Patterns Of Primary Production Research Articles

Mapping the Leaf Economic Spectrum across West African Tropical Forests Using UAV-Acquired Hyperspectral Imagery

The leaf economic spectrum (LES) describes a set of universal trade-offs between leaf mass per area (LMA), leaf nitrogen (N), leaf phosphorus (P) and leaf photosynthesis that influence patterns of primary productivity and nutrient cycling. Many questions regarding vegetation-climate feedbacks can be addressed with a better understanding of LES traits and their controls. Remote sensing offers enormous potential for generating large-scale LES trait data. Yet so far, canopy studies have been limited to imaging spectrometers onboard aircraft, which are rare, expensive to deploy and lack fine-scale resolution. In this study, we measured VNIR (visible-near infrared (400–1050 nm)) reflectance of individual sun and shade leaves in 7 one-ha tropical forest plots located along a 1200–2000 mm precipitation gradient in West Africa. We collected hyperspectral imaging data from 3 of the 7 plots, using an octocopter-based unmanned aerial vehicle (UAV), mounted with a hyperspectral mapping system (450–950 nm, 9 nm FWHM). Using partial least squares regression (PLSR), we found that the spectra of individual sun leaves demonstrated significant (p < 0.01) correlations with LMA and leaf chemical traits: r2 = 0.42 (LMA), r2 = 0.43 (N), r2 = 0.21 (P), r2 = 0.20 (leaf potassium (K)), r2 = 0.23 (leaf calcium (Ca)) and r2 = 0.14 (leaf magnesium (Mg)). Shade leaf spectra displayed stronger relationships with all leaf traits. At the airborne level, four of the six leaf traits demonstrated weak (p < 0.10) correlations with the UAV-collected spectra of 58 tree crowns: r2 = 0.25 (LMA), r2 = 0.22 (N), r2 = 0.22 (P), and r2 = 0.25 (Ca). From the airborne imaging data, we used LMA, N and P values to map the LES across the three plots, revealing precipitation and substrate as co-dominant drivers of trait distributions and relationships. Positive N-P correlations and LMA-P anticorrelations followed typical LES theory, but we found no classic trade-offs between LMA and N. Overall, this study demonstrates the application of UAVs to generating LES information and advancing the study and monitoring tropical forest functional diversity.

Seasonal patterns of thermal stratification and primary production in the northern parts of Lake Tanganyika

Abstract Thermal stratification in meromictic Lake Tanganyika weakens during the cool, dry and windy season, allowing intrusions of deeper nutrient-rich waters into the upper mixed layer enhancing primary productivity. The current study examined the seasonal influence of thermal structure on the patterns of primary production in Lake Tanganyika. Two sites (Kigoma Bay and Mahale) were sampled on a monthly basis for 1 year. Water temperature and chlorophyll a fluorescence profiles (0–100 m) were measured using a multisonde. Water samples were taken every 20 m (0–100 m) to measure soluble reactive phosphorus (SRP), chlorophyll a and primary production. Pulse Amplitude Modulated Fluorometry was used for the measurements of primary production. The results show that the dry season coincided with higher wind speeds, elevated SRP and some peaks of chlorophyll a and primary production at both sites. During the wet season, high levels of chlorophyll a and primary production coincided with an increase in the euphotic depth, a deep chlorophyll maximum (DCM) and a contribution from metalimnetic areal production at both sites. Our results suggest that the vertical distribution of primary production in Lake Tanganyika is affected by the lake thermal structure, nutrient availability and the extent of the euphotic zone. In Lake Tanganyika, estimates of areal primary production were significantly affected by DCM and required estimation throughout the entire upper mixed layer and the metalimnion which extended to ~89 m.

Global patterns in above-ground net primary production and precipitation-use efficiency in grasslands

The above-ground net primary production (ANPP) and the precipitation-use efficiency (PUE) regulate the carbon and water cycles in grassland ecosystems, but the relationships among the ANPP, PUE and precipitation are still controversial. We selected 717 grassland sites with ANPP and mean annual precipitation (MAP) data from 40 publications to characterize the relationships ANPP-MAP and PUE-MAP across different grassland types. The MAP and ANPP showed large variations across all grassland types, ranging from 69 to 2335 mm and 4.3 to 1706 g m(-2), respectively. The global maximum PUE ranged from 0.19 to 1.49 g m(-2) mm(-1) with a unimodal pattern. Analysis using the sigmoid function explained the ANPP-MAP relationship best at the global scale. The gradient of the ANPP-MAP graph was small for arid and semi-arid sites (MAP < 400 mm). This study improves our understanding of the relationship between ANPP and MAP across dry grassland ecosystems. It provides new perspectives on the prediction and modeling of variations in the ANPP for different grassland types along precipitation gradients.

