in operational forest inventory by providing more detailed information about the top height development. We used longitudinal data comprising spatially consistent field and ALS data collected from training plots in 1999, 2010, and 2022 to determine SI using the direct and height differential approaches using all combinations of years and performed an external validation. We also evaluated the use of data assimilation. Values of root mean square error obtained from external validation were in the ranges of 16.3%–21.4% and 12.8%–20.6% of the mean field-registered SI for the direct approach and the height differential approach, respectively. There were no statistically significant effects of time series length or the number of points in time on the obtained accuracies. Data assimilation did not result in any substantial improvement in the obtained accuracies. Although a time series of ALS data did not yield greater accuracies compared to using only two points in time, a larger proportion of the study area could be used in ALS-based determination of SI when a time series was available. This was because areas that were unsuitable for SI determination between two points in time could be subject to SI determination based on data from another part of the time series.

Atmospheric propane (C3H8) column retrievals from ground-based FTIR observations in Xianghe, China

Abstract. Propane (C3H8) is an important trace gas in the atmosphere, as it is a proxy for oil and gas production and has a significant impact on atmospheric chemical reactions related to the hydroxyl radical and tropospheric ozone formation. In this study, solar direct absorption spectra near 2967 cm−1 recorded by a ground-based Fourier transform infrared spectrometer (FTIR) were applied to retrieve C3H8 total columns between June 2018 and July 2022 in Xianghe in north China. The systematic and random uncertainties of the C3H8 column retrieval are estimated to be 18.4 % and 18.1 %, respectively. The mean and standard deviation of the C3H8 columns derived from the FTIR spectra in Xianghe are 1.80 ± 0.81 (1σ) × 1015 molec. cm−2. Good correlations are found between C3H8 and other non-methane hydrocarbons, such as C2H6 (R=0.84) and C2H2 (R=0.79), as well as between C3H8 and CO (R=0.72). However, the correlation between C3H8 and CH4 is relatively weak (R=0.45). Moreover, the FTIR C3H8 measurements in Xianghe are also compared against MkIV measurements at several sites around the world. The new FTIR measurements in Xianghe provide us with insight into C3H8 column variations and the underlying processes in north China.

Modeling regional forest site productivity accounting spatial structure in climatic and edaphic variables

With increasing interest in sustaining productivity amid changing climate, disturbance regimes, and management practices, an accurate forest productivity estimate is important to develop sustainable management regimes. Our goal was to estimate and map the potential productivity of co-occurring tree species. We used forest inventory and analysis (FIA) data and climatic and edaphic variables to model the composite site index (CSI) as a proxy of potential forest productivity. Initially, we identified the site index model for selected species: slash pine (Pinus elliottii), longleaf pine (Pinus palustris), loblolly pine (Pinus taeda), and yellow poplar (Liriodendron tulipifera). We then standardized species-specific site index (SI) values to generate composite site index (CSI) values. Finally, we used a random forest (RF) machine learning algorithm (ML) to predict CSI values based on climatic and edaphic factors while addressing spatial dependencies in the data set. The RF model explained 81 % of the variation (R2adj = 0.81), with a mean bias of 0.11 m and a mean absolute error (MAE) of 3.37 m. The accuracy of modeling and mapping forest productivity using CSI depends on the quality and spatial distribution of national forest inventory data at the species level and climatic information. We recommend modeling forest productivity that accounts for spatial structure in the data to reduce overinflation of overall accuracy.

Evaluating tree-ring proxies for representing the ecosystem productivity in India.

Terrestrial ecosystems are one of the major sinks of atmospheric CO2 and play a key role in climate change mitigation. Forest ecosystems offset nearly 25% of the global annual CO2 emissions, and a large part of this is stored in the aboveground woody biomass. Several studies have focused on understanding the carbon sequestration processes in forest ecosystems and their response to climate change using the eddy covariance (EC) technique and remotely sensed vegetation indices. However, very few of them address the linkage of tree-ring growth with the ecosystem-atmosphere carbon exchange, and nearly none have tested this linkage over a long-term (> 100 years) - limited by the short-term (< 50 years) availability of measured ecosystem carbon flux. Nevertheless, tree-ring indices can potentially act as proxies for ecosystem productivity. We utilise the Coupled Climate Carbon Cycle Model Intercomparison Project (C4MIP) model outputs for its 140-year-long simulated records of mean monthly gross primary productivity (GPP) and compare them with the tree-ring growth indices over the northwestern Himalayan region in India. In this study, we examine three coniferous tree species: Pinus roxburghii and Picea smithiana wall. Boiss and Cedrus deodara and find that the strength of the correlation between GPP and tree ring growth indices (RWI) varies among the species.

