Abiotic factors play an important role in species localisation,but biotic and anthropogenic predictors must also be considered in distribution modelling for models to be biologically meaningful.In this study,we formal...Abiotic factors play an important role in species localisation,but biotic and anthropogenic predictors must also be considered in distribution modelling for models to be biologically meaningful.In this study,we formalised the biotic predictors of nesting sites for four threatened Caucasian vultures by including species distribution models(wild ungulates,nesting tree species)as biotic layers in the vulture Maxent models.Maxent was applied in the R dismo package and the best set of the model parameters were defined in the R ENMeval package.Performance metrics were continuous Boyce index,Akaike's information criterion,the area under receiver operating curve and true skill statistics.We also calculated and evaluated the null models.Kernel density estimation method was applied to assess the overlap of vulture ecological niches in the environmental space.The accessibility of anthropogenic food resources was estimated using the Path Distance measure that considers elevation gradient.The availability of pine forests(Scots Pine)and wild ungulates(Alpine Chamois and Caucasian Goat)contributed the most(29.6%and 34.3%)to Cinereous Vulture(Aegypius monachus)nesting site model.Wild ungulate distribution also contributed significantly(about 46%)to the Bearded Vulture(Gypaetus barbatus)model.This scavenger nests in the highlands of the Caucasus at a minimum distance of 5–10 km from anthropogenic facilities.In contrast,livestock as a food source was most important in colony distribution of Griffon Vulture(Gyps fulvus).The contribution of distances to settlements and agricultural facilities to the model was 45%.The optimal distance from Egyptian Vulture(Neophron percnopterus)nesting sites to settlements was only 3–10 km,to livestock facilities no more than 15 km with the factor contribution of about 57%.Excluding the wild ungulate availability,the ecological niches of studied vultures overlapped significantly.Despite similar foraging and nesting requirements,Caucasian vultures are not pronounced nesting and trophic competitors due to the abundance of nesting sites,anthropogenic food sources and successful niche sharing.展开更多
Species distribution models have been widely used to explore suitable habitats of species,the impact of climate change on the distribution of suitable habitats of species,and the construction of ecological reserves.Th...Species distribution models have been widely used to explore suitable habitats of species,the impact of climate change on the distribution of suitable habitats of species,and the construction of ecological reserves.This paper introduced species distribution models commonly used in biodiversity analysis,as well as model performance evaluation indexes,challenges in the application of species distribution models,and finally prospected the development trend of research on species distribution models.展开更多
As our understanding of ecology deepens and modeling techniques advance,species distribution models have grown increasingly sophisticated,enhancing both their fitting and predictive capabilities.However,the dependabil...As our understanding of ecology deepens and modeling techniques advance,species distribution models have grown increasingly sophisticated,enhancing both their fitting and predictive capabilities.However,the dependability of predictive accuracy remains a critical issue,as the precision of these predictions largely hinges on the quality of the base data.We developed models using both field survey and remote sensing data from 2016 to 2020 to evaluate the impact of different data sources on the accuracy of predictions for Scomber japonicus distributions.Our research findings indicate that the variability of water temperature and salinity data from field suvery is significantly greater than that from remote sensing data.Within the same season,we found that the relationship between the abundance of S.japonicus and environmental factors varied significantly depending on the data source.Models using field survey data were able to more accurately reflect the complex relationships between resource distribution and environmental factors.Additionally,in terms of model predictive performance,models based on field survey data demonstrated greater accuracy in predicting the abundance of S.japonicus compared to those based on remote sensing data,allowing for more accurate mastery of their spatial distribution characteristics.This study highlights the significant impact of data sources on the accuracy of species distribution models and offers valuable insights for fisheries resources management.展开更多
Biological invasions represent one of the main anthropogenic drivers of global change with a substantial impact on biodi-versity.Traditional studies predict invasion risk based on the correlation between species’dist...Biological invasions represent one of the main anthropogenic drivers of global change with a substantial impact on biodi-versity.Traditional studies predict invasion risk based on the correlation between species’distribution and environmental factors,with little attention to the potential contribution of physiological factors.In this study,we incorporated temperature-dependent sex determination(TSD)and sex-ratio data into species distribution models(SDMs)to assess the current and future suitable habitats for the world’s worst invasive reptile species,the pond slider turtle(Trachemys scripta).First,occur-rence records of T.scripta from online databases and published scientific literature were identified.Then,climatic variables representing current(1976-2013)and future(2060-2080)climate scenarios were extracted and combined with sex-ratio records to create hybrid-SDMs with which to assess the current and future suitable habitats for T.scripta.It was found that T.scripta has potential suitable habitat in 136 countries at present.Under the four climate change scenarios(ssp126,ssp245,ssp370 and ssp585)that were modeled,the distribution of T.scripta is predicted to decrease in 78-93 countries but increase in the northern hemisphere.This confirms that there is a greater likelihood that this species will increase in more developed countries.Incorporating the thermal dependence of sex ratio into hybrid-SDMs can be an important addition to detect the invasion risk of TSD species and to develop region-specific invasion management strategies to prevent and/or control invasive species such as T.scripta.展开更多
Giant kelp Macrocystis pyrifera,an important foundation species with great ecological and economic value,is threatened by climate change.To better understand the impact of climate warming on M.pyrifera,we investigated...Giant kelp Macrocystis pyrifera,an important foundation species with great ecological and economic value,is threatened by climate change.To better understand the impact of climate warming on M.pyrifera,we investigated its global distribution dynamics by an optimized species distribution model(SDM).Results showed that wave height,sea surface temperature,benthic temperature,and benthic phosphate concentration were key factors shaping the distribution of M.pyrifera.In addition to currently known distribution regions,the model revealed potential suitable habitats globally.Under future climate scenarios,the habitat suitability of M.pyrifera would decrease at low latitudes and increase at high latitudes,resulting in a poleward shift of suitable habitats.In the regions currently occupied by M.pyrifera,the high suitable habitats were predicted to shrink,which implies that the existing M.pyrifera would be adversely impacted.These results serve as references for the conservation and utilization of M.pyrifera resource.展开更多
