Seasonal Production Patterns Research Articles

Food production and consumption in Bamyan Province, Afghanistan: the challenges of sustainability and seasonality for dietary diversity

ABSTRACT In Asia, high levels of malnutrition threaten the health and livelihoods of millions of households. This paper concentrates on linkages between agriculture and nutrition in Afghanistan where food and nutrition insecurity are increasing and agricultural sustainability is increasingly compromised by climate change. We explore seasonal patterns of food production and consumption in the remote and robust ecological environment of Shah Foladi, Bamyan Province. Analysis of qualitative data from household interviews in eight villages has provided a wealth of insights into the seasonality of diets. Even within a broadly homogeneous environment, households were found to be markedly heterogeneous in respect of their assets, production, market, finance and employment strategies. The so-called ‘lean season’ was found to vary accordingly. Nevertheless, a general lack of dietary diversity during much of the year is likely to cause micronutrient malnutrition, especially for the vulnerable groups of children, adolescent girls and women. Potential interventions are proposed which need to account for the local context in order to overcome the natural and political constraints. These strategies include agricultural innovation and multi-sectoral policy approaches. In the end, reducing national insecurity is a pre-requisite for sustainable improvement in nutrition-sensitive agricultural development.

Daily-seasonal operation in net-zero energy building powered by hybrid renewable energies and hydrogen storage systems

The net-zero energy buildings are often supplied by renewable resources and energy storage systems. These energy resources have different seasonal and daily patterns of power production. Their output power is also uncertain. This paper aims to study these issues including daily-seasonal operation patterns, uncertainty, and cogeneration of various renewable resources and storage systems. These issues are investigated at net-zero energy building supported by renewable resources (i.e., solar energy, hydro energy, and fuelcell) and energy storage systems (i.e., hydrogen storage system). The uncertain parameters of the model are solar-hydro-load powers. The model minimizes the investment cost on solar system. The plan finds optimal sizing and operation for solar, hydro, hydrogen, and fuel-cell. The cooperation of hydrogen storage and fuelcell is optimized to level the uncertainty. The surplus of energy is fed into water electrolyzer to produce hydrogen and the fuelcell consumes the hydrogen to produce electricity. The seasonal operation is dealt by cogeneration of hydro-solar systems. The proposed plan installs 73 kW solar panel. The hydrogen storage system is charged at hours 7–17. When hydro power is increased to 39 kW, the building does not need the solar energy. The proposed model decreases the Carbon Dioxide by about 39546 kg. The model also reduces the total cost by about 50.3%.

Seasonal and spatial patterns of primary production in a high-latitude fjord affected by Greenland Ice Sheet run-off

Abstract. Primary production on the coast and in Greenland fjords sustains important local and sustenance fisheries. However, unprecedented melting of the Greenland Ice Sheet (GrIS) is impacting the coastal ocean, and its effects on fjord ecology remain understudied. It has been suggested that as glaciers retreat, primary production regimes may be altered, rendering fjords less productive. Here we investigate patterns of primary productivity in a northeast Greenland fjord (Young Sound, 74∘ N), which receives run-off from the GrIS via land-terminating glaciers. We measured size fractioned primary production during the ice- free season along a spatial gradient of meltwater influence. We found that, apart from a brief under-ice bloom during summer, primary production remains low (between 50 and 200 mg C m−2 d−1) but steady throughout the ice-free season, even into the fall. Low productivity is due to freshwater run-off from land-terminating glaciers causing low light availability and strong vertical stratification limiting nutrient availability. The former is caused by turbid river inputs in the summer restricting phytoplankton biomass to the surface and away from the nitracline. In the outer fjord where turbidity plays less of a role in light limitation, phytoplankton biomass moves higher in the water column in the fall due to the short day length as the sun angle decreases. Despite this, plankton communities in this study were shown to be well adapted to low-light conditions, as evidenced by the low values of saturating irradiance for primary production (5.8–67 µmol photons m−2 s−1). With its low but consistent production across the growing season, Young Sound offers an alternative picture to other more productive fjords which have highly productive spring and late summer blooms and limited fall production. However, patterns of primary productivity observed in Young Sound are not only due to the influence from land-terminating glaciers but are also consequences of the nutrient-depleted coastal boundary currents and the shallow entrance sill, features which should also be considered when generalizing about how primary production will be affected by glacier retreat in the future.