Firm heterogeneity and export behavior: evidence from Tunisia

ABSTRACT We use unique enterprise survey data to explore the export behavior of firms in Tunisia, a small, trade-dependent country with a complex policy environment regarding exporting. Firms may export directly or indirectly through intermediaries, and can also sell to ‘offshore’ firms, which are export manufacturing firms with special legal status. Firm size, a proxy for productivity, is strongly associated with exporting of either type as well as with sales to offshore firms. In contrast to some studies, exporting is not positively associated with firm age (i.e., experience). Domestic-owned firms are more likely to use intermediaries to export while foreign-owned firms as well as those with more educated managers are more likely to export directly. Multinomial logit results reject the hypothesis of progression from indirect exports through direct plus indirect exporting and then to direct-only exporting as firm size increases; instead, the largest exporting firms are more likely to combine direct and indirect exporting, possibly to reduce risk. The findings from this study – the first to examine the heterogeneity of exporting behavior in Tunisia – reveal a complex picture of such behavior and confirm the importance of trade intermediaries for less sophisticated firms (those with lower manager education and internet access), pointing to potential measures to encourage exporting among such enterprises. The findings also suggest that efforts to encourage exporting may also improve firms’ ability to sell to ‘offshore’ firms, enhancing the so far elusive linkages of that sector with the rest of the economy.

Wintertime productivity and carbon export potential across the Agulhas Current system

The Agulhas Current plays a major role in heat and salt exchange between the Indian and Atlantic Oceans, yet little is known of its influence on ocean fertility. To investigate carbon production and export potential in the Agulhas Current system, we measured net primary production (NPP), nitrate and ammonium uptake, N2 fixation, and nitrification along a transect of the current and adjacent subtropical subgyre (33.4°S–35.7°S) in winter when nutrient supply, and thus productivity, should be highest. Phytoplankton biomass was lowest in the current core, increasing into the subgyre as surface nitrate declined, and was dominated by nanoplankton (2.7–10 μm; 62 ± 5.1% of total biomass). NPP and nitrate uptake were generally high across the transect and increased from the current core into the subgyre; the rates were dominated by picoplankton (<2.7 μm; 53–93%) in the current core and nanoplankton elsewhere (63–69%). On average, euphotic zone nitrification supplied 7.6 ± 6.4% of the nitrate consumed by phytoplankton and N2 fixation was also low (2.1 ± 1.3% of new production); we thus consider nitrate uptake a reasonable proxy for new production, at least in winter. Nitrate uptake was highest at the southern edge of the current core, consistent with current-associated (sub)mesoscale mixing enhancing the upward nutrient supply. The fraction of NPP available for export (i.e., the f-ratio) was high across the transect, ranging from 0.44 to 0.69. Our data thus indicate that both total and new production are elevated across the Agulhas Current system in winter and suggest that the (sub)mesoscale dynamics associated with the current system may enhance carbon production and export in the otherwise oligotrophic southwest Indian Ocean.

Defining algal bloom phenology in Lake Erie

Elucidating the impact of global climate change on aquatic ecosystems, particularly through phenological shifts in primary producers, is critical for understanding ecological resilience. Here, we focus on the phenological shifts in chlorophyll as a proxy for algae biomass and primary production in aquatic ecosystems, specifically in Lake Erie as well as concentrations of the toxin microcystin. By tracking temporal changes in each, we identified key phenological phases important to estimate duration, magnitude, and intensity of harmful algal blooms (HABs). Determining which influential biotic and abiotic factors such as temperature, wind speed, nutrient availability, and climate change is most important, is a long-term management need for Lake Erie, which can be explored using our methodology. Our novel statistical framework employing Bayesian generalized additive mixed models described seasonal chlorophyll and particulate microcystin concentration from Lake Erie and our simple geometric method identified the start, peak, and end of algal blooms. This research enhances our understanding of the ecological effects of nutrient pollution on aquatic ecosystems and provides a repeatable method for determining phenological events without the need for user defined cutoffs which aids in the management and mitigation of HABs, safeguarding water quality in regions dependent on lakes for drinking water.

