Spatial and temporal dynamics of Pacific capelin Mallotus catervarius in the Gulf of Alaska: implications for ecosystem-based fisheries management

2020 ◽  
Vol 637 ◽  
pp. 117-140 ◽  
Author(s):  
DW McGowan ◽  
ED Goldstein ◽  
ML Arimitsu ◽  
AL Deary ◽  
O Ormseth ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Marine Ecosystem ◽  
Gulf Of Alaska ◽  
Data Series ◽  
Limited Information ◽  
Important Species ◽  
Multiple Data ◽  
Spatial And Temporal Dynamics ◽  
Spawning Areas ◽  
Spatio Temporal

Pacific capelin Mallotus catervarius are planktivorous small pelagic fish that serve an intermediate trophic role in marine food webs. Due to the lack of a directed fishery or monitoring of capelin in the Northeast Pacific, limited information is available on their distribution and abundance, and how spatio-temporal fluctuations in capelin density affect their availability as prey. To provide information on life history, spatial patterns, and population dynamics of capelin in the Gulf of Alaska (GOA), we modeled distributions of spawning habitat and larval dispersal, and synthesized spatially indexed data from multiple independent sources from 1996 to 2016. Potential capelin spawning areas were broadly distributed across the GOA. Models of larval drift show the GOA’s advective circulation patterns disperse capelin larvae over the continental shelf and upper slope, indicating potential connections between spawning areas and observed offshore distributions that are influenced by the location and timing of spawning. Spatial overlap in composite distributions of larval and age-1+ fish was used to identify core areas where capelin consistently occur and concentrate. Capelin primarily occupy shelf waters near the Kodiak Archipelago, and are patchily distributed across the GOA shelf and inshore waters. Interannual variations in abundance along with spatio-temporal differences in density indicate that the availability of capelin to predators and monitoring surveys is highly variable in the GOA. We demonstrate that the limitations of individual data series can be compensated for by integrating multiple data sources to monitor fluctuations in distributions and abundance trends of an ecologically important species across a large marine ecosystem.

Modelling and analysis of spatio-temporal dynamics of a marine ecosystem

2015 ◽  
Vol 81 (4) ◽  
pp. 1895-1906 ◽  
Author(s):  
Kunal Chakraborty ◽  
Vamsi Manthena
Keyword(s):  
Temporal Dynamics ◽  
Marine Ecosystem ◽  
Spatio Temporal

scholarly journals Role of jellyfish in the plankton ecosystem revealed using a global ocean biogeochemical model

2021 ◽  
Vol 18 (4) ◽  
pp. 1291-1320
Author(s):  
Rebecca M. Wright ◽  
Corinne Le Quéré ◽  
Erik Buitenhuis ◽  
Sophie Pitois ◽  
Mark J. Gibbons
Keyword(s):  
Temporal Dynamics ◽  
Marine Ecosystem ◽  
Zooplankton Community ◽  
Ocean Model ◽  
Plankton Community ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Ocean Biogeochemical Model ◽  
Spatio Temporal ◽  
Plankton Community Structure

Abstract. Jellyfish are increasingly recognised as important components of the marine ecosystem, yet their specific role is poorly defined compared to that of other zooplankton groups. This paper presents the first global ocean biogeochemical model that includes an explicit representation of jellyfish and uses the model to gain insight into the influence of jellyfish on the plankton community. The Plankton Type Ocean Model (PlankTOM11) model groups organisms into plankton functional types (PFTs). The jellyfish PFT is parameterised here based on our synthesis of observations on jellyfish growth, grazing, respiration and mortality rates as functions of temperature and jellyfish biomass. The distribution of jellyfish is unique compared to that of other PFTs in the model. The jellyfish global biomass of 0.13 PgC is within the observational range and comparable to the biomass of other zooplankton and phytoplankton PFTs. The introduction of jellyfish in the model has a large direct influence on the crustacean macrozooplankton PFT and influences indirectly the rest of the plankton ecosystem through trophic cascades. The zooplankton community in PlankTOM11 is highly sensitive to the jellyfish mortality rate, with jellyfish increasingly dominating the zooplankton community as its mortality diminishes. Overall, the results suggest that jellyfish play an important role in regulating global marine plankton ecosystems across plankton community structure, spatio-temporal dynamics and biomass, which is a role that has been generally neglected so far.

scholarly journals Weevil borers affect the spatio-temporal dynamics of banana Fusarium wilt

