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

P. Attiwill

Shaochun Xu, Shaochun Xu, Shaochun Xu et al.

Under accelerating coastal eutrophication, disentangling the relative roles of light limitation and nitrogen enrichment is essential for diagnosing seagrass decline. We conducted a fully crossed light × ammonium experiment using intact Zostera marina cores from Guzhenkou Bay (4 irradiance levels: 180, 90.6, 17, 0 μmol photons m-2 s-1; 4 NH4Cl levels: 0, 25, 50, 100 μmol L-1; 5 weeks; 16 units; no within-cell replication). Across traits, irradiance—not NH4Cl within the tested range—governed responses at the level of dominant main effects. Shading sharply reduced shoot density, above- and below-ground biomass (AGB, BGB) and Fv/Fm, with near-complete collapse at darkness. Biomass turnover accelerated under shading (higher above-ground shedding, below-ground mass loss), and below-ground carbon content declined, together indicating a shift from carbon accrual to expenditure. By contrast, NH4Cl enrichment showed minimal main effects on morphology, pigments, Fv/Fm, or antioxidant enzymes, although tissue δ15N decreased with NH4Cl addition, evidencing ammonium assimilation. Antioxidant responses were variable (POD increased with reduced irradiance; SOD, CAT, GSH-Px inconsistent), while MDA did not increase under shading and was occasionally higher under high light, consistent with lower photo-oxidative load at low irradiance. Leaf and rhizome δ13C showed no significant treatment effects and only a weak, non-significant tendency toward less negative values under severe shading. Collectively, the trait suite diagnoses light-driven carbon limitation as the proximal stressor, with nitrogen effects contingent on concentration and context. We recommend tiered monitoring that couples rapid photophysiology (Fv/Fm) with structural (shoot density, AGB/BGB) and integrative biogeochemical indicators (below-ground C; δ-isotopes), and management focused on water clarity to meet species-specific light requirements.

Zihao Shi, Dongling Wang

Neural networks have demonstrated significant potential in solving partial differential equations (PDEs). While global approaches such as Physics-Informed Neural Networks (PINNs) offer promising capabilities, they often lack inherent temporal causality, which can limit their accuracy and stability for time-dependent problems. In contrast, local training frameworks that progressively update network parameters over time are naturally suited for evolving PDEs. However, a critical challenge remains: many physical systems possess intrinsic invariants -- such as energy or mass -- that must be preserved to ensure physically meaningful solutions. This paper addresses this challenge by enhancing the Time-Evolving Natural Gradient (TENG) method, a recently proposed local training framework. We introduce two complementary techniques: (i) a relaxation algorithm that ensures the target solution $u_{\text{target}}$ preserves both quadratic and general nonlinear invariants of the original system, providing a structure-preserving learning target; and (ii) a projection technique that maps the updated network parameters $θ(t)$ back onto the invariant manifold, ensuring the final neural network solution strictly adheres to the conservation laws. Numerical experiments on the inviscid Burgers equation, Korteweg-de Vries equation, and acoustic wave equation demonstrate that our proposed approach significantly improves conservation properties while maintaining high accuracy.

Yuye Zou, Xiaohui Wang, Qiang Zhang

This paper analyzes 441 of China's green port policies using text mining and quantitative evaluation methods to promote the sustainable development of China’s ports and accelerate the achievement of the “dual carbon” goal. The study first reviews the evolution of these policies, categorizing them into three stages: the embryonic stage, the startup stage, and the development stage. High-frequency words were extracted for each stage, followed by dimensionality reduction using Principal Component Analysis (PCA) and clustering analysis to classify the policies. The Latent Dirichlet Allocation (LDA) topic model was then applied to identify the main policy themes, and a Policy Modeling Consistency (PMC) index model was developed. The study evaluated 19 representative policies using cosine similarity and correlation coefficients. The analysis revealed several key issues: (1) the entity responsible for policy issuance is singular, with insufficient interdepartmental collaboration; (2) short-term policies are lacking, with weak responsiveness; (3) policies targeting shipping companies are underdeveloped; and (4) there is an imbalance in the use of policy instruments, with a focus on mandatory and hybrid tools. Based on these findings, the paper proposes several suggestions for improving green port development policies.

Xinyu Zheng, Yan Bai, Yan Bai et al.