Seasonal Soybean Price Transmission between the U.S. and Brazil Using the Seasonal Regime-Dependent Vector Error Correction Model

Soybean production and trade in the U.S. and Brazil are seasonal. Our research question is whether the seasonal tendencies cause the price relationship between U.S. and Brazilian soybean prices. Therefore, the objective is to test for seasonality in the price transmission between the U.S. and Brazil soybean prices using the seasonal regime-dependent vector error correction model (VECM). Our results show that the speed of the adjustment for the U.S. soybean price in the first half of the year is greater than the speed of the adjustment for the Brazilian soybean price. However, the pattern of their responses becomes the reverse in the second half of the year. The component share calculated by the result of the VECM with seasonal effects indicates that the U.S. dominates the world soybean market during the second half of the year while Brazil is dominant in the soybean market in the first half of the year. These results give us an important finding that we could not find using the VECM without seasonal effects. Finally, our results imply that the seasonal pattern of production in the U.S. and Brazil could cause the sustainability of the supply chain in the world soybean market.

Seasonal Variations in Primary Productivity and Biomass of Phytoplankton in Geoje-Hansan Bay on the Southern Coast of Korea

Phytoplankton constitutes an important dietary item of oysters in suspended longline aquaculture systems. Primary productivity and the community structure of phytoplankton, as well as hydrographic and nutritional conditions of the water column, were monitored monthly in Geoje-Hansan Bay on the southern coast of Korea between July 2013 and July 2014 to determine the seasonal variation patterns of productivity and structures of phytoplankton assemblages. All measured physicochemical and biological components exhibited temporal variabilities common to all four sampling sites within the bay system. The hydrographic features were characterized by a summer stratified and fall–winter well-mixed structure of the water column. Daily primary productivity in the bay (0.16–2.88 g C m–2 d–1) peaked in summer; it displayed a unimodal cycle, and the most dominant phytoplankton group shifted from diatoms to dinoflagellates. Canonical correspondence analysis, based on environmental factors and the phytoplankton community, enabled the identification of seasonal patterns of phytoplankton assemblage in relation to temporal variations of hydrographic and nutritional conditions. Results indicated that increase of the watercolumn stability and enhanced nutrient input by freshwater discharge during the summer monsoon and possible upward flux from bottom sediment led to the peaking primary productivity and diatom-dominated community during that time, supporting high annual productivity (371 g C m–2 yr–1). Our findings suggest that seasonal properties of hydrodynamics and nutritional conditions play a key role in determining the primary productivity and structuring of the phytoplankton community. Summer peaks in productivity and diatom dominance most likely ultimately determine oyster growth and the final success of aquaculture.

Modeling phenological controls on carbon dynamics in dryland sagebrush ecosystems

Dryland ecosystems play an important role in determining how precipitation anomalies affect terrestrial carbon fluxes at regional to global scales. Thus, to understand how climate change may affect the global carbon cycle, we must also be able to understand and model its effects on dryland vegetation. Dynamic Global Vegetation Models (DGVMs) are an important tool for modeling ecosystem dynamics, but they often struggle to reproduce seasonal patterns of plant productivity. Because the phenological niche of many plant species is linked to both total productivity and competitive interactions with other plants, errors in how process-based models represent phenology hinder our ability to predict climate change impacts. This may be particularly problematic in dryland ecosystems where many species have developed a complex phenology in response to seasonal variability in both moisture and temperature. Here, we examine how uncertainty in key parameters as well as the structure of existing phenology routines affect the ability of a DGVM to match seasonal patterns of leaf area index (LAI) and gross primary productivity (GPP) across a temperature and precipitation gradient. First, we optimized model parameters using a combination of site-level eddy covariance data and remotely-sensed LAI data. Second, we modified the model to include a semi-deciduous phenology type and added flexibility to the representation of grass phenology. While optimizing parameters reduced model bias, the largest gains in model performance were associated with the development of our new representation of phenology. This modified model was able to better capture seasonal patterns of both leaf area index (R2 = 0.75) and gross primary productivity (R2 = 0.84), though its ability to estimate total annual GPP depended on using eddy covariance data for optimization. The new model also resulted in a more realistic outcome of modeled competition between grass and shrubs. These findings demonstrate the importance of improving how DGVMs represent phenology in order to accurately forecast climate change impacts in dryland ecosystems.