Predictive studies play a crucial role in the study of biological invasions of terrestrial plants under possible climate change scenarios.Invasive species are recognized for their ability to modify soil microbial comm...Predictive studies play a crucial role in the study of biological invasions of terrestrial plants under possible climate change scenarios.Invasive species are recognized for their ability to modify soil microbial communities and influence ecosystem dynamics.Here,we focused on six species of allelopathic flowering plants-Ailanthus altissima,Casuarina equisetifolia,Centaurea stoebe ssp.micranthos,Dioscorea bulbifera,Lantana camara,and Schinus terebinthifolia-Xhat are invasive in North America and examined their potential to spread further during projected climate change.We used Species Distribution Models(SDMs)to predict future suitable areas for these species in North America under several proposed future climate models.ENMEval and Maxent were used to develop SDMs,estimate current distributions,and predict future areas of suitable climate for each species.Areas with the greatest predicted suitable climate in the future include the northeastern and the coastal northwestern regions of North America.Range size estimations demonstrate the possibility of extreme range loss for these invasives in the southeastern United States,while new areas may become suitable in the northeastern United States and southeastern Canada.These findings show an overall northward shift of suitable climate during the next few decades,given projected changes in temperature and precipitation.Our results can be utilized to analyze potential shifts in the distribution of these invasive species and may aid in the development of conservation and management plans to target and control dissemination in areas at higher risk for potential future invasion by these allelopathic species.展开更多
Correlative species distribution models(SDMs)are important tools to estimate species’geographic distribution across space and time,but their reliability heavily relies on the availability and quality of occurrence da...Correlative species distribution models(SDMs)are important tools to estimate species’geographic distribution across space and time,but their reliability heavily relies on the availability and quality of occurrence data.Estimations can be biased when occurrences do not fully represent the environmental requirement of a species.We tested to what extent species’physiological knowledge might influence SDM estimations.Focusing on the Japanese sea cucumber Apostichopus japonicus within the coastal ocean of East Asia,we compiled a comprehensive dataset of occurrence records.We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs:a naïve model that solely depends on environmental correlates,and a physiologically informed model that further incorporates physiological information as priors.We further tested the models’sensitivity to calibration area choices by fitting them with different buffered areas around known presences.Compared with naïve models,the physiologically informed models successfully captured the negative influence of high temperature on A.japonicus and were less sensitive to the choice of calibration area.The naïve models resulted in more optimistic prediction of the changes of potential distributions under climate change(i.e.,larger range expansion and less contraction)than the physiologically informed models.Our findings highlight benefits from incorporating physiological information into correlative SDMs,namely mitigating the uncertainties associated with the choice of calibration area.Given these promising features,we encourage future SDM studies to consider species physi-ological information where available.展开更多
Three common species of Miniopterus fuliginosus,M.magnater and M.pusillus are known to inhabit China.However,M.fuliginosus and M.magnater are so similar in external morphology as to pose great challenges for accurate ...Three common species of Miniopterus fuliginosus,M.magnater and M.pusillus are known to inhabit China.However,M.fuliginosus and M.magnater are so similar in external morphology as to pose great challenges for accurate classification.Furthermore,taxonomic statuses,distribution ranges and taxonomic keys of these three species have remained controversial.For addressing these outstanding issues,the authors integrated molecular phylogenetic analyses,ensemble species distribution models(ESDMs),multiple morphological comparisons and decision tree algorithms for reassessing their taxonomy and distribution in China.Mitochondrial cytochrome c oxidase subunit I(COI)gene phylogeny revealed three distinct monophyletic groups corresponding to M.fuliginosus,M.magnater and M.pusillus.And the observed distribution patterns indicated M.fuliginosus had a broad distribution across China while M.magnater and M.pusillus exhibited a more restricted distribution,overlapping with M.fuliginosus in South China.And cranial morphometry indicated M.magnater was slightly larger than M.fuliginosus and significantly larger than M.pusillus.Also three-dimensional(3D)skull geomorphometry uncovered distinct features for each species in rostrum,braincase,tympanic bullae and mandibular shape.Decision tree algorithms helped to identify forearm length,braincase breadth and width across the third upper molars as three major taxonomic keys for assisting species identification.This study corroborated the importance of integrative approaches for identifying Miniopterus species and validated a methodological approach applicable to other cryptic species complexes.展开更多
Medicinal plant diversity(MPD)is an indispensable part of global plant diversity,serving as the foundation for human survival by offering remedies and preventive measures against diseases.However,factors such as overe...Medicinal plant diversity(MPD)is an indispensable part of global plant diversity,serving as the foundation for human survival by offering remedies and preventive measures against diseases.However,factors such as overexploitation,competition from invasive alien species,and climate change,threaten the habitats of medicinal plants,necessitating a comprehensive understanding of their spatial distribution and suitable habitats.We leveraged a decade of field survey data on medicinal plant distribution in the Yinshan Mountains,combined with spatial analysis,species distribution modeling,and the Carnegie Ames Stanford Approach(CASA)to explore the MPD spatial distribution and suitable habitats.Spatial analysis revealed that the central and eastern parts of Yinshan Mountains were the primary MPD hotspots,with no cold spots evident at various spatial scales.As the spatial scale decreased,previous non-significant regions transformed into hotspots,with instances where large-scale hotspots became insignificant.These findings offer valuable guidance for safeguarding and nurturing MPD across diverse spatial scales.In future climate change scenarios within the shared socioeconomic pathways(SSP),the habitat suitability for MPD in the Yinshan Mountains predominantly remains concentrated in the central and eastern regions.Notably,areas with high net primary productivity(NPP)values and abundant vegetation coverage align closely with MPD habitat suitability areas,potentially contributing to the region's rich MPD.展开更多
