Spatio-temporal resolution of spawning and larval nursery habitats using otolith microchemistry is element dependent

2020 ◽  
Vol 636 ◽  
pp. 169-187
Author(s):  
ORB Thomas ◽  
KV Thomas ◽  
GP Jenkins ◽  
SE Swearer

Otolith chemistry is frequently employed in the reconstruction of fish environmental histories. While some elements have been strongly correlated with environmental factors (e.g. salinity, temperature, water chemistry), others may not indicate exogenous factors and simply add endogenous variability to a data set. Several commonly assessed elements were previously identified as being only present in the proteinaceous fraction of endolymph from black bream Acanthopagrus butcheri, suggesting that the choice of elements in otolith multi-elemental fingerprinting could influence their utility as natural environmental markers. To test this hypothesis, we performed several cluster analyses based on different sets of trace element data extracted from both the core and larval region of otoliths of juvenile black bream. We clustered in 3 different ways: (1) all elements analysed; (2) elements identified as being primarily in the salt fraction of the endolymph (i.e. inorganic); and (3) elements identified as being associated with the protein fraction of the endolymph. We subsequently assessed the power of the resulting clusters to resolve cohort identity and/or collection location based on differences in otolith chemistry using multinomial logistic regression. Our results indicate that clustering based solely on salt-fraction elements is best for resolving spatio-temporal variability in spawning sources and larval nursery habitats of black bream.

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 338
Author(s):  
Claire Michelet ◽  
Daniela Zeppilli ◽  
Cédric Hubas ◽  
Elisa Baldrighi ◽  
Philippe Cuny ◽  
...  

Bioindicators assess the mangroves ecological state according to the types of pressures but they differ with the ecosystem’s specificities. We investigated benthic meiofauna diversity and structure within the low human-impacted mangroves in French Guiana (South America) in response to sediment variables with various distances to the main city. Contaminant’s concentrations differed among the stations, but they remained below toxicity guidelines. Meiofauna structure (Foraminifera, Kinorhyncha, Nematoda) however varied accordingly. Nematode’s identification brought details on the sediment’s quality. The opportunistic genus Paraethmolaimus (Jensen, 1994) strongly correlated to the higher concentrations of Hg, Pb. Anoxic sediments were marked by organic enrichment in pesticides, PCB, and mangrove litter products and dominance of two tolerant genus, Terschellingia (de Man, 1888) and Spirinia (Gerlach, 1963). In each of these two stations, we found many Desmodora individuals (de Man, 1889) with the presence of epibionts highlighting the nematodes decreased fitness and defenses. Oxic sediments without contaminants were distinguished by the sensitive genera Pseudocella (Filipjev, 1927) and a higher diversity of trophic groups. Our results suggested a nematodes sensitivity to low contaminants concentrations. Further investigations at different spatio-temporal scales and levels of deterioration, would be necessary to use of this group as bioindicator of the mangroves’ ecological status.


2021 ◽  
pp. 1351010X2098690
Author(s):  
Romana Rust ◽  
Achilleas Xydis ◽  
Kurt Heutschi ◽  
Nathanael Perraudin ◽  
Gonzalo Casas ◽  
...  

In this paper, we present a novel interdisciplinary approach to study the relationship between diffusive surface structures and their acoustic performance. Using computational design, surface structures are iteratively generated and 3D printed at 1:10 model scale. They originate from different fabrication typologies and are designed to have acoustic diffusion and absorption effects. An automated robotic process measures the impulse responses of these surfaces by positioning a microphone and a speaker at multiple locations. The collected data serves two purposes: first, as an exploratory catalogue of different spatio-temporal-acoustic scenarios and second, as data set for predicting the acoustic response of digitally designed surface geometries using machine learning. In this paper, we present the automated data acquisition setup, the data processing and the computational generation of diffusive surface structures. We describe first results of comparative studies of measured surface panels and conclude with steps of future research.


2005 ◽  
Vol 56 (5) ◽  
pp. 609 ◽  
Author(s):  
T. S. Elsdon ◽  
B. M. Gillanders

Elemental concentrations within fish otoliths can track movements and migrations of fish through gradients of environmental variables. Tracking the movements of fish relies on establishing links between environmental variables and otolith chemistry, with links commonly made using laboratory experiments that rear juvenile fish. However, laboratory experiments done on juvenile fish may not accurately reflect changes in wild fish, particularly adults. We tested the hypotheses that: (1) the relationship between ambient (water) and otolith chemistry is similar between laboratory-reared black bream (Acanthopagrus butcheri) and wild black bream; and (2) ontogeny does not influence otolith chemistry. Field-collected and laboratory-reared fish showed similar effects of ambient strontium : calcium (Sr : Ca) on otolith Sr : Ca concentrations. However, ambient and otolith barium : calcium concentrations (Ba : Ca) differed slightly between laboratory-reared and field-collected fish. Importantly, fish reared in stable environmental variables showed no influence of ontogeny on Sr : Ca or Ba : Ca concentrations. Natural distributions of ambient Sr : Ca showed no clear relationship to salinity, yet, ambient Ba : Ca was inversely related to salinity. The distribution of ambient Sr : Ca and Ba : Ca in estuaries inhabited by black bream, suggest that these elements can answer different questions regarding environmental histories of fish. Reconstructing salinity histories of black bream using otolith Ba : Ca concentrations seems plausible, if adequate knowledge of Ba : Ca gradients within estuaries is obtained.


2015 ◽  
Vol 14 ◽  
pp. 70-90 ◽  
Author(s):  
Caley K. Gasch ◽  
Tomislav Hengl ◽  
Benedikt Gräler ◽  
Hanna Meyer ◽  
Troy S. Magney ◽  
...  