Mismatched seasonal patterns of larval production and quality in subtropical barnacle populations along a coastal trophic gradient

The seasonal breeding patterns of a wide array of marine invertebrates are shaped by strong and deterministic environmental factors over their geographic distribution range, such as temperature or photoperiod. Whether or not such patterns will remain adaptive at more localized scales may depend on how consistent are secondary drivers controlling resource supply to parents and offspring. We address this question by examining the seasonal patterns of both the trophic state of coastal waters, and larval production and quality produced by a filter-feeding invertebrate, the intertidal barnacle Chthamalus bisinuatus, along a 150 km long trophic gradient in Southeastern Brazil. Results are consistent to previous remote sensing work showing strong seasonal variation of chlorophyll-a and particulate organic carbon concentrations, increasing 2 to 2.5 times from summer – early autumn to winter, compatible to enhanced production through vertical mixing caused by passing cold fronts. The spatial gradient was also verified and found to be consistent between seasons, but contrasts were of smaller magnitude (coefficients of variations between 15 and 35%). All reproductive parameters showed important seasonal but no spatial trends. Larval production was much higher in summer-early autumn, agreeing with previous results based on gonad development and early recruitment rate for this same species and published results for other chthamalids. However, per capita parental transfer of neutral fatty acids to larvae and larval survival without exogenous food increased 2 and 1.4 times from the breeding to the non-breeding season, respectively, indicating that coastal oceanographic processes favor larval quality when reproductive activity is lower. Given that food limitation is likely frequent in the study region, shifting from oligotrophic to mesotrophic, and that effects of larval nourishing can be carried over to benthic barnacle stages, results also suggest that the contribution of out-of-season offspring to overall recruitment may be disproportionately higher.

Seasonal Patterns of Root Production with Water and Nitrogen Additions Across Three Dryland Ecosystems

Root production is known to contribute at least 50% of total net primary production in dryland ecosystems, yet few studies have addressed seasonal dynamics of root production or the belowground response to altered resource availability. We aimed to identify how root production varies across three dryland ecosystems dominated by different plant functional types: the shortgrass steppe, dominated by C4 perennial bunchgrasses, the northern mixed-grass prairie, co-dominated by perennial C3 and C4 grasses, and the sagebrush steppe, dominated by a perennial shrub with an understory of C3 and C4 grasses and forbs. We also sought to determine how root production changes throughout a growing season for these three systems, and how it responds to increased water and nitrogen availability. We used root ingrowth cores to monitor root production in 6-week intervals between June 1 and October 5, 2017, and with water and nitrogen additions in shortgrass steppe, mixed-grass prairie, and sagebrush steppe in the western Great Plains of the United States. We found that the northern mixed-grass prairie had the highest total root production during our sampling period, and that seasonal patterns of root growth varied significantly across the dryland types, with root growth greatest during the middle of the growing season at the sagebrush steppe and greatest during the end of the growing season at the northern mixed-grass prairie. As expected, belowground root production was about half aboveground production in all sites. Root production responded less to water and nitrogen addition than did aboveground production.

