Hasil untuk "General. Including nature conservation, geographical distribution"

Qiuhua Yang, Lili Wang, Yanfang Zhong et al.

In autumn 2020, cultured sea cucumbers (Apostichopus japonicus) in the Xiapu Sea area (Southeast China) exhibited ulcerative skin lesions. To identify the causative pathogen, the Gram-negative strain 10MKXP20 was isolated from the muscle tissue of diseased animals and identified as Photobacterium leiognathi through phenotypic and genetic analysis. The bacterium was sensitive to 14 antibiotics, including tetracycline and enrofloxacin, but resistant to gentamicin, neomycin, kanamycin, rifampicin, amikacin, and amoxicillin. Minimum inhibitory concentration (MIC) assays revealed varying efficacy among the tested antibiotics, with enrofloxacin, doxycycline, and florfenicol showing particularly low MICs, indicating strong inhibitory activity. Challenge experiments via immersion and intramuscular injection confirmed the pathogenicity of P. leiognathi 10MKXP20, with mortality rates being dose-dependent. This study is the first to identify P. leiognathi as the causative agent of ulcerative skin disease in sea cucumbers, providing crucial insights for disease diagnosis and antibiotic treatment.

Stefanie Simpson, Lindsey S. Smart, Lindsey S. Smart et al.

Blue carbon ecosystems, such as mangroves, tidal marshes, and seagrasses, are important for climate mitigation. As carbon sinks, they often exhibit higher per hectare carbon storage capacity and sequestration rates than terrestrial systems. These ecosystems provide additional benefits, including enhancing water quality, sustaining biodiversity, and maintaining coastal resilience to climate change impacts. The widespread loss of blue carbon ecosystems due to anthropogenic activities can contribute to increasing carbon emissions globally. Monetizing blue carbon through carbon credits offers an avenue to generate revenue and incentivize conservation and restoration efforts. However, limited data on project costs and carbon benefits make prioritization of blue carbon projects challenging. To address these challenges, we have developed, in collaboration with blue carbon experts, the Blue Carbon Cost Tool. This is a user-friendly interface enabling comparison of three core market project components – 1) carbon credit estimation, 2) project cost estimation, and 3) a qualitative, non-economic feasibility assessment – to assess and compare potential for blue carbon projects. Tool simulations with data available from nine countries demonstrate (a) how factors such as country, ecosystem type and project scale drive variability, (b) the need for local or project-specific data to enhance accuracy and reduce uncertainty, particularly in tidal marsh and seagrass systems, and (c) that higher price tolerance or upfront capital is needed to bridge implementation and maintenance cost gaps. The Blue Carbon Cost Tool can aid project developers and investors to better understand market opportunity and the resources needed to develop high quality blue carbon market projects.

Octavio Aburto-Oropeza, Valentina Platzgummer, Erica M. Ferrer et al.

Mechanisms for marine ecological protection and recovery, including area-based conservation tools like ‘Marine Protected Areas’ (MPAs) are necessary tools to reach the Aichi Target or the forthcoming 30x30 target set by the Kunming-Montreal Biodiversity Framework. However, full ecosystem recovery takes years to manifest and the idea that MPA protection alone will foster human well-being is frequently contradicted by socio-economic evidence. Therefore, a new framework for marine area-based conservation and ecosystem restoration that reconciles the discrepancies between ecological recovery and socio-economic growth timelines is needed to effectively meet global biodiversity conservation targets. We introduce the concept of ‘Marine Prosperity Areas,’ (MPpA) an area-based conservation tool that prioritizes human prosperity as opposed to passively relying on ecosystem recovery to catalyze social change and economic growth. This concept leverages a suite of tried-and-true community-based intervention and investment strategies to strengthen and expand access to environmental science, social goods and services, and the financial perks of the blue economy. This data-driven framework may be of interest to stakeholders who support traditional area-based conservation models, but also to those who have been historically opposed to MPAs or have been excluded from past conservation processes.

Mónica-Yanira Rodríguez-Pérez, Laura Sánchez-Velasco, Martha-Patricia Rosas-Hernández et al.