Antarctic krill(Euphausia superba),widely distributes around Antarctica,is a key species supporting the biodiversity of the Southern Ocean ecosystem.The Commission for the Conservation of Antarctic Marine Living Resou...Antarctic krill(Euphausia superba),widely distributes around Antarctica,is a key species supporting the biodiversity of the Southern Ocean ecosystem.The Commission for the Conservation of Antarctic Marine Living Resources(CCAMLR)has thus managed the krill fishery according to a precautionary way.Currently,CCAMLR is making effort to develop a refined krill fishery management approach based on more solid science,which requires accurate predictions of krill distribution.To address this need,this study investigated the effects of algorithm and spatial resolution on the performance of Antarctic krill distribution modelling.We integrated acoustic data from 4 surveys conducted in the waters adjacent to the Antarctic Peninsula with 11 environmental variables characterizing krill prey conditions,water mass properties,and seafloor topography.These data were processed at 4 spatial resolutions(5,10,15,and 20 km)to fit distribution models using 4 algorithms:Random Forests(RF),Generalized Additive Models(GAM),Extreme Gradient Boosting(XGBoost),and Artificial Neural Networks(ANN).Model performance was assessed and compared in terms of goodness-of-fit and predictive accuracy.The results showed that RF achieved the highest predictive performance at most resolutions,whereas GAM performed best at the coarsest resolution(20 km).XGBoost closely following RF in accuracy and demonstrated robustness as evidenced by the highly consistent partial dependence curves across resolutions.In contrast,ANN exhibited limitations with smaller sample sizes,resulting in comparatively poorer predictive performance.The analysis revealed a trade-off whereby reducing spatial resolution improved model fit and mitigated zero-inflation at the expense of fine-scale information and overall predictive accuracy.Ensemble models,integrating RF,GAM,and XGBoost,are proposed as potential balanced solutions to improve predictive stability,offering a more robust scientific basis for the refinement of krill management.展开更多
A chance-constrained energy dispatch model based on the distributed stochastic model predictive control(DSMPC)approach for an islanded multi-microgrid system is proposed.An ambiguity set considering the inherent uncer...A chance-constrained energy dispatch model based on the distributed stochastic model predictive control(DSMPC)approach for an islanded multi-microgrid system is proposed.An ambiguity set considering the inherent uncertainties of renewable energy sources(RESs)is constructed without requiring the full distribution knowledge of the uncertainties.The power balance chance constraint is reformulated within the framework of the distributionally robust optimization(DRO)approach.With the exchange of information and energy flow,each microgrid can achieve its local supply-demand balance.Furthermore,the closed-loop stability and recursive feasibility of the proposed algorithm are proved.The comparative results with other DSMPC methods show that a trade-off between robustness and economy can be achieved.展开更多
Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characterist...Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characteristic,rendering traditional distribution models and parameter estimation methods less effective.To address this,this paper proposes a dual compound-Gaussian model with inverse Gaussian texture(CG-IG)distribution model and combines it with an improved Adam algorithm to introduce a method for parameter correction.This method effectively fits sea clutter with heavy-tailed characteristics.Experiments with real measured sea clutter data show that the dual CGIG distribution model,after parameter correction,accurately describes the heavy-tailed phenomenon in sea clutter amplitude distribution,and the overall mean square error of the distribution is reduced.展开更多
Background: A number of conservation and societal issues require understanding how species are distributed on the landscape, yet ecologists are often faced with a lack of data to develop models at the resolution and e...Background: A number of conservation and societal issues require understanding how species are distributed on the landscape, yet ecologists are often faced with a lack of data to develop models at the resolution and extent desired, resulting in inefficient use of conservation resources.Such a situation presented itself in our attempt to develop waterfowl distribution models as part of a multi-disciplinary team targeting the control of the highly pathogenic H5N1 avian influenza virus in China.Methods: Faced with limited data, we built species distribution models using a habitat suitability approach for China's breeding and non-breeding(hereafter, wintering) waterfowl.An extensive review of the literature was used to determine model parameters for habitat modeling.Habitat relationships were implemented in GIS using land cover covariates.Wintering models were validated using waterfowl census data, while breeding models, though developed for many species, were only validated for the one species with sufficient telemetry data available.Results: We developed suitability models for 42 waterfowl species(30 breeding and 39 wintering) at 1 km resolution for the extent of China, along with cumulative and genus level species richness maps.Breeding season models showed highest waterfowl suitability in wetlands of the high-elevation west-central plateau and northeastern China.Wintering waterfowl suitability was highest in the lowland regions of southeastern China.Validation measures indicated strong performance in predicting species presence.Comparing our model outputs to China's protected areas indicated that breeding habitat was generally better covered than wintering habitat, and identified locations for which additional research and protection should be prioritized.Conclusions: These suitability models are the first available for many of China's waterfowl species, and have direct utility to conservation and habitat planning and prioritizing management of critically important areas, providing an example of how this approach may aid others faced with the challenge of addressing conservation issues with little data to inform decision making.展开更多
Selecting effective biological control agents(BCAs)is critical for managing invasive pests such as the tomato leafminer,Tuta absoluta,a species that has posed a significant agricultural threat in China since its recen...Selecting effective biological control agents(BCAs)is critical for managing invasive pests such as the tomato leafminer,Tuta absoluta,a species that has posed a significant agricultural threat in China since its recent invasion.Traditional selection methods prioritize climate matching but often overlook intrinsic biocontrol efficacy.This study proposes a novel spatially explicit framework that integrates climatic suitability and performance to determine effective BCAs.Using the CLIMEX model,we projected the climatic suitability of T.absoluta and four Trichogramma parasitoids(T.chilonis,T.dendrolimi,T.ostriniae,and T.pretiosum)across China.Crucially,we incorporated the pest kill rate(k_(m))to construct a Comprehensive Index(CI).Spatial projections derived from this parameter revealed a pronounced redistribution of dominant parasitoid species relative to climate-only predictions.T.ostriniae has emerged as the primary dominant agent across China's agricultural zones,including the North China Plain,Yangtze River Basin,Sichuan Basin,and Xinjiang's risk regions,replacing vast areas previously assigned to other parasitoid species under climate-matching models.Moreover,T.pretiosum remained dominant in subtropical southern China.This study demonstrated that integrating intrinsic biocontrol efficacy with climatic suitability significantly enhances the robustness of BCA selection,addressing critical limitations of climate-exclusive approaches.Our CI framework provides an evidence-based,spatially optimized strategy for the sustainable management of T.absoluta,prioritizing the targeted deployment of Trichogramma species in key agroecological zones.This methodology can be readily adapted to optimize biocontrol programs against globally invasive pests.展开更多