Spatial distribution patterns of phytoplankton biomass and primary productivity in six coral atolls in the central South China Sea

Nutrients’ concentration, phytoplankton biomass, and primary productivity were investigated in six coral atolls in the central South China Sea during the southwest monsoon in the early summer. Nutrients’ concentrations were generally very low in these atolls, and showed no obvious variation among outer reef slope, reef flat, and lagoon. The spatial variation of phytoplankton biomass and primary productivity were significant among the different regions of the atolls, and generally followed the order of outer reef slope < reef flat < lagoon. Phytoplankton biomass might be a more sensitive indicator than nutrients for the habitat differences in coral atoll ecosystem. The lagoon of Huangyan Atoll showed the highest phytoplankton biomass and primary productivity. The phytoplankton biomass and primary productivity were mainly contributed by pico-phytoplankton. Moreover, our results suggested that there might have a threshold value of Chl a for pico-phytoplankton abundance. When Chl a was higher than this threshold value (about 0.5 µg L−1), the pico-phytoplankton abundance should not linearly increase with the Chl a concentration. Due to the significantly high-phytoplankton biomass and primary productivity, the anthropogenic eutrophication should be paid attention in the lagoon of Huangyan Atoll.

Spatial pattern of GPP variations in terrestrial ecosystems and its drivers: Climatic factors, CO2 concentration and land-cover change, 1982–2015

Quantitative estimation of spatial pattern of gross primary production (GPP) trends and its drivers plays a crucial role in global change research. This study applied C-Fix model to estimate the net effect of each factor on GPP trends of 1982–2015, used an unsupervised classifier to group similar GPP trend behaviors, and analyzed the responses of GPP to changes in climatic, atmospheric and environmental drivers. According to the features of monthly GPP trends and the patterns of growing season, we presented nine categories as aids in interpreting large-scale behavior. Land-cover change (LCC), rising CO2, temperature and water conditions changes have the positive overall effect on GPP over the entire world, contrary to radiation change effects. The global average contributions of LCC, CO2, temperature, radiation and water on GPP trend are 4.57%, 65.73%, 13.07%, −7.24 and 11.74%, respectively. LCC and climatic factors changes have had a greater impact on GPP in terms of a specific location or regional rather than globally, and the interactions between factors are positive on GPP. The effects of climatic factors trends on GPP in different locations can be opposite, in general: regionally, GPP changes at middle and high latitudes are likely dominated by rises in radiation and temperature; at lower latitudes, GPP changes are likely to be driven by shifts in water conditions; at high altitudes, GPP changes are probably caused by changes in temperature and water conditions. These results will increase the understanding of the variations of carbon flux under future CO2, LCC and climate conditions.

Temporal Variability of MODIS Phenological Indices in the Temperate Rainforest of Northern Patagonia

Western Patagonia harbors unique and sparsely studied terrestrial ecosystems that are threatened by land use changes and exposure to basin-scale climatic variability. We assessed the performance of two satellite vegetation indices derived from MODIS–Terra, EVI (Enhanced Vegetation Index) and NDVI (Normalized Difference Vegetation Index), over the northern and southern sectors of the Chiloé Island System (CIS) to advance our understanding of vegetation dynamics in the region. Then we examined their time-varying relationships with two climatic indices indicative of tropical and extratropical influence, the ENSO (El Niño–Southern Oscillation) and the Antarctic Oscillation (AAO) index, respectively. The 17-year time series showed that only EVI captured the seasonal pattern characteristic of temperate regions, with low (high) phenological activity during Autumn-Winter (Spring–Summer). NDVI saturated during the season of high productivity and failed to capture the seasonal cycle. Temporal patterns in productivity showed a weakened seasonal cycle during the past decade, particularly over the northern sector. We observed a non-stationary association between EVI and both climatic indices. Significant co-variation between EVI and the Niño–Southern Oscillation index in the annual band persisted from 2001 until 2008–2009; annual coherence with AAO prevailed from 2013 onwards and the 2009–2012 period was characterized by coherence between EVI and both climate indices over longer temporal scales. Our results suggest that the influence of large-scale climatic variability on local weather patterns drives phenological responses in the northern and southern regions of the CIS. The imprint of climatic variability on patterns of primary production across the CIS may be underpinned by spatial differences in the anthropogenic modification of this ecosystem, as the northern sector is strongly modified by forestry and agriculture. We highlight the need for field validation of satellite indices around areas of high biomass and high endemism, located in the southern sector of the island, in order to enhance the utility of satellite vegetation indices in the conservation and management of austral ecosystems.