2021 ◽  
Author(s):  
Miroslaw Latka ◽  
Klaudia Kozlowska ◽  
Bruce J. West

Abstract During treadmill walking, the subject’s stride length (SL) and duration (ST) yield a stride speed (SS) which fluctuates over a narrow range centered on the treadmill belt’s speed. We recently demonstrated that ST and SL trends are strongly correlated and serve as control manifolds about which the corresponding gait parameters fluctuate. The fundamental problem, which has not yet been investigated, concerns the contribution of SL and ST fluctuations to SS variability. To investigate this relation, we approximate SS variance by the linear combination of SL variance and ST variance, as well as their covariance. The combination coefficients are nonlinear functions of ST and SL mean values and, consequently, depend on treadmill speed. The approximation applies to constant speed treadmill walking and walking on a treadmill whose belt speed is perturbed by strong, high-frequency noise. In the first case, up to 80% of stride speed variance comes from SL fluctuations. In the presence of perturbations, the SL contribution decreases with increasing speed, but its lowest value is still twice as large as that of either ST variance or SL-ST covariance. The presented evidence supports the hypothesis that stride length adjustments are primarily responsible for speed maintenance during walking. Such a control strategy is evolutionarily advantageous due to the weak speed dependence of the SL contribution to SS variance. The ability to maintain speed close to that of a moving cohort did increase the chance of an individual’s survival throughout most of human evolution.


2018 ◽  
Vol 34 (3) ◽  
pp. 1247-1266 ◽  
Author(s):  
Hua Kang ◽  
Henry V. Burton ◽  
Haoxiang Miao

Post-earthquake recovery models can be used as decision support tools for pre-event planning. However, due to a lack of available data, there have been very few opportunities to validate and/or calibrate these models. This paper describes the use of building damage, permitting, and repair data from the 2014 South Napa Earthquake to evaluate a stochastic process post-earthquake recovery model. Damage data were obtained for 1,470 buildings, and permitting and repair time data were obtained for a subset (456) of those buildings. A “blind” prediction is shown to adequately capture the shape of the recovery trajectory despite overpredicting the overall pace of the recovery. Using the mean time to permit and repair time from the acquired data set significantly improves the accuracy of the recovery prediction. A generalized model is formulated by establishing statistical relationships between key time parameters and endogenous and exogenous factors that have been shown to influence the pace of recovery.


Author(s):  
M. McDermott ◽  
S. K. Prasad ◽  
S. Shekhar ◽  
X. Zhou

Discovery of interesting paths and regions in spatio-temporal data sets is important to many fields such as the earth and atmospheric sciences, GIS, public safety and public health both as a goal and as a preliminary step in a larger series of computations. This discovery is usually an exhaustive procedure that quickly becomes extremely time consuming to perform using traditional paradigms and hardware and given the rapidly growing sizes of today’s data sets is quickly outpacing the speed at which computational capacity is growing. In our previous work (Prasad et al., 2013a) we achieved a 50 times speedup over sequential using a single GPU. We were able to achieve near linear speedup over this result on interesting path discovery by using Apache Hadoop to distribute the workload across multiple GPU nodes. Leveraging the parallel architecture of GPUs we were able to drastically reduce the computation time of a 3-dimensional spatio-temporal interest region search on a single tile of normalized difference vegetative index for Saudi Arabia. We were further able to see an almost linear speedup in compute performance by distributing this workload across several GPUs with a simple MapReduce model. This increases the speed of processing 10 fold over the comparable sequential while simultaneously increasing the amount of data being processed by 384 fold. This allowed us to process the entirety of the selected data set instead of a constrained window.


2021 ◽  
Vol 13 (19) ◽  
pp. 3956
Author(s):  
Shan He ◽  
Huaiyong Shao ◽  
Wei Xian ◽  
Shuhui Zhang ◽  
Jialong Zhong ◽  
...  

Hilly areas are important parts of the world’s landscape. A marginal phenomenon can be observed in some hilly areas, leading to serious land abandonment. Extracting the spatio-temporal distribution of abandoned land in such hilly areas can protect food security, improve people’s livelihoods, and serve as a tool for a rational land plan. However, mapping the distribution of abandoned land using a single type of remote sensing image is still challenging and problematic due to the fragmentation of such hilly areas and severe cloud pollution. In this study, a new approach by integrating Linear stretch (Ls), Maximum Value Composite (MVC), and Flexible Spatiotemporal DAta Fusion (FSDAF) was proposed to analyze the time-series changes and extract the spatial distribution of abandoned land. MOD09GA, MOD13Q1, and Sentinel-2 were selected as the basis of remote sensing images to fuse a monthly 10 m spatio-temporal data set. Three pieces of vegetation indices (VIs: ndvi, savi, ndwi) were utilized as the measures to identify the abandoned land. A multiple spatio-temporal scales sample database was established, and the Support Vector Machine (SVM) was used to extract abandoned land from cultivated land and woodland. The best extraction result with an overall accuracy of 88.1% was achieved by integrating Ls, MVC, and FSDAF, with the assistance of an SVM classifier. The fused VIs image set transcended the single source method (Sentinel-2) with greater accuracy by a margin of 10.8–23.6% for abandoned land extraction. On the other hand, VIs appeared to contribute positively to extract abandoned land from cultivated land and woodland. This study not only provides technical guidance for the quick acquirement of abandoned land distribution in hilly areas, but it also provides strong data support for the connection of targeted poverty alleviation to rural revitalization.


Sign in / Sign up

Export Citation Format

Share Document