Nereididae is a prolific annelid family widely distributed in the world oceans,especially in the Indo-Pacific Convergence Zone(IPCZ).However,its biogeographic pattern remains unexplored in IPCZ.To contribute to the un...Nereididae is a prolific annelid family widely distributed in the world oceans,especially in the Indo-Pacific Convergence Zone(IPCZ).However,its biogeographic pattern remains unexplored in IPCZ.To contribute to the understanding of biodiversity and biogeography of Nereididae in the IPCZ,we integrated historical data of species distributions with those of model-predicted ones to determine the biogeographic patterns of nereid species,from which we projected to its future distribution patterns for 2090-2100 under different climate scenarios(SSP1-1.9 and SSP5-8.5).Functional diversity within IPCZ was assessed using functional richness,functional evenness,and functional disparity.Divergence times within Nereididae were estimated using three DNA marker genes(COI,16S,and 18S rRNA),and a time tree was constructed based on a strict molecular clock model.The IPCZ was established as a key Nereididae biodiversity hotspot through distribution modelling of 256 species(44 genera),and temperature emerging as the predominant climatic driver of species distribution patterns.The distribution of species and functional diversity is notable for its non-centralized pattern.We projected that by the end of the century,areas of medium-to-high species richness will expand significantly under the low-emission SSP1-1.9 climate scenario.However,under the high-emission SSP5-8.5 scenario,the suitability of these regions significantly declines,posing an increasingly severe threat to biodiversity.In addition,by molecular clock analysis,we revealed that the evolutionary divergence of extant nereidid species occurred mainly in the Cretaceous and Jurassic,suggesting that paleogeographical and environmental events,such as oceanic anoxic events,might have played a pivotal role in shaping the evolutionary trajectory and ecological adaptations of marine annelids.These findings highlight the importance of considering both current biodiversity patterns and historical contexts in conservation planning,and provided insights into the potential factors on the biogeographic distribution and evolutionary processes of Nereididae.展开更多
The aim of this study was to explore the spatial distribution and submerged scope for storm surge in the Pearl River Delta(PRD) region.Based on the data of storm surges in the PRD region in the past 30 years,the retur...The aim of this study was to explore the spatial distribution and submerged scope for storm surge in the Pearl River Delta(PRD) region.Based on the data of storm surges in the PRD region in the past 30 years,the return periods of 12 tide-gauge stations for storm surges were calculated separately with the methods of Gumbel and Pearson-III.The data of another six tide-gauge stations in Guangdong Coast was quoted to depict the overall features of storm surges in Guangdong.Using least-square method,the spatial distribution models of storm surges in different return periods were established to reveal the distribution rule of the set-up values of storm surges.The spatial distribution curves of storm surges in different return periods in the PRD Region were drawn up based on the models and the terrain of Guangdong Coast.According to the curves,the extreme set-up values of storm surges in 1 000,100,10 a return periods were determined on each spot of Guangdong Coast.Applying the spatial analysis technology of ArcGIS,with the topography data of the PRD Region,the submerged scopes of flood caused by storm surge in 1 000,100,10 a return periods were drawn up.The loss caused by storm surges was estimated.Results showed that the storm surges and the topography of PRD region jointly led to the serious flood in the PRD region.This assessment would be useful for the planning and design department to make decision and provide government scientific basis for storm surge prediction,coastal engineering designing and the prevention of storm surge disaster.展开更多
Brazil is one of the countries with the greatest biodiversity, being covered by diverse ecosystems. Native trees commercially planted generate numerous benefits for communities, providing cultural, recreational, touri...Brazil is one of the countries with the greatest biodiversity, being covered by diverse ecosystems. Native trees commercially planted generate numerous benefits for communities, providing cultural, recreational, tourism riches, as well as ecological benefits, such as nutrient regulation and carbon sequestration. Thus, this work aimed to generate potential distribution modeling for the Brazilian forest species, to provide information that will serve as a strategy for conservation, restoration and commercial plantation of them, that is, encouraging the use of legal native species in the forest sector. Eleven tree species and 19 bioclimatic variables were selected. The software Maxent 3.3.3 was applied in the generation of the distribution models and the area under the curve of receiver operating characteristic （AUC） was used to analyze the model. The Jackknife test contributed to identify which bioclimatic variables are most important or influential in the model. The models showed AUC values ranged from 0.857 to 0.983. The species with higher AUC values were Araucaria angustifolia, Mimosa scabrella and Euterpe edulis, respectively. The maximum temperature of warmest month showed the highest influence for the most species, followed by the mean diurnal range and annual precipitation. It was observed that for some species, there were restricted areas of environmental suitability, such as Araucaria angustifolia, Ilex paraguariensis and Mimosa scabrella. The models used could trace the potential distribution areas using the environmental variables, and these models contribute significantly to sustainable forest management.展开更多
Objectives This study aimed to explore the lagged and cumulative effects of risk factors on disability in older adults using distributed lag non-linear models(DLNMs).Methods We utilized data from the China Health and ...Objectives This study aimed to explore the lagged and cumulative effects of risk factors on disability in older adults using distributed lag non-linear models(DLNMs).Methods We utilized data from the China Health and Retirement Longitudinal Study(CHARLS).After feature selection via Elastic Net Regularization,we applied DLNMs to evaluate the lagged effects of risk factors.Disability was defined as the presence of any difficulties in basic activities of daily living(BADL).The cumulative relative risk(CRR)was calculated by summing the lag-specific risk estimates,representing the cumulative disability risk over the specified lag period.Effect modifications and sensitivity analyses were also performed.Results This study included a total of 2,318 participants.Early-phase lag factors,such as the difficulty in stooping(CRR=3.58;95%CI:2.31-5.55;P<0.001)and walking(CRR=2.77;95%CI:1.39-5.55;P<0.001),exerted the strongest effects immediately upon occurrence.Mid-phase lag factors,such as arthritis(CRR=1.51;95%CI:1.10-2.06;P=0.001),showed a resurgence in disability risk within 2-3 years.Late-phase lag factors,including depressive symptoms(CRR=2.38;95%CI:1.30-4.35;P<0.001)and elevated systolic blood pressure(CRR=1.64;95%CI:1.06-2.79;P=0.02),exhibited significant long-term cumulative risks.Conversely,grip strength(CRR=0.80;95%CI:0.54-0.95;P=0.02)and social participation(CRR=0.89;95%CI:0.73-0.99;P=0.04)were significant protective factors.Conclusions The findings underscore the importance of tailored interventions that account for various lag characteristics of different factors to effectively mitigate disability risk.Future studies should explore the underlying biological and sociological mechanisms of these lagged effects,identify intervention strategies that target risk factors with different lagged patterns,and evaluate their effectiveness.展开更多