IntroductionGlobal warming and glacier melt are transforming Southern Ocean ecosystems, profoundly affecting phytoplankton dynamics. This study investigates long-term phytoplankton changes in the Amundsen and Cosmonaut Seas, focusing on responses to climate-driven environmental shifts and the influence of the Southern Annular Mode (SAM).MethodsWe analyzed high-resolution (4 km, monthly averaged) satellite-derived chlorophyll-a (Chla) and net primary productivity (NPP) data from austral summers (2003–2020). Environmental parameters, including sea surface temperature (SST), photosynthetically active radiation (PAR) and wind speed (WS), sea ice concentration (SIC) and mixed layer depth (MLD), were examined to elucidate their roles in driving phytoplankton variability in the Amundsen and Cosmonaut Seas.ResultsDuring positive SAM phases, Chla and NPP generally increased across both seas, but local ocean circulation led to divergent subregional trends. North of the Southern Antarctic Circumpolar Front (sACCF) and within the Weddell Gyre, enhanced wind-driven MLD promoted Chla increases. In the northern Ross Gyre, cooling SST and deeper MLD intensified upwelling and nutrient, sustaining Chla growth, while shallower MLD and weaker upwelling in the eastern Ross Gyre reduced Chla. In coastal Amundsen Sea, warming SST facilitated sea ice melt, increasing Chla, whereas cooling SST in the Cosmonaut Sea and Prydz Bay increased SIC, reducing Chla.DiscussionThis high-resolution analysis highlights the complex interplay of physical and biological drivers in polar marine ecosystems, providing critical insights into climate change impacts on Southern Ocean phytoplankton dynamics and their regional variability.

Rémi Abgrall, Pierre-Henri Maire, Mario Ricchiuto

The purpose of this review is to discuss the notion of conservation in hyperbolic systems and how one can formulate it at the discrete level depending on the solution representation of the solution. A general theory is difficult. We discuss several possibilities: if the solution is represented by average in volumes; if the mesh is staggerred; if the solution is solely represented by point values and an example where all the previous options are mixed. We show how each configuration can provide, or not, enough flexibility. The discussion could be adapted to any hyperbolic system endowed with an entropy, but we focus on compressible fluid mechanics, in its Eulerian and Lagrangian formulations. The unifying element is that we systematically express the update of conserved variables as $u^{n+1}=u^n- Δt\; δu$, where the functional $δu$ depends on the value of $u$ in the stencil of the scheme. Then, one can naturally define a graph connecting the states defining $δu$. The notion of local conservation can be defined from this graph. We are aware of only two possible situations: either the graph is constructed from the faces of the mesh elements (or the dual mesh), or it is defined from the mesh itself. Two notions of local conservation then emerge: either we define a numerical flux, or we define a "residual" attached to elements and the degrees of freedom within the element. We show that this two notions are in a way equivalent, but the one with residual allows much more flexibility, especially if additional algebraic constraints must be satisfied. Examples of specific additional conservation constraints are provided to illustrate this. We also show that this notion of conservation gives a very clear framework for the design of scheme in the Lagrangian framework. We end by providing a number of ongoing research questions, and highlight some open questions.

Yuhao Jiang, Junfeng Qiao, Nataliya Paulish et al.

Maximally-localized Wannier functions (MLWFs) are widely employed as an essential tool for calculating the physical properties of materials due to their localized nature and computational efficiency. Projectability-disentangled Wannier functions (PDWFs) have recently emerged as a reliable and efficient approach for automatically constructing MLWFs that span both occupied and lowest unoccupied bands. Here, we extend the applicability of PDWFs to magnetic systems and/or those including spin-orbit coupling, and implement such extensions in automated workflows. Furthermore, we enhance the robustness and reliability of constructing PDWFs by defining an extended protocol that automatically expands the projectors manifold, when required, by introducing additional appropriate hydrogenic atomic orbitals. We benchmark our extended protocol on a set of 200 chemically diverse materials, as well as on the 40 systems with the largest band distance obtained with the standard PDWF approach, showing that on our test set the present approach delivers a 100% success rate in obtaining accurate Wannier-function interpolations, i.e., an average band distance below 15 meV between the DFT and Wannier-interpolated bands, up to 2 eV above the Fermi level.