2021 ◽  
Author(s):  
Daniel Heck ◽  
Gabriel Alves ◽  
Eduardo S. G. Mizubuti
Keyword(s):  
Fusarium Wilt ◽  
Temporal Dynamics ◽  
Insect Pests ◽  
Field Conditions ◽  
Disease Progress ◽  
Spatial And Temporal Dynamics ◽  
Comparative Epidemiology ◽  
Progress Rate ◽  
Spatio Temporal ◽  
Metamasius Hemipterus

AbstractDispersal of propagules of a pathogen has remarkable effects on the development of epidemics. Previous studies suggested that insect pests play a role in the development of Fusarium wilt (FW) epidemics in banana fields. We provided complementary evidence for the involvement of two insect pests of banana, the weevil borer (Cosmopolites sordidus L. - WB) and the false weevil borer (Metamasius hemipterus L. - FWB), in the dispersal of Fusarium oxysporum f. sp. cubense (Foc) using a comparative epidemiology approach under field conditions. Two banana plots located in a field with historical records of FW epidemics were used, one was managed with Beauveria bassiana to reduce the population of weevils, and the other was left without B. bassiana applications. The number of WB and FWB was monitored biweekly and the FW incidence was quantified bimonthly during two years. The population of WB and the incidence (6.7%) of FW in the plot managed with B. bassiana were lower than in the plot left unmanaged (13%). The monomolecular model best fitted the FW disease progress data and, as expected, the average estimated disease progress rate was lower in the plot managed with the entomopathogenic fungus (r = 0.0024) compared to the unmanaged plot (r = 0.0056). Aggregation of FW was higher in the field with WB management. WB affected the spatial and temporal dynamics of FW epidemics under field conditions and brought evidence that managing the insects may reduce FW of bananas intensity.

scholarly journals Spatio-Temporal Dynamics of Municipal Planning, a case study of Barahathawa Municipality, Nepal

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Kedar Dahal ◽  
Krishna P. Timilsina
Keyword(s):  
Urban Growth ◽  
Agricultural Land ◽  
Temporal Dynamics ◽  
Transportation Network ◽  
Urban Expansion ◽  
Infrastructure Development ◽  
Rural Settlements ◽  
Goods And Services ◽  
Spatial And Temporal Dynamics ◽  
Spatio Temporal

The Rapid transformation of rural settlements into municipalities in Nepal has brought significant changes in land use and urban expansion patterns mostly through the conversion of agricultural land into the built-up area. The issue is studied taking a case of rapidly growing town Barahathawa Municipality of Sarlahi District. After the declaration of the municipality, several new roads have been opened and upgraded; and the municipality has well-connected to the national transportation network. After promulgated the Constitution of Nepal 2015 and elected local bodies, the municipality budget has been increased significantly as a result of increasing municipal investment in socio-economic and physical infrastructure development and environmental protection which have attracted people, goods, and services creating the zone of influence. One of the changes found in the municipality is the increasing built-up area and expansion of urban growth through the decreasing agricultural land. Urban growth has been observed taking place around the Barahathawa Bazaar and main roadsides. The built-up area in Barahathawa municipality has remarkably increased by 184% with the decrease of shrub and agricultural land within 10 years. Implications of such spatial and temporal dynamics have been a core issue of urban planning in most of the newly declared municipalities in Nepal

scholarly journals Data, models and ecosystem services: the Marine Ecosystems Research Programme

2018 ◽  
Author(s):  
Paul J. Somerfield
Keyword(s):  
Ecosystem Services ◽  
Food Web ◽  
Temporal Dynamics ◽  
Marine Ecosystem ◽  
Research Programme ◽  
Marine Ecosystems ◽  
Marine Food Webs ◽  
Common Framework ◽  
Spatio Temporal ◽  
Ecosystem Changes

The effects of marine ecosystem changes on ecosystem services are difficult to predict because of our limited understanding of marine food-webs, how they respond to changes in pressures, and how those changes then influence services. Biogeochemical ecosystem models do a good job of representing change in groups of organisms primarily influenced by spatio-temporal dynamics in physics and chemistry, such as phytoplankton and small zooplankton. For groups of organisms higher in the food-web, such as fish, mammals and birds, a variety of different modelling approaches are used. No particular approach attempts to model the entire system, each viewing the food-web from a different perspective. Links to services are rarely explicit. To allow us to respond appropriately to change we need to improve our understanding of, and ability to model, the marine ecosystem as a whole, and links between changes in the marine ecosystem and its ability to deliver services. The Marine Ecosystems Research Programme (www.marine-ecosystems.org.uk) provides mechanisms to bring together existing data, targeted new data, different models, and to link them to ecosystem services within a common framework. A key aim is to project effects of possible policy decisions on ecosystem services which are mediated by ecosystem processes.