Due to the fact that the emergency medicine distribution is vital to the quick response to urgent demand when an epidemic occurs, the optimal vaccine distribution approach is explored according to the epidemic diffusi...Due to the fact that the emergency medicine distribution is vital to the quick response to urgent demand when an epidemic occurs, the optimal vaccine distribution approach is explored according to the epidemic diffusion rule and different urgency degrees of affected areas with the background of the epidemic outbreak in a given region. First, the SIQR （susceptible, infected, quarantined,recovered） epidemic model with pulse vaccination is introduced to describe the epidemic diffusion rule and obtain the demanded vaccine in each pulse. Based on the SIQR model, the affected areas are clustered by using the self-organizing map （SOM） neutral network to qualify the results. Then, a dynamic vaccine distribution model is formulated, incorporating the results of clustering the affected areas with the goals of both reducing the transportation cost and decreasing the unsatisfied demand for the emergency logistics network. Numerical study with twenty affected areas and four distribution centers is carried out. The corresponding numerical results indicate that the proposed approach can make an outstanding contribution to controlling the affected areas with a relatively high degree of urgency, and the comparison results prove that the performance of the clustering method is superior to that of the non-clustering method on controlling epidemic diffusion.展开更多
The classical source-to-trap petroleum system concept only considers the migration and accumulation of conventional oil and gas in traps driven dominantly by buoyance in a basin,although revised and improved,even some...The classical source-to-trap petroleum system concept only considers the migration and accumulation of conventional oil and gas in traps driven dominantly by buoyance in a basin,although revised and improved,even some new concepts as composite petroleum system,total petroleum system,total composite petroleum system,were proposed,but they do not account for the vast unconventional oil and gas reservoirs within the system,which is not formed and distributed in traps dominantly by buoyancedriven.Therefore,the petroleum system concept is no longer adequate in dealing with all the oil and gas accumulations in a basin where significant amount of the unconventional oil and gas resources are present in addition to the conventional oil and gas accumulations.This paper looked into and analyzed the distribution characteristics of conventional and unconventional oil/gas reservoirs and their differences and correlations in petroliferous basins in China and North America,and then proposed whole petroleum system(WPS)concept,the WPS is defined as a natural system that encompasses all the conventional and unconventional oil and gas,reservoirs and resources originated from organic matter in source rocks,the geological elements and processes involving the formation,evolution,and distribution of these oil and gas,reservoirs and resources.It is found in the WPS that there are three kinds of hydrocarbons dynamic fields,three kinds of original hydrocarbons,three kinds of reservoir rocks,and the coupling of these three essential elements lead to the basic ordered distribution model of shale oil/gas reservoirs contacting or interbeded with tight oil/gas reservoirs and separated conventional oil/gas reservoirs from source rocks upward,which is expressed as“S\T-C”.Abnormal conditions lead to other three special ordered distribution models:The first is that with shale oil/gas reservoirs separated from tight oil/gas reservoirs.The second is that with two direction ordered distributions from source upward and downward.The third is with lateral distribution from source outside.展开更多
基金the State Assignment,project 075-00347-19-00(Patterns of the spatiotemporal dynamics of meadow and forest ecosystems in mountainous areas(Russian Western and Central Caucasus)WWF's‘Save the Forest-Home of Raptors’project(2020-2022).
文摘Abiotic factors play an important role in species localisation,but biotic and anthropogenic predictors must also be considered in distribution modelling for models to be biologically meaningful.In this study,we formalised the biotic predictors of nesting sites for four threatened Caucasian vultures by including species distribution models(wild ungulates,nesting tree species)as biotic layers in the vulture Maxent models.Maxent was applied in the R dismo package and the best set of the model parameters were defined in the R ENMeval package.Performance metrics were continuous Boyce index,Akaike's information criterion,the area under receiver operating curve and true skill statistics.We also calculated and evaluated the null models.Kernel density estimation method was applied to assess the overlap of vulture ecological niches in the environmental space.The accessibility of anthropogenic food resources was estimated using the Path Distance measure that considers elevation gradient.The availability of pine forests(Scots Pine)and wild ungulates(Alpine Chamois and Caucasian Goat)contributed the most(29.6%and 34.3%)to Cinereous Vulture(Aegypius monachus)nesting site model.Wild ungulate distribution also contributed significantly(about 46%)to the Bearded Vulture(Gypaetus barbatus)model.This scavenger nests in the highlands of the Caucasus at a minimum distance of 5–10 km from anthropogenic facilities.In contrast,livestock as a food source was most important in colony distribution of Griffon Vulture(Gyps fulvus).The contribution of distances to settlements and agricultural facilities to the model was 45%.The optimal distance from Egyptian Vulture(Neophron percnopterus)nesting sites to settlements was only 3–10 km,to livestock facilities no more than 15 km with the factor contribution of about 57%.Excluding the wild ungulate availability,the ecological niches of studied vultures overlapped significantly.Despite similar foraging and nesting requirements,Caucasian vultures are not pronounced nesting and trophic competitors due to the abundance of nesting sites,anthropogenic food sources and successful niche sharing.
基金Supported by Natural Science Foundation of Hunan Province (2021JJ30375)Natural Science Foundation of Hunan Provincial Department of Education (20A275)Science and Technology Innovation Team Project of Hunan Province (201937924).
文摘Species distribution models have been widely used to explore suitable habitats of species,the impact of climate change on the distribution of suitable habitats of species,and the construction of ecological reserves.This paper introduced species distribution models commonly used in biodiversity analysis,as well as model performance evaluation indexes,challenges in the application of species distribution models,and finally prospected the development trend of research on species distribution models.
基金The Research Project of China Yangtze River Three Gorges Group Limited under contract No.201903173the Zhejiang Mariculture Research Institute of China under contract No.325000。
文摘As our understanding of ecology deepens and modeling techniques advance,species distribution models have grown increasingly sophisticated,enhancing both their fitting and predictive capabilities.However,the dependability of predictive accuracy remains a critical issue,as the precision of these predictions largely hinges on the quality of the base data.We developed models using both field survey and remote sensing data from 2016 to 2020 to evaluate the impact of different data sources on the accuracy of predictions for Scomber japonicus distributions.Our research findings indicate that the variability of water temperature and salinity data from field suvery is significantly greater than that from remote sensing data.Within the same season,we found that the relationship between the abundance of S.japonicus and environmental factors varied significantly depending on the data source.Models using field survey data were able to more accurately reflect the complex relationships between resource distribution and environmental factors.Additionally,in terms of model predictive performance,models based on field survey data demonstrated greater accuracy in predicting the abundance of S.japonicus compared to those based on remote sensing data,allowing for more accurate mastery of their spatial distribution characteristics.This study highlights the significant impact of data sources on the accuracy of species distribution models and offers valuable insights for fisheries resources management.