Comparison of litterfall production in three forest types in Jeju Island, South Korea

Litterfall, which is influenced by physical and biological factors, is a major pathway for carbon and nutrient cycling in forest ecosystems. The purpose of this study was to investigate monthly litterfall production in three forests in Jeju Island differentiated by forest composition and precipitation: Cheongsu (Quercus glauca as the dominant species; low precipitation), Seonheulb (Q. glauca as the dominant species; high precipitation), and Seonheulm (Q. glauca and Pinus thunbergii as the dominant species; high precipitation). Litterfall was collected monthly from April to December 2015 and divided into leaf litter, twig, bark, seeds, and unidentified materials. Seasonal patterns of litterfall production varied across stands according to their species composition. However, the amount of leaf litterfall and total litterfall were comparable among stands, ranging from 362 to 375 g m−2 for leaf litter and 524 g m−2 to 580 g m−2 for total litterfall. Oak leaf litter in May was the highest in all stands, while needle litter was the highest in December in Seonheulm. High twig litterfall in July may be attributable to high rainfall with strong winds and storms during the rainy season. Although forest type and climate factor had no influence on litterfall amounts in this study, the pattern of litterfall production was species dependent, suggesting diverse effects on carbon and nutrient cycling in these forests.

Metabolic rhythms in flowing waters: An approach for classifying river productivity regimes

AbstractAlthough seasonal patterns of ecosystem productivity have been extensively described and analyzed with respect to their primary forcings in terrestrial and marine systems, comparatively little is known about these same processes in rivers. However, it is now possible to perform a large‐scale synthesis on the patterns and drivers of river productivity regimes because of the recent sensor advances allowing for near‐continuous estimates of river productivity. Here, we explore a dataset of 47 U.S. rivers to examine whether there are characteristic river productivity regimes. We use classification approaches to develop a typology of productivity regimes and then use these regimes to examine differences with respect to potential controls of productivity. We identified two distinct metabolic regimes, which we named Summer Peak and Spring Peak Rivers, within our dataset. These regimes meaningfully differed in both the timing and magnitude of productivity and were robust to different approaches to classification. We also found that several variables, including watershed area and characteristics of water temperature or discharge, were able to predict the class membership of these regimes with modest accuracy. Our results support the presence of characteristic metabolic regimes and suggests that these regimes may have common sets of environmental controls. We present classification as one approach to begin exploring the productivity regimes of rivers. The strength of our approach is that it fully leverages these newly available high‐frequency productivity estimates to create classes that can be used to draw inferences about how the controls of river productivity differ between or within systems.

Seasonal, Interannual, and Longitudinal Patterns in Estuarine Metabolism Derived from Diel Oxygen Data Using Multiple Computational Approaches

Twenty-three station-years of diel oxygen data for the James River Estuary were analyzed to characterize longitudinal, seasonal, and interannual patterns of gross primary production (GPP) and ecosystem respiration (ER). We compared two commonly used methods for deriving metabolism (bookkeeping and Bayesian) to determine whether the observed patterns were robust with respect to computational methodology. The two methods revealed similar longitudinal patterns of increasing GPP and ER, and decreasing net ecosystem metabolism (NEM), with increasing salinity. Seasonal patterns in GPP and ER tracked water temperature and solar radiation, except during high discharge events when metabolism declined by 40%. The bookkeeping method yielded higher estimates of GPP and ER in the higher end of the range, and smaller estimates in the low end of the range, thereby accentuating seasonal and longitudinal differences. Inferences regarding net autotrophy and heterotrophy were robust, as both methods yielded positive estimates of NEM at the chlorophyll maximum (tidal fresh segment) and negative values for the saline portion of the estuary. Inferences regarding the relative importance of allochthonous inputs (based on inferred ER at GPP = 0) differed between the two methods. Values derived by the bookkeeping method indicated that respiration was largely supported by autochthonous production, whereas the Bayesian results indicated that autochthonous and allochthonous inputs were equally important. Overall, our findings show that methodological differences were small in the context of longitudinal, seasonal, and interannual variation but that the bookkeeping method yielded a wider range of values for GPP and ER relative to the Bayesian estimates.