Seasonal patterns in phytoplankton biomass across the northern and deep Gulf of Mexico: a numerical model study

Abstract. Biogeochemical models that simulate realistic lower-trophic-level dynamics, including the representation of main phytoplankton and zooplankton functional groups, are valuable tools for improving our understanding of natural and anthropogenic disturbances in marine ecosystems. Previous three-dimensional biogeochemical modeling studies in the northern and deep Gulf of Mexico (GoM) have used only one phytoplankton and one zooplankton type. To advance our modeling capability of the GoM ecosystem and to investigate the dominant spatial and seasonal patterns of phytoplankton biomass, we configured a 13-component biogeochemical model that explicitly represents nanophytoplankton, diatoms, micro-, and mesozooplankton. Our model outputs compare reasonably well with observed patterns in chlorophyll, primary production, and nutrients over the Louisiana–Texas shelf and deep GoM region. Our model suggests silica limitation of diatom growth in the deep GoM during winter and near the Mississippi delta during spring. Model nanophytoplankton growth is weakly nutrient limited in the Mississippi delta year-round and strongly nutrient limited in the deep GoM during summer. Our examination of primary production and net phytoplankton growth from the model indicates that the biomass losses, mainly due to zooplankton grazing, play an important role in modulating the simulated seasonal biomass patterns of nanophytoplankton and diatoms. Our analysis further shows that the dominant physical process influencing the local rate of change of model phytoplankton is horizontal advection in the northern shelf and vertical mixing in the deep GoM. This study highlights the need for an integrated analysis of biologically and physically driven biomass fluxes to better understand phytoplankton biomass phenologies in the GoM.

Allometric scaling of estuarine ecosystem metabolism

There are still significant uncertainties in the magnitude and direction of carbon fluxes through coastal ecosystems. An important component of these biogeochemical budgets is ecosystem metabolism, the net result of organismal metabolic processes within an ecosystem. In this paper, I present a synthesis of published ecosystem metabolism studies from coastal ecosystems and describe an empirical observation that size-dependent patterns in aquatic gross primary production and community respiration exist across a wide range of coastal geomorphologies. Ecosystem metabolism scales to the 3/4 power with volume in deeper estuaries dominated by pelagic primary production and nearly linearly with area in shallow estuaries dominated by benthic primary production. These results can be explained by applying scaling arguments for efficient, directed transport networks developed to explain similar size-dependent patterns in organismal metabolism. The main conclusion from this synthesis is that the residence time of new, nutrient-rich water is a fundamental organizing principle for the observed patterns. Residence time changes allometrically with size in pelagic ecosystems because velocities change by only an order of magnitude across systems that span more than ten orders of magnitude in size. This nonisometric change in velocity with size requires lower specific metabolic rates at larger ecosystem sizes. This change in transport may also explain a shift from predominantly net heterotrophy to net autotrophy with increasing size. The scaling results are applied to the total estuarine area in the continental United States to estimate the contribution of estuarine systems to the overall coastal budget of organic carbon.