Hakan Topal

This article examines how artistic practices respond to the emergence of a “negative community” after a disaster, where people are bound together by displacement, abandonment, and infrastructural control rather than choice or solidarity. Drawing on fieldwork in coastal Japan following the 2011 earthquake, tsunami, and nuclear accident, this article reflects on how art can resist the reduction of catastrophe to either spectacle or state‐managed recovery. Through practices of observation, witnessing, and collective engagement, art creates vital spaces of proximity, care, and dissent. In doing so, it unsettles imposed forms of community and opens possibilities for imagining a new social life beyond the structures of ruin and control.

Yuhan Wang, Silu He, Qinyao Luo et al.

The existing methods learn geographic network representations through deep graph neural networks (GNNs) based on the i.i.d. assumption. However, the spatial heterogeneity and temporal dynamics of geographic data make the out-of-distribution (OOD) generalisation problem particularly salient. The latter are particularly sensitive to distribution shifts (feature and structural shifts) between testing and training data and are the main causes of the OOD generalisation problem. Spurious correlations are present between invariant and background representations due to selection biases and environmental effects, resulting in the model extremes being more likely to learn background representations. The existing approaches focus on background representation changes that are determined by shifts in the feature distributions of nodes in the training and test data while ignoring changes in the proportional distributions of heterogeneous and homogeneous neighbour nodes, which we refer to as structural distribution shifts. We propose a feature-structure mixed invariant representation learning (FSM-IRL) model that accounts for both feature distribution shifts and structural distribution shifts. To address structural distribution shifts, we introduce a sampling method based on causal attention, encouraging the model to identify nodes possessing strong causal relationships with labels or nodes that are more similar to the target node. Inspired by the Hilbert-Schmidt independence criterion, we implement a reweighting strategy to maximise the orthogonality of the node representations, thereby mitigating the spurious correlations among the node representations and suppressing the learning of background representations. Our experiments demonstrate that FSM-IRL exhibits strong learning capabilities on both geographic and social network datasets in OOD scenarios.

Puya Memarzia, Huaxin Zhang, Kelvin Ho et al.

Geographically distributed database systems use remote replication to protect against regional failures. These systems are sensitive to severe latency penalties caused by centralized transaction management, remote access to sharded data, and log shipping over long distances. To tackle these issues, we present GaussDB-Global, a sharded geographically distributed database system with asynchronous replication, for OLTP applications. To tackle the transaction management bottleneck, we take a decentralized approach using synchronized clocks. Our system can seamlessly transition between centralized and decentralized transaction management, providing efficient fault tolerance and streamlining deployment. To alleviate the remote read and log shipping issues, we support reads on asynchronous replicas with strong consistency, tunable freshness guarantees, and dynamic load balancing. Our experimental results on a geographically distributed cluster show that our approach provides up to 14x higher read throughput, and 50% more TPC-C throughput compared to our baseline.

Shirley Wu, Kaidi Cao, Bruno Ribeiro et al.

Graph data are inherently complex and heterogeneous, leading to a high natural diversity of distributional shifts. However, it remains unclear how to build machine learning architectures that generalize to the complex distributional shifts naturally occurring in the real world. Here, we develop GraphMETRO, a Graph Neural Network architecture that models natural diversity and captures complex distributional shifts. GraphMETRO employs a Mixture-of-Experts (MoE) architecture with a gating model and multiple expert models, where each expert model targets a specific distributional shift to produce a referential representation w.r.t. a reference model, and the gating model identifies shift components. Additionally, we design a novel objective that aligns the representations from different expert models to ensure reliable optimization. GraphMETRO achieves state-of-the-art results on four datasets from the GOOD benchmark, which is comprised of complex and natural real-world distribution shifts, improving by 67% and 4.2% on the WebKB and Twitch datasets. Code and data are available at https://github.com/Wuyxin/GraphMETRO.