Matteo Straccamore, Matteo Bruno, Andrea Tacchella

Debates over the trade-offs between specialization and diversification have long intrigued scholars and policymakers. Specialization can amplify an economy by concentrating on core strengths, while diversification reduces vulnerability by distributing investments across multiple sectors. In this paper, we use patent data and the framework of Economic Complexity to investigate how the degree of technological specialization and diversification affects economic development at different scales: metropolitan areas, regions and countries. We examine two Economic Complexity indicators. Technological Fitness assesses an economic player's ability to diversify and generate sophisticated technologies, while Technological Coherence quantifies the degree of specialization by measuring the similarity among technologies within an economic player's portfolio. Our results indicate that a high degree of Technological Coherence is associated with increased economic growth only at the metropolitan area level, while its impact turns negative at larger scales. In contrast, Technological Fitness shows a U-shaped relationship with a positive effect in metropolitan areas, a negative influence at the regional level, and again a positive effect at the national level. These findings underscore the complex interplay between technological specialization and diversification across geographical scales. Understanding these distinctions can inform policymakers and stakeholders in developing tailored strategies for technological advancement and economic growth.

Jose Carlos Báez

Song Zhao, Long Wang, Lujie Song et al.

Accurate identification of coastal hyperspectral remote sensing targets plays a significant role in the observation of marine ecosystems. Deep learning is currently widely used in hyperspectral recognition. However, most deep learning methods ignore the complex correlation and data loss problems that exist between features at different scales. In this study, Multi-scale attention reconstruction convolutional network (MARCN) is proposed to address the above issues. Firstly, a multi-scale attention mechanism is introduced into the network to optimize the feature extraction process, enabling the network to capture feature information at different scales and improve the target recognition performance. Secondly, the reconstruction module is introduced to fully utilize the spatial and spectral information of hyperspectral imagery, which effectively solves the problem of losing spatial and spectral information. Finally, an adaptive loss function, coupling cross-entropy loss, center loss, and feature space loss is used to enable the network to learn the feature representation and improve the accuracy of the model. The experimental results showed that the effectiveness of MARCN was validated with a recognition rate of 96.62%, and 97.92% on the YRE and GSOFF datasets.

Dominique Ghijselinck

Igor V. Karyakin, Elvira G. Nikolenko, Elena P. Shnayder

The range and abundance of Saker Falcon (Falco cherrug) in Russia and Kazakhstan are systematically declining. It is no exaggeration to say that the Saker Falcon is by far the most endangered raptor species in the Palaearctic. A compilation of literature data shows the species’ estimated abundance in 1970s Russia was at least 9,000–10,000 pairs (Galushin, 2004; Karyakin, 2008), while it appears over 15,000 pairs nested in Kazakhstan – in the 1990s their abundance there was estimated at 5,218 (4,808–5,628) pairs.

Shixuan Liu, Shixuan Liu, Shixuan Liu et al.

This research is motivated by the practical requirements in the sustainable deployment of ocean moored buoy observing networks. Ocean moored buoys play an important role in the global marine environment monitoring. Ocean buoy station layout planning is a typical multiple-objective spatial optimization problem that aims to reduce the spatial correlation of buoy stations and improve their spatial monitoring efficiency. In this paper, we develop a multi-objective mathematical model for allocating ocean buoy stations (MOLMofOBS) based on Tobler’s first law of geography. A spatial neighborhood model based on a Voronoi diagram is built to represent the spatial proximity of distributed buoy stations and delimit the effective monitoring region of every station. Then, a heuristic method based on a multiple-objective particles swarm optimization (MOPSO) algorithm is developed to calculate the MOLMofOBS via a dynamic inertia weight strategy. Meanwhile, a series of experiments is conducted to verify the efficiency of the proposed model and algorithms in solving single- and multiple-buoy station location problems. Finally, an interactive portal is developed in the Cyberinfrastructure environment to provide decision-making services for online real-time planning of the ocean buoy station locations. The work reported in this paper will provide spatial decision-making support for the sustainable development of ocean buoy observing networks.

Tianyu Wang, Jiashuo Liu, Peng Cui et al.

