Picophytoplankton biomass distribution in the global ocean

The smallest marine phytoplankton, collectively termed picophytoplankton, have been routinely enumerated by flow cytometry since the late 1980s during cruises throughout most of the world ocean. We compiled a database of 40 946 data points, with separate abundance entries for Prochlorococcus, Synechococcus and picoeukaryotes. We use average conversion factors for each of the three groups to convert the abundance data to carbon biomass. After gridding with 1? spacing, the database covers 2.4% of the ocean surface area, with the best data coverage in the North Atlantic, the South Pacific and North Indian basins, and at least some data in all other basins. The average picophytoplankton biomass is 12 ± 22 µg Cl-1 or 1.9 g Cm-2. We estimate a total global picophytoplankton biomass of 0.53–1.32 Pg C (17–39% Prochlorococcus, 12–15% Synechococcus and 49–69% picoeukaryotes), with an intermediate/best estimate of 0.74 Pg C. Future efforts in this area of research should focus on reporting calibrated cell size and collecting data in undersampled regions

Picoheterotroph (Bacteria and Archaea) biomass distribution in the global ocean

We compiled a database of 39 766 data points consisting of flow cytometric and microscopical measurements of picoheterotroph abundance, including both Bacteria and Archaea. After gridding with 1° spacing, the database covers 1.3% of the ocean surface. There are data covering all ocean basins and depths except the Southern Hemisphere below 350m or from April until June. The average picoheterotroph biomass is 3.9 ± 3.6 µg Cl-1 with a 20-fold decrease between the surface and the deep sea. We estimate a total ocean inventory of about 1.3 × 1029 picoheterotroph cells. Surprisingly, the abundance in the coastal regions is the same as at the same depths in the open ocean. Using an average of published open ocean measurements for the conversion from abundance to carbon biomass of 9.1 fg cell-1, we calculate a picoheterotroph carbon inventory of about 1.2 Pg C. The main source of uncertainty in this inventory is the conversion factor from abundance to biomass. Picoheterotroph biomass is ? 2 times higher in the tropics than in the polar oceans

Mapping Biomass Distribution Potential

Undergraduate Student, Environmental Studies, The University of KansasPlatinum Sponsors * KU Department of Geography * Coca-Cola Gold Sponsors * KU Institute for Policy & Social Research * State of Kansas Data Access and Support Center (DASC) * KU Libraries GIS and Data Services * Wilson & Company Engineers and Architects Silver Sponsors * ASPRS - Central Region * Bartlett & West * C-CHANGE Program (NSF IGERT) * Garmin * Kansas Applied Remote Sensing Program * KansasView * KU Transportation Research Institute * KU Biodiversity Institute Bronze Sponsors * KU Center for Remote Sensing of Ice Sheets (CReSIS) * KU Center for Global & International Studies * KU Environmental Studies Progra

The biomass distribution on Earth

A census of the biomass on Earth is key for understanding the structure and dynamics of the biosphere. However, a global, quantitative view of how the biomass of different taxa compare with one another is still lacking. Here, we assemble the overall biomass composition of the biosphere, establishing a census of the ≈550 gigatons of carbon (Gt C) of biomass distributed among all of the kingdoms of life. We find that the kingdoms of life concentrate at different locations on the planet; plants (≈450 Gt C, the dominant kingdom) are primarily terrestrial, whereas animals (≈2 Gt C) are mainly marine, and bacteria (≈70 Gt C) and archaea (≈7 Gt C) are predominantly located in deep subsurface environments. We show that terrestrial biomass is about two orders of magnitude higher than marine biomass and estimate a total of ≈6 Gt C of marine biota, doubling the previous estimated quantity. Our analysis reveals that the global marine biomass pyramid contains more consumers than producers, thus increasing the scope of previous observations on inverse food pyramids. Finally, we highlight that the mass of humans is an order of magnitude higher than that of all wild mammals combined and report the historical impact of humanity on the global biomass of prominent taxa, including mammals, fish, and plants

Biomass distribution among tropical tree species grown under\ud differing regional climates