Spatial-temporal consistency between gross primary productivity and solar-induced chlorophyll fluorescence of vegetation in China during 2007–2014

Accurately estimating spatial-temporal patterns of gross primary production (GPP) is important for the global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatial-temporal dynamics of GPP. However, the accuracy assessment of GPP simulations from LUE models at both spatial and temporal scales remains a challenge. In this study, we simulated GPP of vegetation in China during 2007–2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images with 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPPVPM) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPPVPM and SIF data over a single year (2010) and multiple years (2007–2014) in most areas of China. GPPVPM is also significantly positive correlated with GOME-2 SIF (R2 > 0.43) spatially for seasonal scales. However, poor consistency was detected between GPPVPM and SIF data at yearly scale. GPP dynamic trends have high spatial-temporal variation in China during 2007–2014. Temperature, leaf area index (LAI), and precipitation are the most important factors influence GPPVPM in the regions of East Qinghai-Tibet Plateau, Loss Plateau, and Southwestern China, respectively. The results of this study indicate that GPPVPM is temporally and spatially in line with GOME-2 SIF data, and space-borne SIF data have great potential for evaluating LUE-based GPP models.

Primary productivity in the Gulf of Riga (Baltic Sea) in relation to phytoplankton species and nutrient variability

Summary The seasonal patterns of primary production, phytoplankton biomass, chlorophyll a, and nutrients were investigated in the central part of the Gulf of Riga (Baltic Sea) during 2011 and 2012. Annual primary productivity in the gulf was in the range of 353.4–376.2 gC m−2. Maximum carbon fixation rates occurred during the phytoplankton spring bloom from April to May when the winter nutrient pool was rapidly exhausted, suggesting the use of regenerated nutrients already in spring. The new production calculated on the draw-down of nitrates amounted to 51.80% of spring net community production. The production rates during summer were considerably lower owing to the availability of only regenerated nutrients and limited nitrogen fixation. Autumn was established as the least productive season. In autumn despite the elevated nutrient concentrations, the increasingly limited light hindered photosynthetic activity. Species governing the nutrient fluxes and the productivity of the Gulf of Riga are the diatom species responsible for new production in spring. The photosynthetic ciliate Mesodinium rubrum ((Lohmann) Hamburger & Buddenbrock 1911) prevailed in all seasons and significantly correlated with elevated productivity, while diazotrophic cyanobacteria Aphanizomenon flosaquae (Ralfs ex Bornet & Flahault 1886) contributed to new production in the summer nutrient regenerating system.

Fish movement drives spatial and temporal patterns of nutrient provisioning on coral reef patches

AbstractNutrient provisioning by animals can be a major driver of primary productivity in ecosystems. Animal‐mediated nutrient sources are particularly important in nutrient‐poor systems such as coral reefs. However, aggregations of mobile animals might lead to temporal and spatial variability in local nutrient availability, which is not well understood. In this study, we quantified how patterns of fish movement and abundance influence the stability of nitrogen provisioning on Bahamian coral reefs. We empirically measured and modeled nitrogen excretion estimates for 16 coral reef fish communities and combined these measurements with fish abundance and behavioral observations to compare reef nutrient budgets on diel, monthly, and annual time scales. Diel reef nitrogen provisioning by fishes varied greatly, with diurnal rates being on average four times greater than nocturnal rates. Diurnal rates were highly variable among reefs and were driven primarily by migratory grunts (Haemulidae) resting over reefs during the day but foraging off reefs at night. At the reef scale, overall nitrogen excretion rates were correlated with grunt abundance; however, grunt abundance could not be predicted by any reef physical characteristics. Within‐reef grunt excretion rates changed little across a 4‐month period but varied significantly over two years, indicating that nutrient supply on a patch reef is not stable over long periods of time. Quantifying how nutrient provisioning on patch reefs is linked to fish activity and movement patterns and how provisioning varies on different spatial and temporal scales is important for understanding overall patterns of primary productivity on reefs.

Possible patterns of marine primary productivity during the Great Ordovician Biodiversification Event

Following the appearance of numerous animal phyla during the ‘Cambrian Explosion’, the ‘Great Ordovician Biodiversification Event’ (GOBE) records their rapid diversification at the lower taxonomic levels, constituting the most significant rise in biodiversity in Earth's history. Recent studies suggest that the rapid rise in phytoplankton diversity observed at the Cambrian–Ordovician boundary may have profoundly restructured marine trophic chains, paving the way for the subsequent flourishing of plankton-feeding groups during the Ordovician. Unfortunately, the fossil record of plankton is incomplete. Its smaller members represent the bulk of the modern marine biomass, but they are usually not documented in Palaeozoic sediments, preventing any definitive assumption with regard to an eventual correlation between biodiversity and biomass at that time. Here, we use an up-to-date ocean general circulation model with biogeochemical capabilities (MITgcm) to simulate the spatial patterns of marine primary productivity throughout the Ordovician, and we compare the model output with available palaeontological and sedimentological data.