基金funded by National Key R&D Program of China(2024YFF1307500)the National Natural Science Foundation of China(№32030013 and 32300420)OO was supported by the ANSO Scholarship for Young Talents(No.2022ANP10120).
文摘Biological invasions represent one of the main anthropogenic drivers of global change with a substantial impact on biodi-versity.Traditional studies predict invasion risk based on the correlation between species’distribution and environmental factors,with little attention to the potential contribution of physiological factors.In this study,we incorporated temperature-dependent sex determination(TSD)and sex-ratio data into species distribution models(SDMs)to assess the current and future suitable habitats for the world’s worst invasive reptile species,the pond slider turtle(Trachemys scripta).First,occur-rence records of T.scripta from online databases and published scientific literature were identified.Then,climatic variables representing current(1976-2013)and future(2060-2080)climate scenarios were extracted and combined with sex-ratio records to create hybrid-SDMs with which to assess the current and future suitable habitats for T.scripta.It was found that T.scripta has potential suitable habitat in 136 countries at present.Under the four climate change scenarios(ssp126,ssp245,ssp370 and ssp585)that were modeled,the distribution of T.scripta is predicted to decrease in 78-93 countries but increase in the northern hemisphere.This confirms that there is a greater likelihood that this species will increase in more developed countries.Incorporating the thermal dependence of sex ratio into hybrid-SDMs can be an important addition to detect the invasion risk of TSD species and to develop region-specific invasion management strategies to prevent and/or control invasive species such as T.scripta.
基金Supported by the National Key Research and Development Program of China(No.2023YFD2400800)the Laoshan Laboratory(Nos.LSKJ202203801,LSKJ202203204)+4 种基金the Natural Science Foundation of Shandong Province(Nos.ZR2023MD127,ZR2021MD075)the Central Public-interest Scientific Institution Basal Research Fund CAFS(Nos.2023TD28,20603022023012)the National Natural Science Foundation of China(No.32373107)the China Agriculture Research System(No.CARS-50)the Taishan Scholars Program。
文摘Giant kelp Macrocystis pyrifera,an important foundation species with great ecological and economic value,is threatened by climate change.To better understand the impact of climate warming on M.pyrifera,we investigated its global distribution dynamics by an optimized species distribution model(SDM).Results showed that wave height,sea surface temperature,benthic temperature,and benthic phosphate concentration were key factors shaping the distribution of M.pyrifera.In addition to currently known distribution regions,the model revealed potential suitable habitats globally.Under future climate scenarios,the habitat suitability of M.pyrifera would decrease at low latitudes and increase at high latitudes,resulting in a poleward shift of suitable habitats.In the regions currently occupied by M.pyrifera,the high suitable habitats were predicted to shrink,which implies that the existing M.pyrifera would be adversely impacted.These results serve as references for the conservation and utilization of M.pyrifera resource.
基金This research was supported by NSF grants DBI-1458640 and DBI-1547229.
文摘Predictive studies play a crucial role in the study of biological invasions of terrestrial plants under possible climate change scenarios.Invasive species are recognized for their ability to modify soil microbial communities and influence ecosystem dynamics.Here,we focused on six species of allelopathic flowering plants-Ailanthus altissima,Casuarina equisetifolia,Centaurea stoebe ssp.micranthos,Dioscorea bulbifera,Lantana camara,and Schinus terebinthifolia-Xhat are invasive in North America and examined their potential to spread further during projected climate change.We used Species Distribution Models(SDMs)to predict future suitable areas for these species in North America under several proposed future climate models.ENMEval and Maxent were used to develop SDMs,estimate current distributions,and predict future areas of suitable climate for each species.Areas with the greatest predicted suitable climate in the future include the northeastern and the coastal northwestern regions of North America.Range size estimations demonstrate the possibility of extreme range loss for these invasives in the southeastern United States,while new areas may become suitable in the northeastern United States and southeastern Canada.These findings show an overall northward shift of suitable climate during the next few decades,given projected changes in temperature and precipitation.Our results can be utilized to analyze potential shifts in the distribution of these invasive species and may aid in the development of conservation and management plans to target and control dissemination in areas at higher risk for potential future invasion by these allelopathic species.
基金support from the National Key R&D Program of China(2022YFC3102403)the Stra-tegic Priority Research Program of the Chinese Academy of Sciences(XDB42030204)+5 种基金Science and Technology Planning Project of Guang-dong Province,China(2023B1212060047)development fund of South China Sea Institute of Oceanology of the Chinese Academy of Sciences(SCSIO202208)supported by JST SICORP Grant Number JPMJSC20E5,Japanthe Portuguese National Funds from FCT-Foundation for Science and Technology through projects UIDB/04326/2020,UIDP/04326/2020,LA/P/0101/2020,PTDC/BIA-CBI/6515/2020(https://doi.org/10.54499/PTDC/BIA-CBI/6515/2020)the Individual Call to Scientific Employment Stimulus 2022.00861.CEECINDsupported by the National Multidisciplinary Laboratory for Climate Change(NKFIH-471-3/2021,RRF-2.3.1-21-2022-00014).
文摘Correlative species distribution models(SDMs)are important tools to estimate species’geographic distribution across space and time,but their reliability heavily relies on the availability and quality of occurrence data.Estimations can be biased when occurrences do not fully represent the environmental requirement of a species.We tested to what extent species’physiological knowledge might influence SDM estimations.Focusing on the Japanese sea cucumber Apostichopus japonicus within the coastal ocean of East Asia,we compiled a comprehensive dataset of occurrence records.We then explored the importance of incorporating physiological knowledge into SDMs by calibrating two types of correlative SDMs:a naïve model that solely depends on environmental correlates,and a physiologically informed model that further incorporates physiological information as priors.We further tested the models’sensitivity to calibration area choices by fitting them with different buffered areas around known presences.Compared with naïve models,the physiologically informed models successfully captured the negative influence of high temperature on A.japonicus and were less sensitive to the choice of calibration area.The naïve models resulted in more optimistic prediction of the changes of potential distributions under climate change(i.e.,larger range expansion and less contraction)than the physiologically informed models.Our findings highlight benefits from incorporating physiological information into correlative SDMs,namely mitigating the uncertainties associated with the choice of calibration area.Given these promising features,we encourage future SDM studies to consider species physi-ological information where available.