Tim Z. Xiao, Johannes Zenn, Robert Bamler

The Street View House Numbers (SVHN) dataset is a popular benchmark dataset in deep learning. Originally designed for digit classification tasks, the SVHN dataset has been widely used as a benchmark for various other tasks including generative modeling. However, with this work, we aim to warn the community about an issue of the SVHN dataset as a benchmark for generative modeling tasks: we discover that the official split into training set and test set of the SVHN dataset are not drawn from the same distribution. We empirically show that this distribution mismatch has little impact on the classification task (which may explain why this issue has not been detected before), but it severely affects the evaluation of probabilistic generative models, such as Variational Autoencoders and diffusion models. As a workaround, we propose to mix and re-split the official training and test set when SVHN is used for tasks other than classification. We publish a new split and the indices we used to create it at https://jzenn.github.io/svhn-remix/ .

Xueqi Li, Xueqi Li, Qinfeng Gao et al.

A two-stage diet-switch experiment was conducted to examine the hypothesis that the changes in digestive enzyme activities of sea cucumber (Apostichopus japonicus) induced by historic diets might persist in the regenerated intestines. In stage I, A. japonicus were treated with two different diets for 56 days, including diet A with 11% crude protein, 1% crude lipid, and 40% carbohydrate, and diet B with 18% crude protein, 2% crude lipid, and 35% carbohydrate. In stage II, each treatment was subjected to evisceration with 0.35M KCl or not (eviscerated and non-eviscerated groups), half of which were then switched to different diets from diet A to B or vice versa for 112 days. The persistence of digestive enzyme activities was evaluated by measuring the changes in digestive enzyme activities before and after evisceration. In stage I, diets B and A increased trypsin and amylase activities, respectively. In stage II, the higher trypsin activities were observed in eviscerated and non-eviscerated A. japonicus that had consumed diet B in stage I. The higher amylase activities were observed only in eviscerated A. japonicus that had consumed diet A in stage I. It indicated that the historic diets showed long-term effects on the digestion of A. japonicus, which led to the persistence of changes in both trypsin and amylase activities in intestines, especially in the regenerated intestines. In addition, the specific growth rates (SGRs) and metabolic rates (MRs) of A. japonicus were affected by the long-term effects of historic diets. Meanwhile, the relationships between enzymic activities, SGRs, and MRs were observed in A. japonicus, indicating that the historic diets could produce long-term effects on the growth and metabolism of A. japonicus through their long-term effects of historic diets on digestive enzyme activities. In conclusion, the present study showed that the changes in digestive enzyme activities induced by different diets in stage I could persist in the intestines and regenerated intestines, leading to long-term effects of historic diets on the growth and metabolism of A. japonicus.

Amália Maria Sacilotto Detoni, Ajit Subramaniam, Sheean T. Haley et al.

Inputs of new nitrogen by cyanobacterial diazotrophs are critical to ocean ecosystem structure and function. Relative to other ocean regions, there is a lack of data on the distribution of these microbes in the western South Atlantic. Here, the abundance of six diazotroph phylotypes: Trichodesmium, Crocosphaera, UCYN-A, Richelia associated with Rhizosolenia (Het-1) or Hemiaulus (Het-2), and Calothrix associated with Chaetoceros (Het-3) was measured by quantitative PCR (qPCR) of the nifH gene along a transect extending from the shelf-break to the open ocean along the Vitória-Trindade seamount chain (1200 km). Using nifH gene copies as a proxy for phylotype abundance, Crocosphaera signals were the most abundant, with a broad distribution throughout the study region. Trichodesmium signals were the second most abundant, with the greatest numbers confined to the warmer waters closer to the coast, and a significant positive correlation with temperature. The average signals for the host-associated diazotrophs (UCYN-A, Het-1, and Het-2) were consistently lower than for the other phylotypes. These findings expand measurements of cyanobacterial diazotroph distribution in the western South Atlantic, and provide a new resource to enhance modeling studies focused on patterns of nitrogen fixation in the global ocean.

Siyu Yan, Binbin Li, Kunxia Yu et al.