Assessment of Everglades mangrove forest resilience: Implications for above-ground net primary productivity and carbon dynamics

We evaluated mangrove forest resilience in the Florida Coastal Everglades (FCE) by analyzing long-term (2001–2014) spatial and temporal patterns of litterfall net primary productivity (NPPL), including the impact and recovery from two natural disturbance events: Hurricane Wilma (October-2005) and a cold snap (January-2010). Specifically, we tested whether the disturbance driven recovery trajectory of mangrove forests (i.e. recovery duration and rate) depends on the disturbance impact magnitude and initial forest structure in three study sites. Hurricane Wilma caused canopy defoliation at all sites and was a function of the wind-field strength such that higher wind speeds at the SRS-6 site (30–40ms−1) induced greatest defoliation (4.7MgCha−1yr−1). Disturbance magnitude (decrease in NPPL from 2005 to 2006) was higher in SRS-6 (7.8MgCha−1yr−1), followed by SRS-4 (5.7MgCha−1yr−1) and SRS-5 (5.5MgCha−1yr−1). We observed differential NPPL recovery times among sites and species, where sites SRS-5 and SRS-6 returned to pre-Wilma NPPL rates by 2010 while SRS-4 has not yet fully recovered. In contrast, the cold snap had significant disturbance impact, yet recovery occurred within one month across all sites. We conclude that differential resilience to Hurricane Wilma was a result of a synergy of local changes in hydrology, salinity and storm impact. The long-term ability of subtropical mangroves to recover to pre-disturbance production rates within a short period (<5years) demonstrates their resilience capacity in cases where massive defoliation occurs as result of natural disturbances.

Determinants of arctic-alpine pasture resources: the need for a spatially and functionally fine-scaled perspective

ABSTRACTThe current greening of arctic-alpine landscapes poses the question about its underlying ecological mechanisms. Given its importance across various contexts and scales, it is vital to understand the drivers of contemporary patterns in phytomass and primary productivity to improve predictions under altered environmental conditions. Here, we analysed local patterns in above-ground phytomass, calorific energy contents, and primary productivity as important pasture resources in a complex arctic-alpine landscape along pronounced micro-topographical and elevational gradients. Using data from 110 sampling sites, of which 38 were equipped with on-site recordings of soil moisture and near-surface temperatures, we asked how the observed patterns in pasture resources are related to the environment and whether commonly used structural proxies or physiologically relevant, functional data were better suited for their explanation. Using partial least squares regression based on a set of structural plus functional explanatory variables, the latter revealed to be the best determinants. Our results suggest how the ecological mechanisms behind contemporary pasture resources and, likewise, the arctic-alpine greening are interactively driven by the near-surface thermal regime, associated snow coverage, and soil moisture availability. Moreover, they reveal an obvious decoupling of near-surface processes from the overall atmospheric and topographic constraints which are commonly used as proxies. We conclude that estimates of current and future pasture resources would be significantly improved if fine-scaled, functional data, rather than structural data, could be used. However, this implies further effort in providing such data, since appropriate regionalization techniques are still lacking.

Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years.

The uncertainties of China's gross primary productivity (GPP) estimates by global data-oriented products and ecosystem models justify a development of high-resolution data-oriented GPP dataset over China. We applied a machine learning algorithm developing a new GPP dataset for China with 0.1° spatial resolution and monthly temporal frequency based on eddy flux measurements from 40 sites in China and surrounding countries, most of which have not been explored in previous global GPP datasets. According to our estimates, mean annual GPP over China is 6.62±0.23PgC/year during 1982-2015 with a clear gradient from southeast to northwest. The trend of GPP estimated by this study (0.020±0.002PgC/year2 from 1982 to 2015) is almost two times of that estimated by the previous global dataset. The GPP increment is widely spread with 60% area showing significant increasing trend (p<.05), except for Inner Mongolia. Most ecosystem models overestimated the GPP magnitudes but underestimated the temporal trend of GPP. The monsoon affected eastern China, in particular the area surrounding Qinling Mountain, seems having larger contribution to interannual variability (IAV) of China's GPP than the semiarid northwestern China and Tibetan Plateau. At country scale, temperature is the dominant climatic driver for IAV of GPP. The area where IAV of GPP dominated by temperature is about 42%, while precipitation and solar radiation dominate 31% and 27% respectively over semiarid area and cold-wet area. Such spatial pattern was generally consistent with global GPP dataset, except over the Tibetan Plateau and northeastern forests, but not captured by most ecosystem models, highlighting future research needs to improve the modeling of ecosystem response to climate variations.