scholarly journals TMOD-15. IDENTIFYING THE SPATIAL AND TEMPORAL DYNAMICS OF GLIOBLASTOMA SUBPOPULATIONS WITHIN INDIVIDUAL PATIENTS

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi265-vi266
Author(s):  
Bethan Morris ◽  
Lee Curtin ◽  
Andrea Hawkins-Daarud ◽  
Bernard Bendok ◽  
Maciej Mrugala ◽  
...  
Keyword(s):  
Treatment Response ◽  
Temporal Dynamics ◽  
Dynamic Information ◽  
Treatment Regimes ◽  
Spatially Resolved ◽  
Spatial And Temporal Dynamics ◽  
Genetic Features ◽  
Spatio Temporal ◽  
Insight Into

Abstract Glioblastomas (GBMs) are known to be complex tumors comprising multiple subpopulations of genetically-distinct cancer cells; it is thought that this genetic variation is a major factor in the lack of observed survival benefit of treatment regimes that target one of these subpopulations. The field of radiogenomics seeks to study correlations between MRI patterns and genetic features of GBM tumors. Spatial radiogenomic maps produced using machine-learning (ML) methods that are trained against information from image-localized patient biopsies identify regions where particular cancer sub-populations are predicted to occur within a GBM, thus non-invasively characterizing the regional genetic variability of these tumors. These tumor subpopulations may also interact with one another, in ways which may be of a competitive or cooperative nature to varying degrees. It is important to ascertain the nature of these interactions, as they may have implications for treatment response to targeted therapies, and characterization of the spatio-temporal dynamics of these co-evolving sub-populations will shed light on why some therapies fail. Here we combine mathematical modeling techniques and spatially-resolved radiogenomic maps to study the nature of these interactions between molecularly-distinct GBM subpopulations. We model the interactions between cell populations using a partial differential equation based formalism. The model is parameterized using radiogenomic ML maps from which we infer the nature of interactions between subpopulations. Furthermore, using maps as inputs, the model turns static maps into dynamic information, thus providing insight into how these subpopulations composing the tumor change over time and the effect this has on observed treatment response for individual patients.

scholarly journals Weevil Borers Affect the Spatio-Temporal Dynamics of Banana Fusarium Wilt

2021 ◽  
Vol 7 (5) ◽  
pp. 329
Author(s):  
Daniel W. Heck ◽  
Gabriel Alves ◽  
Eduardo S. G. Mizubuti
Keyword(s):  
Fusarium Wilt ◽  
Temporal Dynamics ◽  
Insect Pests ◽  
Field Conditions ◽  
Disease Progress ◽  
Spatial And Temporal Dynamics ◽  
Comparative Epidemiology ◽  
Progress Rate ◽  
Spatio Temporal ◽  
Metamasius Hemipterus

Dispersal of propagules of a pathogen has remarkable effects on the development of epidemics. Previous studies suggested that insect pests play a role in the development of Fusarium wilt (FW) epidemics in banana fields. We provided complementary evidence for the involvement of two insect pests of banana, the weevil borer (Cosmopolites sordidus L., WB) and the false weevil borer (Metamasius hemipterus L., FWB), in the dispersal of Fusarium oxysporum f. sp. cubense (Foc) using a comparative epidemiology approach under field conditions. Two banana plots located in a field with historical records of FW epidemics were used; one was managed with Beauveria bassiana to reduce the population of weevils, and the other was left without B. bassiana applications. The number of WB and FWB was monitored biweekly and the FW incidence was quantified bimonthly during two years. The population of WB and the incidence (6.7%) of FW in the plot managed with B. bassiana were lower than in the plot left unmanaged (13%). The monomolecular model best fitted the FW disease progress data, and as expected, the average estimated disease progress rate was lower in the plot managed with the entomopathogenic fungus (r = 0.002) compared to the unmanaged plot (r = 0.006). Aggregation of FW was higher in the field with WB management. WB affected the spatial and temporal dynamics of FW epidemics under field conditions. Management of the insects may reduce yield loss due to FW.

scholarly journals Ensemble Spatio-Temporal Distance Net for Skeleton Based Action Recognition