Productivity experienced a more rapid enhancement trend than greenness across the Tibetan Plateau

Satellite-derived products and field measurements verify that Tibetan Plateau (TP) has been experiencing continuous vegetation greening and productivity increase; however, it remains unclear how this greening translates into productivity and how long-term productivity variations depend on greenness across the TP. Moreover, ignoring the accuracy evaluation of satellite-derived greenness and productivity products may mislead the understanding of TP vegetation changes. Thus, we initially assessed the accuracy of three widely used leaf area index (LAI, proxy of greenness) products (i.e., MODIS, GLASS and GEOV2 LAI) and three gross primary productivity (GPP, proxy of productivity) products (i.e., MODIS, GLASS and PML-V2 GPP) to selected robust products to represent greenness and productivity respectively. Then, we explored the dependence of spatiotemporal GPP dynamics on greenness variations during 2000–2020. Results indicated that PML-V2 GPP and MODIS LAI were more robust and reliable than other satellite-derived products when compared to the reference values. They revealed a prevailing increase in GPP over the past two decades, with a regional average of 71 % higher than that of LAI. Notably, the area proportion of significant productivity enhancement was 31.6 % higher than that of significant greening. About 24.7 % of the TP displayed significantly inconsistent trends. The dependency of GPP on LAI gradually decreased with the increasing water availability, the complexity of vegetation structures, and dense canopy community. By calculating leaf photosynthetic capacity, we found that this indicator greatly regulated the velocity discrepancy between GPP and LAI, and the contribution of only greening to productivity is limited, only occupying 11.9 % of the TP, which was helpful in understanding the inter-annual changes of vegetation dynamics under varying environment conditions. We therefore reveal an unexpected rapid increase in productivity than greening during 2000–2020 on the TP, as well as highlight the caution of only using satellite-derived greenness indicators for assessing long-term changes in vegetation productivity dynamics, especially over mesic ecosystems with complex vegetation structures and dense canopies of TP.

Sulfur isotopic fractionation during hydrolysis of carbonyl sulfide

Carbonyl Sulfide (OCS) is the most abundant sulfur-containing gas in the atmosphere, and it is used as a proxy for terrestrial gross primary productivity (GPP). Oceans are the major source of OCS to the atmosphere, produced by photochemical and “dark” reactions. Hydrolysis to H2S and CO2 is the major removal process of OCS from the ocean's surface. Measuring the sulfur isotope values (δ34S) and the isotopic fractionation (ε) associated with these major OCS sources and sinks could decrease the uncertainties in its fluxes. In the current study, we aim to determine the ε during the hydrolysis process of OCS (εh). We used a purge and trap system coupled to a GC/MC-ICPMS to measure δ34S values during hydrolysis under different temperatures (4–40 °C), salinities (0.2–40 g/L), and pH (4–9), representing various natural environmental conditions. In addition, we use the quantum chemical method to calculate the equilibrium εh and compare it to the empirical results. Our results for the low salinity (S =0.2 g/L; pH 8.0) water show a temperature dependency of the εh from −3.9 ‰ ± 0.2 ‰ (4 °C,) to −2.2 ± 0.6 ‰ (40 °C). The higher fractionation at low temperatures has implication for ice-core data interpretation. However, in natural seawater at 4°C and 22 °C (S = 40 g/L, pH 8.2) there was no such temperature dependency and the εh averaged −2.6 ± 0.3 ‰. Thus, it seems that salinity cancels the temperature effect close to the freezing temperature of water. Varying the pH between 4 and 9 (at 22 °C) did not result in any εh trend. Ab-initio calculations suggest that OCS hydrolysis is not controlled by equilibrium. The εh values we report will aid in quantifying the impact of OCS's hydrolysis on the observable sulfur isotopic signature of OCS in oceanic and in freshwater environments. This in turn will facilitate more accurate mass-balance calculations for the OCS budget from the ocean to the atmosphere.