Benthic macroinfaunal community structure, resource utilisation and trophic relationships in two Canadian Arctic Archipelago polynyas.

Climate change driven alterations to patterns of Arctic marine primary production, with increasing phytoplankton- and decreasing ice algal production, have the potential to change the resource utilisation and trophic structure of the benthic communities relying on the algae for food. To predict the benthic responses to dietary changes, we studied the macroinfaunal community compositions, and used the faunal δ13C and δ15N signatures to investigate their main food sources and trophic positions in North Water (NOW) and Lancaster Sound (LS) polynyas in the Canadian Arctic Archipelago. Macroinfaunal density (10 952 ind. m-2) and biomass (3190 mg C m-2) recorded in NOW were higher than previously found in the Arctic at depths >500m, and significantly higher than in LS (8355 ind. m-2 and 2110 mg C m-2). This was attributed to higher particulate organic matter fluxes to seafloor in NOW. Polychaetes were significant taxa at both sites in terms of density and biomass, and in addition crustacean density in NOW and bivalve density in LS were high. Facultative filter and surface deposit feeders were highly prevalent at both sites, suggesting feeding plasticity is a successful strategy for accessing different food sources. The macrofaunal δ13C signatures reflected the signatures of pelagic particulate organic matter at the sites, and an isotope mixing model confirmed phytoplankton as the main food source for most taxa and feeding guilds. The food web length in LS was longer than in NOW (3.2 vs. 2.8 trophic levels). This was attributed to a larger reliance on reworked organic matter by the benthic community in LS, whereas the high export fluxes at the highly productive NOW resulted in higher rates of selective consumption of fresh algal matter. Despite studies suggesting that loss of ice algae from consumer diets in the Arctic might have a negative impact on the benthos, this study suggests that Arctic macrobenthic communities thrive using phytoplankton as their main food source and should thus be able to cope or even benefit from predicted changes to patterns of primary production.

Spatio-temporal pattern of net primary productivity in Hengduan Mountains area, China: impacts of climate change and human activities

Net primary productivity (NPP), a metric used to define and identify changes in plant communities, is greatly affected by climate change, human activities and other factors. Here, we used the Carnegie-Ames-Stanford Approach (CASA) model to estimate the NPP of plant communities in Hengduan Mountains area of China, and to explore the relationship between NPP and altitude in this region. We examined the mechanisms underlying vegetation growth responses to climate change and quantitatively assessed the effects of ecological protection measures by partitioning the contributions of climate change and human activities to NPP changes. The results demonstrated that: 1) the average total and annual NPP values over the years were 209.15 Tg C and 468.06 g C/(m(2)center dot yr), respectively. Their trend increasingly fluctuated, with spatial distribution strongly linked to altitude (i.e., lower and higher NPP in high altitude and low altitude areas, respectively) and 2400 m represented the marginal altitude for vegetation differentiation; 2) areas where climate was the main factor affecting NPP accounted for 18.2% of the total research area, whereas human activities were the primary factor influencing NPP in 81.8% of the total research area, which indicated that human activity was the main force driving changes in NPP. Areas where climatic factors (i.e., temperature and precipitation) were the main driving factors occupied 13.6% (temperature) and 6.0% (precipitation) of the total research area, respectively. Therefore, the effect of temperature on NPP changes was stronger than that of precipitation; and 3) the majority of NPP residuals from 2001 to 2014 were positive, with human activities playing an active role in determining regional vegetation growth, possibly due to the return of farmland back to forest and natural forest protection. However, this positive trend is decreasing. This clearly shows the periodical nature of ecological projects and a lack of long-term effectiveness.