[Objective] The erosion intensity and the causes of erosion of the production roads after rainstorm in the small watershed at Xiji County, Ningxia Hui Autonomous Region were explored in order to provide a theoretical basis for improving the situation of soil erosion and improving the construction and maintenance of water and soil conservation projects in the future. [Methods] From July 25 to 29, 2022, Soil and Water Conservation Monitoring Center of the Ministry of Water Resources organized a comprehensive survey on soil and water conservation of the "7·13" rainstorm at Xiji County, Ningxia Hui Autonomous Region. The environment and erosion status of the production road in the small watershed of the Wushicha small watershed were investigated and the erosion intensity was calculated by using the "section method". The erosion intensity status and the causes of erosion were analyzed. [Results] ① The rainfall, the characteristics of road and the human activities are the main influencing factors of the production roads erosion in the Wushicha small watershed. Each road shows different erosion patterns, among which the lower reaches of the small watershed, along the runoff direction and with low vegetation coverage are seriously eroded. ② The road erosion modulus of small watershed is analyzed and calculated. The calculated value of "section method" is 1 054.49 t/km2, and the measured value of 3D image is 1 277.91 t/km2. The damage rate of the survey section is 53.39%. [Conclusion] It is necessary and effective to implement soil and water conservation measures. Good soil and water conservation measures and high vegetation coverage rate can effectively prevent the occurrence of soil and water loss on production roads.

Bingying Xu, Yuechong Liu, Kai Chen et al.

Single-cell proteins are attracting growing attention as viable alternatives for fishmeal (FM) in aquatic feed. Methanotroph (Methylococcus capsulatus, Bath) bacteria meal FeedKind® (FK) is a type of single cell protein with high protein content (75.14%) and desirable amino acids profile, produced by Methylococcus capsulatus (Bath) living on methane consumption. The present study evaluated the potential of replacing FM with FK in the diet of black sea bream (Acanthopagrus schlegelii). Five iso-energetic and iso-nitrogenous diets were designed with FK replacing 0, 4.13, 8.27, 16.53, and 24.80% FM protein in the basal diet (40% FM content), respectively. All the diets were fed to three replicates of fish (initial weight 6.56 ± 0.02 g) for 70 days. After the feeding trial, replacing dietary 8.27% FM protein with FK significantly improved the weight gain and specific growth rate of fish (P < 0.05), while other groups showed no significant difference in the growth performance (P > 0.05). The fish fed diets with 8.27 and 16.53% replacement levels exhibited significantly increased feeding rates. The 8.27% FK diet significantly increased the whole-body and muscle crude protein contents, apparent digestibility of crude lipid, foregut, and midgut amylase activities. The microvillus density in the midgut of fish fed the 24.80% FK diet significantly increased. The diet with 8.27% FK increased the serum triglyceride content of the fish, while the 24.80% FK diet reduced the serum triglyceride, total cholesterol, and low-density lipoprotein cholesterol contents of the fish. In conclusion, the results indicated that replacing dietary FM protein with up to 24.80% FK had no adverse effects on the growth of black sea bream, whilst replacing 8.27% FM protein with FK enhanced its growth performance and feed utilization.

Wenhong Pang, Xiaoyan Zhou, Zhijun Dai et al.

Beach intra-tidal bed level changes are of significance to coastal protection amid global climate changes. However, due to the limitation of instruments and the disturbance induced by wave motions superimposed on water levels, it was difficult to detect the high-frequency oscillation of the submerged beach bed level. In this study, an observation, lasting for 12 days and covering the middle tide to the following spring tide, was conducted on a meso-macro tidal beach, Yintan Beach, to simultaneously detect the characteristics and influence mechanism of bed level changes at intra-tidal and tidal cycle scales. The collected data included water depth, suspended sediment concentration (SSC), waves, high-frequency three-dimensional (3-D) velocity, and the distance of the seabed to the acoustic Doppler velocimeter (ADV) probe, which were measured by an optical backscatter sensor, two Tide & Wave Recorder-2050s, and an ADV, respectively. The results showed that the tidal cycle-averaged bed level decreased by 58.8 mm, increased by 12.6 mm, and increased by 28.9 mm during neap, middle, and spring tides in succession, respectively, compared with the preceding tidal regimes. The net erosion mainly resulted from large incident wave heights and the consequent strong offshore-directed sediment transport induced by undertows. Moreover, the variations in the bed level were more prominent during a neap to middle tides than during middle to spring tides, which were jointly caused by the wave-breaking probability regulated by water depth and the relative residence times of shoaling wave, breaker, and surf zones that were determined by relative tidal range. In terms of the intra-tidal bed level, it displayed an intra-tidal tendency of increase during floods and decrease during ebb tides, i.e., the intra-tidal bed level changes were controlled by water depth, which modulated the effects of waves on sediment resuspension and vertical sediment exchange. To be specific, waves and SSC were responsible for the intra-tidal bed level changes under low-energy wave conditions, while mean current and bedform exerted important influences on the variations of the intra-tidal bed level under moderate wave conditions, which broke the foregoing interrelation between bed level, waves, and SSC. This study, therefore, emphasizes the usage of ADV measurement to investigate bed level changes in sandy coasts.