2019 ◽  
Vol 20 (3) ◽  
pp. 485-494
Author(s):  
M Naveenkumar ◽  
S Domnic
Keyword(s):  
Action Recognition ◽  
Short Term Memory ◽  
Temporal Dynamics ◽  
Spatial Dynamics ◽  
Recognition System ◽  
Temporal Distance ◽  
Spatial Distance ◽  
Spatial And Temporal Dynamics ◽  
Entire Sequence ◽  
Spatio Temporal

The performance of an efficient and accurate action recognition system heavily depends on distinctive representations for a different class of action sequences. To address this issue, we propose an ensemble network in this paper. We design two multilayer Long Short Term Memory networks to capture spatial and temporal dynamics of the entire sequence, referred to as Spatial-distance Net (SdNet) and Temporal-distance Net (TdNet) respectively. More specifically, SdNet captures the spatial dynamics of joints within a frame and TdNet explores the temporal dynamics of joints between frames along the sequence. Finally, two nets are fused as one Ensemble network, referred to as Spatio -Temporal distance Net (STdNet) to explore both spatial and temporal dynamics. The efficacy of the proposed method is evaluated on two widely used datasets, UTD MHAD and NTU RGB+D, and the proposed STdNet achieved 91.16% and 80.03% accuracies respectively.

scholarly journals Signatures of the collapse and incipient recovery of an overexploited marine ecosystem

2017 ◽  
Vol 4 (7) ◽  
pp. 170215 ◽  
Author(s):  
Eric J. Pedersen ◽  
Patrick L. Thompson ◽  
R. Aaron Ball ◽  
Marie-Josée Fortin ◽  
Tarik C. Gouhier ◽  
...  
Keyword(s):  
Regime Shift ◽  
Temporal Dynamics ◽  
Atlantic Cod ◽  
Marine Ecosystem ◽  
Management Strategies ◽  
Individual Species ◽  
Trawl Survey ◽  
Effective Management ◽  
Spatial And Temporal Dynamics ◽  
Wide Perspective

The Northwest Atlantic cod stocks collapsed in the early 1990s and have yet to recover, despite the subsequent establishment of a continuing fishing moratorium. Efforts to understand the collapse and lack of recovery have so far focused mainly on the dynamics of commercially harvested species. Here, we use data from a 33-year scientific trawl survey to determine to which degree the signatures of the collapse and recovery of the cod are apparent in the spatial and temporal dynamics of the broader groundfish community. Over this 33-year period, the groundfish community experienced four phases of change: (i) a period of rapid, synchronous biomass collapse in most species, (ii) followed by a regime shift in community composition with a concomitant loss of functional diversity, (iii) followed in turn by periods of slow compositional recovery, and (iv) slow biomass growth. Our results demonstrate how a community-wide perspective can reveal new aspects of the dynamics of collapse and recovery unavailable from the analysis of individual species or a combination of a small number of species. Overall, we found evidence that such community-level signals should be useful for designing more effective management strategies to ensure the persistence of exploited marine ecosystems.

scholarly journals A novel 5D brain parcellation approach based on spatio-temporal encoding of resting fMRI data from deep residual learning

2021 ◽  
Author(s):  
Behnam Kazemivash ◽  
Vince D. Calhoun
Keyword(s):  
Temporal Dynamics ◽  
Brain Network ◽  
Brain Anatomy ◽  
Temporal Networks ◽  
Residual Network ◽  
Brain Organization ◽  
Spatial And Temporal Dynamics ◽  
Temporal Encoding ◽  
Spatio Temporal ◽  
The Brain

AbstractObjectiveBrain parcellation is an essential aspect of computational neuroimaging research and deals with segmenting the brain into (possibly overlapping) sub-regions employed to study brain anatomy or function. In the context of functional parcellation, brain organization which is often measured via temporal metrics such as coherence, is highly dynamic. This dynamic aspect is ignored in most research, which typically applies anatomically based, fixed regions for each individual, and can produce misleading results.MethodsIn this work, we propose a novel spatio-temporal-network (5D) brain parcellation scheme utilizing a deep residual network to predict the probability of each voxel belonging to a brain network at each point in time.ResultsWe trained 53 4D brain networks and evaluate the ability of these networks to capture spatial and temporal dynamics as well as to show sensitivity to individual or group-level variation (in our case with age).ConclusionThe proposed system generates informative spatio-temporal networks that vary not only across individuals but also over time and space.SignificanceThe dynamic 5D nature of the developed approach provides a powerful framework that expands on existing work and has potential to identify novel and typically ignored findings when studying the healthy and disordered brain.

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