Multi-Scale Phenology of Temperate Grasslands: Improving Monitoring and Management With Near-Surface Phenocams

Grasslands of the Australian Southern Tablelands represent a patchwork of native and exotic systems, occupying a continuum of C3-dominated to C4-dominated grasslands where composition depends on disturbance factors (e.g. grazing) and climate. Managing these complex landscapes is both challenging and critical for maintaining the security of Australia’s pasture industries, and for protecting the biodiversity of native remnants. Differentiating C3 from C4 vegetation has been a prominent theme in remote sensing research due to distinct C3/C4 seasonal productivity patterns (phenology) and high uncertainty about how C3/C4 vegetation will respond to a changing climate. Phenology is used in northern hemisphere ecosystems for a range of purposes but has not been widely adopted in Australia, where dynamic climate often results in non-repetitive seasonal vegetation patterns. We employed time-lapse cameras (phenocams) to study the phenology of twelve grassland areas dominated by cool season (C3) and warm season (C4), native or exotic grasses near Canberra, Australia. Our aims were to assess phenological characteristics of the functional types and to determine the drivers of phenological variability. We compared the fine-scale phenocam seasonal profiles with field sampling and MODIS/Landsat satellite products to assess paddock-to-landscape functioning. We found C3/C4 species dominance to be the primary driver of phenological differences among grassland types, with C3 grasslands demonstrating peak greenness in spring, and senescing rapidly in response to high summer temperatures. In contrast, C4 grasslands showed peak activity in Austral summer and autumn (January-March). Some sites displayed primary and secondary peaks dependent on rainfall and species composition. We found that the proportion of dead vegetation is an important biophysical driver of grassland phenology, as were grazing pressures and species-dependent responses to rainfall and temperature. The satellite and field datasets were in general agreement with the phenocam results. However, the higher temporal fidelity of the cameras captured changes in vegetation not observed in the coarser satellite or field results. Our phenocam data shows consistent periods of increasing and decreasing greenness over as little as five days. Applications for management of grasslands in temperate Australia include the identification of remnant native grasslands, tracking biosecurity issues, and assessing productivity responses to climate variability.

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.

Modeling seasonal and vertical habitats of planktonic foraminifera on a global scale

Abstract. Species of planktonic foraminifera exhibit specific seasonal production patterns and different preferred vertical habitats. The seasonal and vertical habitats are not constant throughout the range of the species and changes therein must be considered when interpreting paleoceanographic reconstructions based on fossil foraminifera. However, detecting the effect of changing vertical and seasonal habitat on foraminifera proxies requires independent evidence for either habitat or climate change. In practice, this renders accounting for habitat tracking from fossil evidence almost impossible. An alternative method that could reduce the bias in paleoceanographic reconstructions is to predict species-specific habitat shifts under climate change using an ecosystem modeling approach. To this end, we present a new version of a planktonic foraminifera model, PLAFOM2.0, embedded into the ocean component of the Community Earth System Model version 1.2.2. This model predicts monthly global concentrations of the planktonic foraminiferal species Neogloboquadrina pachyderma, N. incompta, Globigerina bulloides, Globigerinoides ruber (white), and Trilobatus sacculifer throughout the world ocean, resolved in 24 vertical layers to 250 m of depth. The resolution along the vertical dimension has been implemented by applying the previously used spatial parameterization of carbon biomass as a function of temperature, light, nutrition, and competition on depth-resolved parameter fields. This approach alone results in the emergence of species-specific vertical habitats, which are spatially and temporally variable. Although an explicit parameterization of the vertical dimension has not been carried out, the seasonal and vertical distribution patterns predicted by the model are in good agreement with sediment trap data and plankton tow observations. In the simulation, the colder-water species N. pachyderma, N. incompta, and G. bulloides show a pronounced seasonal cycle in their depth habitat in the polar and subpolar regions, which appears to be controlled by food availability. During the warm season, these species preferably occur in the subsurface (below 50 m of water depth), while towards the cold season they ascend through the water column and are found closer to the sea surface. The warm-water species G. ruber (white) and T. sacculifer exhibit a less variable shallow depth habitat with highest carbon biomass concentrations within the top 40 m of the water column. Nevertheless, even these species show vertical habitat variability and their seasonal occurrence outside the tropics is limited to the warm surface layer that develops at the end of the warm season. The emergence in PLAFOM2.0 of species-specific vertical habitats, which are consistent with observations, indicates that the population dynamics of planktonic foraminifera species may be driven by the same factors in time, space, and with depth, in which case the model can provide a reliable and robust tool to aid the interpretation of proxy records.