基金the National Natural Sciences Foundation of China(32192421)the Special Grant Foundations for National Science and &Technology Basic Research Program of China(2021FY100303)the DFGP Project of Fauna of Guangdong Province(202115)。
文摘Three common species of Miniopterus fuliginosus,M.magnater and M.pusillus are known to inhabit China.However,M.fuliginosus and M.magnater are so similar in external morphology as to pose great challenges for accurate classification.Furthermore,taxonomic statuses,distribution ranges and taxonomic keys of these three species have remained controversial.For addressing these outstanding issues,the authors integrated molecular phylogenetic analyses,ensemble species distribution models(ESDMs),multiple morphological comparisons and decision tree algorithms for reassessing their taxonomy and distribution in China.Mitochondrial cytochrome c oxidase subunit I(COI)gene phylogeny revealed three distinct monophyletic groups corresponding to M.fuliginosus,M.magnater and M.pusillus.And the observed distribution patterns indicated M.fuliginosus had a broad distribution across China while M.magnater and M.pusillus exhibited a more restricted distribution,overlapping with M.fuliginosus in South China.And cranial morphometry indicated M.magnater was slightly larger than M.fuliginosus and significantly larger than M.pusillus.Also three-dimensional(3D)skull geomorphometry uncovered distinct features for each species in rostrum,braincase,tympanic bullae and mandibular shape.Decision tree algorithms helped to identify forearm length,braincase breadth and width across the third upper molars as three major taxonomic keys for assisting species identification.This study corroborated the importance of integrative approaches for identifying Miniopterus species and validated a methodological approach applicable to other cryptic species complexes.
基金The National Key Research and Development Program of China,No.2021YFE0190100Inner Mongolia Autonomous Region Mongolian Medicine Standardization Project,No.2023-[MB023]The Earmarked Fund for CARS,No.CARS-21。
文摘Medicinal plant diversity(MPD)is an indispensable part of global plant diversity,serving as the foundation for human survival by offering remedies and preventive measures against diseases.However,factors such as overexploitation,competition from invasive alien species,and climate change,threaten the habitats of medicinal plants,necessitating a comprehensive understanding of their spatial distribution and suitable habitats.We leveraged a decade of field survey data on medicinal plant distribution in the Yinshan Mountains,combined with spatial analysis,species distribution modeling,and the Carnegie Ames Stanford Approach(CASA)to explore the MPD spatial distribution and suitable habitats.Spatial analysis revealed that the central and eastern parts of Yinshan Mountains were the primary MPD hotspots,with no cold spots evident at various spatial scales.As the spatial scale decreased,previous non-significant regions transformed into hotspots,with instances where large-scale hotspots became insignificant.These findings offer valuable guidance for safeguarding and nurturing MPD across diverse spatial scales.In future climate change scenarios within the shared socioeconomic pathways(SSP),the habitat suitability for MPD in the Yinshan Mountains predominantly remains concentrated in the central and eastern regions.Notably,areas with high net primary productivity(NPP)values and abundant vegetation coverage align closely with MPD habitat suitability areas,potentially contributing to the region's rich MPD.
基金funded by the National Key R&D Program of China(Grant no.2022YFC2807504)the Marine S&T Fund of Shandong Province for Qingdao Marine Science and Technology Center(Grant no.2022QNLM030002-1)the Central Public-interest Scientific Institution Basal Research(Grant no.2023TD02).
文摘Antarctic krill(Euphausia superba),widely distributes around Antarctica,is a key species supporting the biodiversity of the Southern Ocean ecosystem.The Commission for the Conservation of Antarctic Marine Living Resources(CCAMLR)has thus managed the krill fishery according to a precautionary way.Currently,CCAMLR is making effort to develop a refined krill fishery management approach based on more solid science,which requires accurate predictions of krill distribution.To address this need,this study investigated the effects of algorithm and spatial resolution on the performance of Antarctic krill distribution modelling.We integrated acoustic data from 4 surveys conducted in the waters adjacent to the Antarctic Peninsula with 11 environmental variables characterizing krill prey conditions,water mass properties,and seafloor topography.These data were processed at 4 spatial resolutions(5,10,15,and 20 km)to fit distribution models using 4 algorithms:Random Forests(RF),Generalized Additive Models(GAM),Extreme Gradient Boosting(XGBoost),and Artificial Neural Networks(ANN).Model performance was assessed and compared in terms of goodness-of-fit and predictive accuracy.The results showed that RF achieved the highest predictive performance at most resolutions,whereas GAM performed best at the coarsest resolution(20 km).XGBoost closely following RF in accuracy and demonstrated robustness as evidenced by the highly consistent partial dependence curves across resolutions.In contrast,ANN exhibited limitations with smaller sample sizes,resulting in comparatively poorer predictive performance.The analysis revealed a trade-off whereby reducing spatial resolution improved model fit and mitigated zero-inflation at the expense of fine-scale information and overall predictive accuracy.Ensemble models,integrating RF,GAM,and XGBoost,are proposed as potential balanced solutions to improve predictive stability,offering a more robust scientific basis for the refinement of krill management.
基金Supported by the National Natural Science Foundation of China(No.U24B20156)the National Defense Basic Scientific Research Program of China(No.JCKY2021204B051)the National Laboratory of Space Intelligent Control of China(Nos.HTKJ2023KL502005 and HTKJ2024KL502007)。
文摘A chance-constrained energy dispatch model based on the distributed stochastic model predictive control(DSMPC)approach for an islanded multi-microgrid system is proposed.An ambiguity set considering the inherent uncertainties of renewable energy sources(RESs)is constructed without requiring the full distribution knowledge of the uncertainties.The power balance chance constraint is reformulated within the framework of the distributionally robust optimization(DRO)approach.With the exchange of information and energy flow,each microgrid can achieve its local supply-demand balance.Furthermore,the closed-loop stability and recursive feasibility of the proposed algorithm are proved.The comparative results with other DSMPC methods show that a trade-off between robustness and economy can be achieved.