Silica spherules in Late Pleistocene‑Holocene glaciomarine sediments from the Ross Sea, Antarctica: insights into the formation and significance

In this study, we investigate silica spherules with a diameter &lt;1.25 mm from sediment cores retrieved from the northern Drygalski Trough, during the Italian Antarctic Research Programme (PNRA) expeditions in 1999 and 2002. In the past, these unique spherules have been a subject of interest due to their distinctive characteristics. Despite previous hypotheses on their origin, a comprehensive discussion on their formation mechanism and implications in marine sediments was lacking. Our analysis encompasses the depositional environment, morphology, internal texture, major element composition, and age determination through radiocarbon dating (14C) and 40Ar‑39Ar dating of spherule-containing sediments. By integrating our findings with a critical review of existing literature, we propose that spherules form by cyclical chemical precipitation of silica when silica‑rich freshwater mixed with seawater during extensive events of ice melting. We also tentatively suggest that these spherules possibly represent a proxy for significant meltwater production and discharge into the Antarctic Ocean. This research contributes to a better understanding of silica spherules in polar marine environments and their implications for past climate conditions.

Resource selection at fine scale: what drives the decision of a generalist herbivore?

Abstract Spatial patterns in topography and forage distribution significantly influence the movements and choices of large herbivores. However, understanding the foraging strategies of free-grazing herbivores at different temporal and spatial scales remains limited, as different behavioral decisions can apply at different hierarchical levels. This study investigates the fine-scale foraging strategies of the Plains Zebra (Equus quagga) in a South African savanna, with a specific focus on their selection of green vegetation at the plant and feeding patch levels. We used the Normalized Difference Vegetation Index as a proxy for vegetation productivity and quality. Our findings reveal that zebras adapted their foraging strategies according to scale and season. During the late-dry season and early-wet season, selection for greenness was at both the grass tuft and feeding site levels. In contrast, during the mid-dry season, selection was predominantly at the tuft level, focusing solely on greenness. These insights emphasize the importance of conducting multilevel studies when investigating factors influencing foraging decisions. Findings at 1 hierarchical level may not necessarily apply across other levels of investigation, highlighting the need for a nuanced and comprehensive approach to understanding the complex foraging behaviors of animals.

Arctic Alaska deepwater organic carbon burial and environmental changes during the late Albian–early Campanian (103–82 Ma)

The middle Cretaceous greenhouse period experienced profound environmental change including episodes of enhanced global burial of organic carbon marked by carbon isotopic excursions (CIEs). However, the role and response of polar regions like the newly formed, partially enclosed Arctic Ocean Basin during middle Cretaceous carbon burial remains enigmatic. We present the first Arctic deepwater CIE record that characterizes conditions offshore of the Alaska margin north of 75°N paleolatitude. Organic carbon isotopes (δ13Corg) and 103–82 Ma ash zircon U-Pb dates from the distal Hue Shale record multiple Albian–Campanian CIEs during slow ∼3–15 m/Myr sediment accumulation rates. Average total organic carbon (TOC) increased substantially during large 2–3 ‰ CIEs of the ∼101 Ma Albian-Cenomanian boundary event (from 7 to 18 % TOC) and ∼94 Ma Cenomanian-Turonian boundary event (5 to 10 % TOC). Turonian TOC remained elevated (8–13 %) during high global sea levels and temperatures of the Cretaceous Thermal Maximum, followed by an increase from 7 to 11 % TOC during the ∼90 Ma late Turonian event 1.5 ‰ CIE. Average TOC subsequently decreased in the Coniacian–Campanian, but relative maxima occurred during subtle 0.5–1 ‰ CIEs interpreted as the ∼87 Ma late Coniacian event (increase from 4 to 7 % TOC), ∼85 Ma Horseshoe Bay event (3.5 to 4.5 % TOC), and ∼84 Ma Santonian-Campanian boundary event (3.5 to 5 % TOC). Increases in hydrogen index and productivity proxies (P, Ba, Nd) that accompanied each CIE episode with enhanced TOC suggest a strong link between marine productivity and organic carbon burial at short-term CIE timescales. However, long-term (>5–8 Myr) changes in trace metal redox (Mo, Fe, V) and salinity (B/Ga) proxies suggest shifts in prevailing environmental conditions at timescales longer than the CIEs. Late Albian–middle Turonian marine salinity occurred during euxinic (103–98 Ma) and suboxic (98–90 Ma) conditions with deposition interpreted to have occurred within and beneath an oxygen minimum zone, respectively. In contrast, late Turonian–early Campanian (90–82 Ma) freshening and restricted euxinic basin conditions may signal the start of widespread restriction known to characterize the Paleogene Arctic. Overall, these results highlight that middle Cretaceous Arctic deepwater remained a productive marine carbon sink coupled to the global carbon cycle despite evolving Arctic greenhouse conditions.