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.

Net ecosystem productivity and carbon dynamics of the traditionally managed Imperata grasslands of North East India

There have been few comprehensive descriptions of how fire management and harvesting affect the carbon dynamics of grasslands. Grasslands dominated by the invasive weed Imperata cylindrica are considered as environmental threats causing low land productivity throughout the moist tropical regions in Asia. Imperata grasslands in North East India are unique in that they are traditionally managed and culturally important in the rural landscapes. Given the importance of fire in the management of Imperata grassland, we aimed to assess (i) the seasonal pattern of biomass production, (ii) the eventual pathways for the produced biomass, partitioned between in situ decomposition, harvesting and combustion, and (iii) the effect of customary fire management on the ecosystem carbon cycle. Comparatively high biomass production was recorded during pre-monsoon (154 g m−2 month−1) and monsoon (214 g m−2 month−1) compared to the post-monsoon (91 g m−2 month−1) season, and this is attributed to nutrient return into the soil immediately after fire in February. Post fire effects might have killed roots and rhizomes leading to high belowground litter production 30–35 g m−2 during March to August. High autotrophic respiration was recorded during March–July, which was related to high belowground biomass production (35–70 g m−2) during that time. Burning removed all the surface litter in March and this appeared to hinder surface decomposition and result in low heterotrophic respiration. Annual total biomass carbon production was estimated at 886 g C m−2. Annual harvest of biomass (estimated at 577 g C m−2) was the major pathway for carbon fluxes from the system. Net ecosystem production (NEP) of Imperata grassland was estimated at 91 g C m−2 yr−1 indicating that these grasslands are a net sink of CO2, although this is greatly influenced by weather and fire management.

Understanding the life cycle of North Sea brown shrimp Crangon crangon: a simulation model approach

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 584:119-143 (2017) - DOI: https://doi.org/10.3354/meps12325 Understanding the life cycle of North Sea brown shrimp Crangon crangon: a simulation model approach Axel Temming*, Claudia Günther, Chris Rückert, Marc Hufnagl Institute of Hydrobiology and Fishery Science, University of Hamburg, Olbersweg 24, 22767 Hamburg, Germany *Corresponding author: atemming@uni-hamburg.de ABSTRACT: A simulation model of the life cycle of Crangon crangon tracking daily cohorts from the egg stage to the adult stage was programmed in R taking into account size-specific, seasonally varying natural mortality rates of all life stages, temperature-dependent development rates of eggs and larvae, juvenile and adult growth rates as a function of temperature and size, sex, maturation, egg production, and seasonally varying size-specific fishing mortalities. The observed seasonal patterns of commercial catch and egg production could only be reproduced with fast growth rates, which linked winter egg production with the subsequent juvenile recruitment in May-June, the commercial catch peak in September and the peak in egg production over the following winter. Likewise, substantially lowered natural mortalities in winter are essential to generate seasonal patterns similar to the observed ones. The seasonal pattern of egg production can only be reproduced with a minimum spawning age. Cohorts from summer eggs rapidly follow the earlier winter egg cohorts, forming an annual joint wave of growing shrimp. The summer egg cohort originates from summer eggs of the previous year and, depending on winter and spring mortality levels, also from large individuals of the preceding winter egg cohort. The model represents a new tool to investigate maximum yield per recruit in this species as a function of seasonal effort levels, mesh sizes and seasonal closures under different predation and temperature scenarios. KEY WORDS: Brown shrimp · North Sea · Life cycle · Simulation model · Growth · Mortality · Maturity · Sex · Cohort structure Full text in pdf format Supplementary material PreviousNextCite this article as: Temming A, Günther C, Rückert C, Hufnagl M (2017) Understanding the life cycle of North Sea brown shrimp Crangon crangon: a simulation model approach. Mar Ecol Prog Ser 584:119-143. https://doi.org/10.3354/meps12325 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 584. Online publication date: December 07, 2017 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2017 Inter-Research.