Meng Xia, Tom Carruthers, Richard Kindong et al.

Fisheries researchers have focused on the value of information (VOI) in fisheries management and trade-offs since scientists and managers realized that information from different resources has different contribution in the management process. We picked seven indicators, which are log-normal annual catch observation error (Cobs), annual catch observation bias (Cbias), log-normal annual index observation error (Iobs), maximum length observation bias (Linfbias), observed natural mortality rate bias (Mbias), observed von Bertalanffy growth parameter K bias (Kbias), and catch-at-age sample size (CAA_nsamp), and built operating models (OMs) to simulate fisheries dynamics, and then applied management strategy evaluation (MSE). Relative yield is chosen as the result to evaluate the contribution of the seven indicators. Within the parameter range, there was not much information value reflected from fisheries-dependent parameters including Cobs, Cbias, and Iobs. On the other hand, for fisheries-independent parameters such as Kbias, Mbias, and Linfbias, similar tendency of the information value was showed in the results, in which the relative yield goes down from the upper bound to the lower bound of the interval. CAA_nsamp had no impact on the yield after over 134 individuals. The VOI analysis contributes to the trade-offs in the decision-making process. Information with more value is more worthy to collect in case of waste of time and money so that we could make the best use of scientific effort. But we still need to improve the simulation process such as enhancing the diversity and predictability in an OM. More parameters are on the way to be tested in order to collect optimum information for management and decision-making.

Kerry-Ann van der Walt, Kerry-Ann van der Walt, Warren M. Potts et al.

Climate change not only drives increases in global mean ocean temperatures, but also in the intensity and duration of marine heatwaves (MHWs), with potentially deleterious effects on local fishes. A first step to assess the vulnerability of fishes to MHWs is to quantify their upper thermal thresholds and contrast these limits against current and future ocean temperatures during such heating events. Heart failure is considered a primary mechanism governing the upper thermal limits of fishes and begins to occur at temperatures where heart rate fails to keep pace with thermal dependency of reaction rates. This point is identified by estimating the Arrhenius breakpoint temperature (TAB), which is the temperature where maximum heart rate (fHmax) first deviates from its exponential increase with temperature and the incremental Q10 breakpoint temperature (TQB), which is where the Q10 temperature coefficient (relative change in heart rate for a 10°C increase in temperature) for fHmax abruptly decreases during acute warming. Here we determined TAB, TQB and the temperature that causes cardiac arrhythmia (TARR) in adults of the marine sparid, Diplodus capensis, using an established technique. Using these thermal indices results, we further estimated adult D. capensis vulnerability to contemporary MHWs and increases in ocean temperatures along the warm-temperate south-east coast of South Africa. For the established technique, we stimulated fHmax with atropine and isoproterenol and used internal heart rate loggers to measure fHmax under conditions of acute warming in the laboratory. We estimated average TAB, TQB, and TARR values of 20.8°C, 21.0°C, and 28.3°C. These findings indicate that the physiology of D. capensis will be progressively compromised when temperatures exceed 21.0°C up to a thermal end-point of 28.3°C. Recent MHWs along the warm-temperate south-east coast, furthermore, are already occurring within the TARR threshold (26.6–30.0°C) for cardiac function in adult D. capensis, suggesting that this species may already be physiologically compromised by MHWs. Predicted increases in mean ocean temperatures of a conservative 2.0°C, may further result in adult D. capensis experiencing more frequent MHWs as well as a contraction of the northern range limit of this species as mean summer temperatures exceed the average TARR of 28.3°C.