Different distribution shifts require different interventions, and algorithms must be grounded in the specific shifts they address. However, methodological development for robust algorithms typically relies on structural assumptions that lack empirical validation. Advocating for an empirically grounded data-driven approach to algorithm development, we build an empirical testbed comprising natural shifts across 8 tabular datasets, 172 distribution pairs over 45 methods and 90,000 method configurations encompassing empirical risk minimization and distributionally robust optimization (DRO) methods. We find $Y|X$-shifts are most prevalent in our testbed, in stark contrast to the heavy focus on $X$ (covariate)-shifts in the ML literature, and that the performance of robust algorithms is no better than that of vanilla methods. To understand why, we conduct an in-depth empirical analysis of DRO methods and find that underlooked implementation details -- such as the choice of underlying model class (e.g., LightGBM) and hyperparameter selection -- have a bigger impact on performance than the ambiguity set or its radius. We illustrate via case studies how a data-driven, inductive understanding of distribution shifts can provide a new approach to algorithm development.

Alejandro D. Owen Aquino, Samuel Talkington, Daniel K. Molzahn

Combinatorial distribution system optimization problems, such as scheduling electric vehicle (EV) charging during evacuations, present significant computational challenges. These challenges stem from the large numbers of constraints, continuous variables, and discrete variables, coupled with the unbalanced nature of distribution systems. In response to the escalating frequency of extreme events impacting electric power systems, this paper introduces a method that integrates sample-based conservative linear power flow approximations (CLAs) into an optimization framework. In particular, this integration aims to ameliorate the aforementioned challenges of distribution system optimization in the context of efficiently minimizing the charging time required for EVs in urban evacuation scenarios.

M. Niemiller, Mark A. Davis, Milton Tan et al.

Cryptic species present particular challenges to biodiversity conservation, as true species diversity and distributional boundaries remain obscured. However, modern molecular tools have afforded unparalleled opportunities to elucidate cryptic species, define their distributions, and, ultimately, develop conservation interventions to extend their evolutionary trajectories into the future. The Green Salamander (Aneides aeneus) complex provides an evolutionary focal point and the Appalachian Highlands an ecological context for the exploration of cryptic speciation in an imperiled taxon. A recent study uncovered significant levels of genetic and genomic variation geographically structured across the Appalachian Highlands, including up to four lineages, one of which (A. caryaensis) was described therein. Here we extend the genetic and genomic examination of the Castaneides species complex by intensive sampling of additional populations along Cumberland Plateau and Appalachian Valley and Ridge of Alabama and Tennessee, employing both mtDNA and RADseq species delimitation approaches to delineate cryptic diversity and boundaries in this region. Analyses of two mitochondrial loci (nd4 and cytb) identified two reciprocally monophyletic lineages, which are also supported by population clustering and phylogenetic analyses of SNPs, that identified two population clusters with no evidence of gene flow. Our genetic and genomic results support the recognition of two additional cryptic lineages in the Castaneides species complex. Ultimately, this information is critical in developing successful adaptive management strategies for this important and endemic component of Appalachian Highland biodiversity.

Deepti M. Patel, Monica F. Brinchmann, Anna Hanssen et al.

Lumpfish (Cyclopterus lumpus L) is a North Atlantic species harvested for its roe and increasingly used as a cleanerfish in Atlantic salmon (Salmo salar L.) farming to remove salmon louse (Lepeophtheirus salmonis). In aquaculture, the health and welfare of fish depends on optimal levels of several biotic and abiotic factors. Crowding, a common abiotic stress factor in aquaculture practice, can affect the welfare and survival of fish. In this study, lumpfish was exposed to crowding stress daily at random timepoints for one month (stress group) or no crowding (control group). Blood and skin were sampled weekly for physiological parameter analysis and proteomics, respectively. Adrenocorticotropic hormone (ACTH) stimulation and dexamethasone (DEX) suppression test were conducted at the sampling timepoints. Gel-based proteomics coupled with liquid chromatography and tandem mass spectrometry (LC-MS/MS) was used to identify protein changes in skin tissues of lumpfish under crowding. The results indicated that the stress group showed signs of allostatic overload type 2 (chronic stress) due to oversensitivity to ACTH, and a reduced negative feedback system with increased baseline levels of cortisol. These chronic changes in the endocrine system promoted changes in secondary and tertiary stress responses as reduced osmoregulatory capacity and stunted growth, after 14 days of stress and onward. Calmodulin, guanine nucleotide binding protein subunit beta 2, glutathione-S-transferase Mu 3, fatty acid binding protein, heat shock cognate 70 kDa protein, keratin, histone H4 and 14-3-3 alpha/beta showed protein spot intensity changes compared with controls in lumpfish skin at one or several time points during the one month period of crowding stress. The differentially expressed proteins are related to several metabolic pathways and are involved in stress and immune responses. Overall, the study shows that lumpfish can suffer from chronic stress with possible dire consequences for the animal welfare.