Fine root dynamics after soil disturbance evaluated with a root scanner method

Fine root production in ecosystems has been estimated mainly by excavation methods that cause soil disturbance. In this study, patterns of fine root dynamics following soil disturbance were monitored for multiple years and were analyzed quantitatively by applying a root scanner method that allows continuous observations. Eleven scanners were inserted into the soil of cypress and oak forests with soil disturbance, and weekly soil profiles were scanned for several years. Then fine root dynamics were estimated quantitatively by image analyses. Fine roots emerged intensively in the immediate year of the scanner installation. Seasonal patterns of cumulative root area production followed the logistic curve, but its parameters varied depending on stands and elapsed years after the scanner installation. Estimates of the annual production and instantaneous production rate from the logistic equation differed between the immediate and the following years after disturbance in the cypress and oak stands. The root scanner method is a viable technique to quantitatively describe fine root dynamics of forests, including the possible effects of soil disturbance. The results suggested that fine root production can be described by a logistic equation providing both an asymptotic upper boundary and a growth coefficient.

Sea ice phenology and primary productivity pulses shape breeding success in Arctic seabirds

Spring sea ice phenology regulates the timing of the two consecutive pulses of marine autotrophs that form the base of the Arctic marine food webs. This timing has been suggested to be the single most essential driver of secondary production and the efficiency with which biomass and energy are transferred to higher trophic levels. We investigated the chronological sequence of productivity pulses and its potential cascading impacts on the reproductive performance of the High Arctic seabird community from Svalbard, Norway. We provide evidence that interannual changes in the seasonal patterns of marine productivity may impact the breeding performance of little auks and Brünnich’s guillemots. These results may be of particular interest given that current global warming trends in the Barents Sea region predict one of the highest rates of sea ice loss within the circumpolar Arctic. However, local- to regional-scale heterogeneity in sea ice melting phenology may add uncertainty to predictions of climate-driven environmental impacts on seabirds. Indeed, our fine-scale analysis reveals that the inshore Brünnich’s guillemots are facing a slower advancement in the timing of ice melt compared to the offshore-foraging little auks. We provide a suitable framework for analyzing the effects of climate-driven sea ice disappearance on seabird fitness.

How Well Does Chlorophyll Explain the Seasonal Variation in Phytoplankton Activity?

The seasonal variation in phytoplankton activity is determined by analysing 1385 primary production (PP) profiles, chlorophyll a (Chl) concentration profiles and phytoplankton carbon biomass concentrations (C) from the period 1998–2012. The data was collected at six different stations in the Baltic Sea transition zone (BSTZ) which is a location with strong seasonal production patterns with light as the key parameter controlling this productivity. We show that the use of Chl as a proxy for phytoplankton activity strongly overestimates the contribution from the spring production to annual pelagic carbon flow. Spring (February and March) Chl comprised 16–30% of the total annual Chl produced, whereas spring C was much lower (8–23%) compared to the annual C. Spring PP accounted for 10–18% of the total annual PP, while the July–August production contributed 26–33%, i.e. within the time frame when zooplankton biomass and grazing pressure are highest. That is, Chl failed in this study to reflect the importance of the high summer PP. A better proxy for biomass may be C, which correlated well with the seasonal pattern of PP (Pearson correlation, p < 0.05). Thus, this study suggests to account for the strong seasonal pattern in C/Chl ratios when considering carbon flow in coastal systems. Seasonal data for PP were fitted to a simple sinusoidal wave model describing the seasonal distribution of PP in the BSTZ and were proposed to present a better parameterizaton of PP in shallow stratified temperate regions than more commonly applied proxies.