Key benthic species are affected by predicted warming in winter but show resistance to ocean acidification.

The effects of climate change on coastal biodiversity are a major concern because altered community compositions may change associated rates of ecosystem functioning and services. Whilst responses of single species or taxa have been studied extensively, it remains challenging to estimate responses to climate change across different levels of biological organisation. Studies that consider the effects of moderate realistic near-future levels of ocean warming and acidification are needed to identify and quantify the gradual responses of species to change. Also, studies including different levels of biological complexity may reveal opportunities for amelioration or facilitation under changing environmental conditions. To test experimentally for independent and combined effects of predicted near-future warming and acidification on key benthic species, we manipulated three levels of temperature (winter ambient, +0.8 and +2°C) and two levels of pco 2 (ambient at 450 ppm and elevated at 645 ppm) and quantified their effects on mussels and algae growing separately and together (to also test for inter-specific interactions). Warming increased mussel clearance and mortality rates simultaneously, which meant that total biomass peaked at +0.8°C. Surprisingly, however, no effects of elevated pco 2 were identified on mussels or algae. Moreover, when kept together, mussels and algae had mutually positive effects on each other's performance (i.e. mussel survival and condition index, mussel and algal biomass and proxies for algal productivity including relative maximum electron transport rate [rETRmax], saturating light intensity [I k] and maximum quantum yield [F v/F m]), independent of warming and acidification. Our results show that even moderate warming affected the functioning of key benthic species, and we identified a level of resistance to predicted ocean acidification. Importantly, we show that the presence of a second functional group enhanced the functioning of both groups (mussels and algae), independent of changing environmental conditions, which highlights the ecological and potential economic benefits of conserving biodiversity in marine ecosystems.

Analysis of the latitudinal and longitudinal (coastal and pelagic zones) variability of coccolithophore assemblages in the water column of the Western Iberian Margin in late summer of 2022

This study investigates the abundance, composition, and biogeographical distribution of coccolithophores in the water column of the northwestern Iberian coastal upwelling system during late summer 2022. Coccolithophore data were compared with in situ measurements of physical, chemical, and biological parameters, as well as with satellite data and the upwelling index (UI) for the study area. Canonical Correspondence Analysis (CCA) was performed to determine the relationships between coccolithophore assemblages and environmental variables. The results reveal a latitudinal and longitudinal gradient in coccolithophore abundance, with higher concentrations towards the north and east, indicating a stronger influence of coastal upwelling near the coast (stations CA-7, CA-8, CA-4). Our data suggest that the source of upwelled water in the north (Eastern North Atlantic Central Waters of subpolar origin, ENACWsp) differs from that in the south (ENACWst, of subtropical origin). Significant correlations between UI and the total abundance of coccoliths and coccospheres underscore the role of upwelling in coccolithophore distribution. Additionally, correlations with fluorescence and turbidity indicate that coccolithophores contribute substantially to primary production in the region. Certain species are proposed as paleoenvironmental indicators due to their affinity for specific environmental conditions. The small Noëlaerhabdaceae group (small Gephyrocapsa group + Emiliania huxleyi) serves as a proxy for primary productivity and intense upwelling, while Florisphaera profunda is associated with upwelling relaxation and low productivity. Discrepancies with satellite data are attributed to their limitations in detecting subsurface biological processes. This study also supports the use of the N-ratio in water column samples, not just in sediments, and improves the understanding of primary productivity at the Western Iberian Margin during the upwelling season.