Liu Lihong, Jiang Peng, Wen Yongshuai

[Objective] The influence of water-related structures on the flood routing process before and after structure construction was analyzed to provide scientific supports for the real and efficient calculation of bridge engineering in flood storage and detention areas, and for the effective development of flood control in flood storage areas. [Methods] The Mengwa flood storage area in Fuyang City, Anhui Province was selected as the study area. Based on the latest data of regional topography, hydrological data, and bridge engineering design, the unstructured hydrodynamic model of MIKE 21 was used to simulate the flood evolution process of the Mengwa flood storage area in real time. The influence of bridge construction on flood evolution time, velocity distribution, and water level change in the flood storage and detention area was analyzed. [Results] After the construction of the bridge project, the flood-splitting time near the bridge position was 45 s behind the maximum lag before the construction of the project; the flow rate distribution range of the mainstream area was 0.4 to 0.6 m/s; the local velocity change rate was 7.409%; the maximum elevation value of the water level near the bridge was 0.006 m; and the maximum change rate of the water level was -0.22‰. [Conclusion] Bridge construction delayed the flooding time in the flood storage area, raised the water level near the pier, and changed the distribution of the flow rate near the project. However, the overall impact on the flood storage area was small, and basically did not affect the normal operation of the flood storage area.

Chengcheng Shen, Chengcheng Shen, Hong Cheng et al.

Hexactinellid sponges often form structural habitats for other organisms and thus support high biodiversity. Two representative morphotypes of hexactinellid sponges were sampled by a remotely operated vehicle along a transect (depths of 2377–2758 m) on the Ko-Hakucho Guyot in the northwestern Pacific Ocean, both new to science. One new species, Flavovirens hemiglobus gen. et sp. nov., which is pedunculate and bears the main choanosomal spicules of diactins, is clearly attributed to the euplectellid subfamily Bolosominae. Its set of microscleres present (namely, predominating oxyhexasters and discasters, and rare discohexasters and staurodiscs) characterizes it as a new genus. The other new species, Chonelasma tyloscopulatum sp. nov., which is funnel in form without dichotomous branching tubes or lateral oscula and has firm body walls supported by a three-layered dictyonal framework, is clearly attributed to the euretid genus Chonelasma (subfamily Chonelasmatinae). Its presence of surface pentactins, two types of scopules, and both oxy- and disco-tipped hexasters or hemihexasters as common microscleres, characterizes it as a new species. The placements are also supported by molecular phylogenetic evidence from nuclear 18S rDNA and 28S rDNA, and mitochondrial 16S rDNA and cytochrome c oxidase subunit I (COI) gene. More sampling efforts should be conducted to improve the understanding of the biodiversity of deep-sea seamount sponges.

Daniel S. Cooper, Eric M. Wood, Nurit D Katz et al.

Urbanization is a major driver of global species loss. While cities with suitable habitats and conservation policies may support locally-high biodiversity levels, we suspected that the complexity of managing very large cities might counteract the advantage of large geographic area, and these cities may be less effective at biodiversity conservation. To answer this, we examined the relationship between the number of native indicator wildlife species (mean and maximum) in 112 cities across three metropolitan areas in California (Los Angeles, San Diego, and San Jose), with metrics related to scale and environmental variables. We found that indicator species richness is positively related to area, income (the luxury effect), and pervious cover—including trees, shrubs, and grasses. Despite having a high maximum number of indicator species within their boundaries, the largest cities in our study, Los Angeles, San Jose, and San Diego, do a relatively poor job compared with smaller cities at distributing native biodiversity throughout neighborhoods, as measured by their mean species richness. Such variation in “neighborhood biodiversity” may exacerbate existing inequities in residents' access to nature. Using Los Angeles County as a case study, we compared biodiversity management within the County's 88 cities of various sizes and characteristics. We ranked General Plan wording in terms of references to biodiversity and conservation and created a management metric. We found that municipalities of various sizes that had high management scores generally had high indicator species richness. This suggests that robust policies may be able to overcome the challenges posed by city size and population.