Mark M. Dekker

Railway systems provide pivotal support to modern societies, making their efficiency and robustness important to ensure. However, these systems are susceptible to disruptions and delays, leading to accumulating economic damage. The large spatial scale of delay spreading typically make it difficult to distinguish which regions will ultimately affected from an initial disruption, creating uncertainty for risk assessment. In this paper, we identify geographical structures that reflect how delay spreads through railway networks. We do so by proposing a graph-based, hybrid schedule and empirical-based model for delay propagation and apply spectral clustering. We apply the model to four European railway systems: the Netherlands, Germany, Switzerland and Italy. We characterize geographical structures in the railway systems of these countries and interpret these regions in terms of delay severity and how dynamically disconnected they are from the rest. The method also allows us to point out important differences between these countries' railway systems. For practitioners, this geographical characterization of railways provide natural boundaries for local decision-making structures and a first-order prioritization on which regions are at risk, given an initial disruption.

Kirsty A. McQuaid, Martin J. Attrill, Malcolm R. Clark et al.

Extractive activities in the ocean are expanding into the vast, poorly studied deep sea, with the consequence that environmental management decisions must be made for data-poor seafloor regions. Habitat classification can support marine spatial planning and inform decision-making processes in such areas. We present a regional, top–down, broad-scale, seafloor-habitat classification for the Clarion-Clipperton Fracture Zone (CCZ), an area targeted for future polymetallic nodule mining in abyssal waters in the equatorial Pacific Ocean. Our classification uses non-hierarchical, k-medoids clustering to combine environmental correlates of faunal distributions in the region. The classification uses topographic variables, particulate organic carbon flux to the seafloor, and is the first to use nodule abundance as a habitat variable. Twenty-four habitat classes are identified, with large expanses of abyssal plain and smaller classes with varying topography, food supply, and substrata. We then assess habitat representativity of the current network of protected areas (called Areas of Particular Environmental Interest) in the CCZ. Several habitat classes with high nodule abundance are common in mining exploration claims, but currently receive little to no protection in APEIs. There are several large unmanaged areas containing high nodule abundance on the periphery of the CCZ, as well as smaller unmanaged areas within the central CCZ, that could be considered for protection from mining to improve habitat representativity and safeguard regional biodiversity.

Dino Osmanovic

Certain types of active systems can be treated as an equilibrium system with excess non-conservative forces driving some of the microscopic degrees of freedom. We derive results for how many particles interacting with each other with both conservative and non-conservative forces will behave. Treating non-conservative forces perturbatevily, we show how the probability distribution of the microscopic degrees of freedom is modified from the Boltzmann distribution. We compare the perturbative expansion to an exactly solvable non-conservative system. We then derive approximate forms of this distribution through analyzing the nature of our perturbations. Finally, we consider how the approximate forms for the microscopic distributions we have derived lead to different macroscopic states when coarse grained, and compare it qualitatively to simulation of non-conservatively interacting particles. In particular we note by introducing non-conservative interactions between particles we modify densities through extra terms which couple to surfaces

Paolo Casula

The Great Capricorn beetle, Cerambyx cerdo, and Mediterranean oak habitats (Quercus ilex – 9340 and Quercus suber – 9330) are protected by the Habitats Directive (HD). However, in the Mediterranean basin, these habitats are also traditionally used for animal, wood, and cork productions. Cerambyx cerdo feeds into the wood of trees and can be perceived by forest practitioners as an umbrella species or as a pest, depending on the context. Monitoring programmes involving forest practitioners could thus focus on assessing: 1) the conservation status of the Great Capricorn beetle and habitats (distribution and abundance of insects and reproductive sites or colonised trees), 2) pest status, and 3) management options to achieve both conservational and economic benefits. Considering that Cerambyx cerdo and Cork and Holm oak forests are not priority species or habitats under the HD, targeted funding is likely to be limited for monitoring. In this context, citizen science could gather important information on the target species useful for the monitoring programmes and management. To address management questions, the citizen science based programme for Cerambyx cerdo monitoring and habitat conservation should be seen not only as citizens collecting good data sets, but also as a deeper collaboration amongst different knowledge bodies and perspectives within a community – based environmental monitoring and learning network.