Sea ice thermohaline dynamics and biogeochemistry in the Arctic Ocean: Empirical and model results

Large changes in the sea ice regime of the Arctic Ocean have occurred over the last decades justifying the development of models to forecast sea ice physics and biogeochemistry. The main goal of this study is to evaluate the performance of the Los Alamos Sea Ice Model (CICE) to simulate physical and biogeochemical properties at time scales of a few weeks and to use the model to analyze ice algal bloom dynamics in different types of ice. Ocean and atmospheric forcing data and observations of the evolution of the sea ice properties collected from 18 April to 4 June 2015, during the Norwegian young sea ICE expedition, were used to test the CICE model. Our results show the following: (i) model performance is reasonable for sea ice thickness and bulk salinity; good for vertically resolved temperature, vertically averaged Chl a concentrations, and standing stocks; and poor for vertically resolved Chl a concentrations. (ii) Improving current knowledge about nutrient exchanges, ice algal recruitment, and motion is critical to improve sea ice biogeochemical modeling. (iii) Ice algae may bloom despite some degree of basal melting. (iv) Ice algal motility driven by gradients in limiting factors is a plausible mechanism to explain their vertical distribution. (v) Different ice algal bloom and net primary production (NPP) patterns were identified in the ice types studied, suggesting that ice algal maximal growth rates will increase, while sea ice vertically integrated NPP and biomass will decrease as a result of the predictable increase in the area covered by refrozen leads in the Arctic Ocean.

Benthic foraminiferal paleoecology and depositional patterns during the Albian at DSDP Site 327 (Falkland Plateau)

The present paleoenvironmental study uses a spectrum of analytical methods, such as benthic foraminiferal assemblages, total organic carbon (TOC), calcium carbonate (CaCO3) contents and magnetic susceptibility (MS), to monitor variations in primary productivity, bottom-water oxygenation and depositional patterns within the Albian interval recovered at DSDP Site 327, Hole A, Falkland Plateau. Thirty-three benthic foraminiferal species were identified in the studied section and, based on the abundances of morphogroups (epifaunal and shallow infaunal), two distinct associations were identified. Stratigraphic intervals dominated by the epifaunal morphogroup can be interpreted as indicative of bottom-waters with low-oxygen content. However, these decreases in oxygenation were not vigorous enough to establish a dominance of deep-infaunal morphotypes, as supported by the low TOC values. Intervals dominated by the shallow infaunal morphogroup were interpreted as subjected to moderate to high nutrient flux to the ocean floor. These intervals are associated with high MS values and low CaCO3 content, suggesting that dissolution processes, rather than increased primary productivity, controlled CaCO3 accumulation in the studied section. Furthermore, faunal analysis points to deposition in an outer neritic to upper bathyal paleoenvironment.

Regional distribution patterns of chemical parameters in surface sediments of the south-western Baltic Sea and their possible causes

This study presents selected results of a sediment geochemical mapping program of German territorial waters in the south-western Baltic Sea. The field work was conducted mainly during the early 2000s. Due to the strong variability of sediment types in the study area, it was decided to separate and analyse the fine fraction (<63 μm, mud) from more than 600 surficial samples, combined with recalculations for the bulk sediment. For the contents of total organic carbon (TOC) and selected elements (P, Hg), the regional distribution maps show strong differences between the analysed fine fraction and the recalculated total sediment. Seeing that mud contents vary strongly between 0 and 100%, this can be explained by the well-known grain-size effect. To avoid (or at least minimise) this effect, further interpretations were based on the data for the fine fraction alone. Lateral transport from the large Oder River estuary combined with high abundances and activities of benthic fauna on the shallow-water Oder Bank (well sorted fine sand) could be some main causes for hotspots identified in the fine-fraction element distribution. The regional pattern of primary production as the main driver of nutrient element fixation (C, N, P, Si) was found to be only weakly correlated with, for example, the TOC distribution in the fine fraction. This implies that, besides surface sediment dynamics, local conditions (e.g. benthic secondary production) also have strong impacts. To the best of the authors’ knowledge, there is no comparable study with geochemical analyses of the fine fraction of marine sediments to this extent (13,600 km2) and coverage (between 600 and 800 data points) in the Baltic Sea. This aspect proved pivotal in confidently pinpointing geochemical “anomalies” in surface sediments of the south-western Baltic Sea.