In the Neotropics, there is a growing interest in establishing plantations of native tree species for commerce, local consumption, and to replant on abandoned agricultural lands. Although numerous trial plantations have been established, comparative information on the performance of native trees under different regional environments is generally lacking. In this study, we evaluated the accumulation and partitioning of above-ground biomass in 16 native and two exotic tree species growing in replicated species selection trials in Panama under humid and dry regional environments. Seven of the 18 species accumulated greater total biomass at the humid site than at the dry site over a two-year period. Species specific biomass partitioning among leaves, branches and trunks was observed. However, awide range of total biomass found among species (from 1.06 kg for Dipteryx panamensis to 29.84 kg for Acacia mangium at Soberania) justified the used of an Aitchison log ratio transformation to adjust for size. When biomass partitioning was adjusted for size, a majority of these differences proved to be a result of the ability of the tree to support biomass components rather than the result of differences in the regional environments at the two sites. These findings were confirmed by comparative ANCOVAs on Aitchison-transformed and non-Aitchison-transformed variables. In these comparisons, basal diameter, height and diameter at breast height were robust predictors of biomass for the pooled data from both sites, but Aitchison-transformed\ud variables had little predictive power

A Study of Phytoplankton Dynamics in Lake Fayetteville as a Means of Assessing Water Quality

Phytoplankton community was analyzed for seasonal and vertical distribution in Lake Fayetteville. This northwest Arkansas reservoir maintains a stable water level and chemical input with a relatively constant, slow overflow. Its source is groundwater seepage through a calcareous substrate with little contribution from the limited drainage basin. Phytoplankton community development with its associations and assemblages, chlorophylls -a, -b and c, and biomass distribution are described. The seasonal cycles of the chemical parameters NH4-N, NO2-N, NO3-N, ortho-phosphate, silicon, pH, HCO3- and total-alkalinity plus oxygen are described and discussed. The physical parameters of temperature, light and climate are included. The interaction of these parameters and other factors are related to phytoplankton dynamics

Vertical biomass distribution drives flow through aquatic vegetation

Seagrass meadows represent important ecosystems providing many services, which have been disappearing, mostly due to anthropogenic reasons. Restoration attempts require deep understanding of the hydrodynamics involved, as well as the role of the biomechanical traits of the plants. This study analyzes the utilization of artificial elements as seagrass surrogates and their effect on flow. The surrogates are tested against a unidirectional current in a circular track-flume at velocities of 5, 10, 20 and 30 cm/s for three different vertical biomass distributions to assess the influence of biomechanical traits. Results show that the vertical biomass distribution plays an important role in the reduction of current velocity. The low shoot density tested also proved to be enough to onset current reduction utilizing artificial elements. This proves that ecosystem services such as sedimentation and energy dissipation are reproducible with artificial elements, and can be used as means for restoration and protection

How self-regulation, the storage effect and their interaction contribute to coexistence in stochastic and seasonal environments

Explaining coexistence in species-rich communities of primary producers remains a challenge for ecologists because of their likely competition for shared resources. Following Hutchinson's seminal suggestion, many theoreticians have tried to create diversity through a fluctuating environment, which impairs or slows down competitive exclusion. However, fluctuating-environment models often only produce a dozen of coexisting species at best. Here, we investigate how to create richer communities in fluctuating environments, using an empirically parameterized model. Building on the forced Lotka-Volterra model of Scranton and Vasseur (Theor Ecol 9(3):353-363, 2016), inspired by phytoplankton communities, we have investigated the effect of two coexistence mechanisms, namely the storage effect and higher intra- than interspecific competition strengths (i.e., strong self-regulation). We tuned the intra/inter competition ratio based on empirical analyses, in which self-regulation dominates interspecific interactions. Although a strong self-regulation maintained more species (50%) than the storage effect (25%), we show that none of the two coexistence mechanisms considered could ensure the coexistence of all species alone. Realistic seasonal environments only aggravated that picture, as they decreased persistence relative to a random environment. However, strong self-regulation and the storage effect combined superadditively so that all species could persist with both mechanisms at work. Our results suggest that combining different coexistence mechanisms into community models might be more fruitful than trying to find which mechanism best explains diversity. We additionally highlight that while biomass-trait distributions provide some clues regarding coexistence mechanisms, they cannot indicate unequivocally which mechanisms are at play.Comment: 27 pages, 9 figures, Theor Ecol (2019

Mathematical algorithm to transform digital biomass distribution maps into linear programming networks in order to optimize bio-energy delivery chains

Many linear programming models have been developed to model the logistics of bio-energy chains. These models help to determine the best set-up of bio-energy chains. Most of them use network structures built up from nodes with one or more depots, and arcs connecting these depots. Each depot is source of a certain biomass type. Nodes can also be a storage point for a certain biomass type or a production facility (e.g. power plant) where the biomass is used. Arcs represent transport between depots. To be able to combine GIS spatial studies with linear programming models it is necessary to build a network from a digital map. In this work a mathematical calculation method is developed to select the actual points on the map where to collect biomass that will then be considered as biomass sources in a network model