文摘Accurate modeling and parameter estimation of sea clutter are fundamental for effective sea surface target detection.With the improvement of radar resolution,sea clutter exhibits a pronounced heavy-tailed characteristic,rendering traditional distribution models and parameter estimation methods less effective.To address this,this paper proposes a dual compound-Gaussian model with inverse Gaussian texture(CG-IG)distribution model and combines it with an improved Adam algorithm to introduce a method for parameter correction.This method effectively fits sea clutter with heavy-tailed characteristics.Experiments with real measured sea clutter data show that the dual CGIG distribution model,after parameter correction,accurately describes the heavy-tailed phenomenon in sea clutter amplitude distribution,and the overall mean square error of the distribution is reduced.
基金supported by the United States Geological Survey(Ecosystems Mission Area)the National Science Foundation Small Grants for Exploratory Research(No.0713027)Wetlands International
文摘Background: A number of conservation and societal issues require understanding how species are distributed on the landscape, yet ecologists are often faced with a lack of data to develop models at the resolution and extent desired, resulting in inefficient use of conservation resources.Such a situation presented itself in our attempt to develop waterfowl distribution models as part of a multi-disciplinary team targeting the control of the highly pathogenic H5N1 avian influenza virus in China.Methods: Faced with limited data, we built species distribution models using a habitat suitability approach for China's breeding and non-breeding(hereafter, wintering) waterfowl.An extensive review of the literature was used to determine model parameters for habitat modeling.Habitat relationships were implemented in GIS using land cover covariates.Wintering models were validated using waterfowl census data, while breeding models, though developed for many species, were only validated for the one species with sufficient telemetry data available.Results: We developed suitability models for 42 waterfowl species(30 breeding and 39 wintering) at 1 km resolution for the extent of China, along with cumulative and genus level species richness maps.Breeding season models showed highest waterfowl suitability in wetlands of the high-elevation west-central plateau and northeastern China.Wintering waterfowl suitability was highest in the lowland regions of southeastern China.Validation measures indicated strong performance in predicting species presence.Comparing our model outputs to China's protected areas indicated that breeding habitat was generally better covered than wintering habitat, and identified locations for which additional research and protection should be prioritized.Conclusions: These suitability models are the first available for many of China's waterfowl species, and have direct utility to conservation and habitat planning and prioritizing management of critically important areas, providing an example of how this approach may aid others faced with the challenge of addressing conservation issues with little data to inform decision making.
基金supported by the Major Special Projects for Green Pest Control,China(110202401016(LS-06))the National Key Research and Development Project of China(2021YFD1400200).
文摘Selecting effective biological control agents(BCAs)is critical for managing invasive pests such as the tomato leafminer,Tuta absoluta,a species that has posed a significant agricultural threat in China since its recent invasion.Traditional selection methods prioritize climate matching but often overlook intrinsic biocontrol efficacy.This study proposes a novel spatially explicit framework that integrates climatic suitability and performance to determine effective BCAs.Using the CLIMEX model,we projected the climatic suitability of T.absoluta and four Trichogramma parasitoids(T.chilonis,T.dendrolimi,T.ostriniae,and T.pretiosum)across China.Crucially,we incorporated the pest kill rate(k_(m))to construct a Comprehensive Index(CI).Spatial projections derived from this parameter revealed a pronounced redistribution of dominant parasitoid species relative to climate-only predictions.T.ostriniae has emerged as the primary dominant agent across China's agricultural zones,including the North China Plain,Yangtze River Basin,Sichuan Basin,and Xinjiang's risk regions,replacing vast areas previously assigned to other parasitoid species under climate-matching models.Moreover,T.pretiosum remained dominant in subtropical southern China.This study demonstrated that integrating intrinsic biocontrol efficacy with climatic suitability significantly enhances the robustness of BCA selection,addressing critical limitations of climate-exclusive approaches.Our CI framework provides an evidence-based,spatially optimized strategy for the sustainable management of T.absoluta,prioritizing the targeted deployment of Trichogramma species in key agroecological zones.This methodology can be readily adapted to optimize biocontrol programs against globally invasive pests.
基金Supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDB42000000)the National Natural Science Foundation of China(No.42376092)the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(No.2022QNLM030004)。
文摘Nereididae is a prolific annelid family widely distributed in the world oceans,especially in the Indo-Pacific Convergence Zone(IPCZ).However,its biogeographic pattern remains unexplored in IPCZ.To contribute to the understanding of biodiversity and biogeography of Nereididae in the IPCZ,we integrated historical data of species distributions with those of model-predicted ones to determine the biogeographic patterns of nereid species,from which we projected to its future distribution patterns for 2090-2100 under different climate scenarios(SSP1-1.9 and SSP5-8.5).Functional diversity within IPCZ was assessed using functional richness,functional evenness,and functional disparity.Divergence times within Nereididae were estimated using three DNA marker genes(COI,16S,and 18S rRNA),and a time tree was constructed based on a strict molecular clock model.The IPCZ was established as a key Nereididae biodiversity hotspot through distribution modelling of 256 species(44 genera),and temperature emerging as the predominant climatic driver of species distribution patterns.The distribution of species and functional diversity is notable for its non-centralized pattern.We projected that by the end of the century,areas of medium-to-high species richness will expand significantly under the low-emission SSP1-1.9 climate scenario.However,under the high-emission SSP5-8.5 scenario,the suitability of these regions significantly declines,posing an increasingly severe threat to biodiversity.In addition,by molecular clock analysis,we revealed that the evolutionary divergence of extant nereidid species occurred mainly in the Cretaceous and Jurassic,suggesting that paleogeographical and environmental events,such as oceanic anoxic events,might have played a pivotal role in shaping the evolutionary trajectory and ecological adaptations of marine annelids.These findings highlight the importance of considering both current biodiversity patterns and historical contexts in conservation planning,and provided insights into the potential factors on the biogeographic distribution and evolutionary processes of Nereididae.
基金Supported by National Key Technology R&D Program of China(2006BAD20B05)
文摘The aim of this study was to explore the spatial distribution and submerged scope for storm surge in the Pearl River Delta(PRD) region.Based on the data of storm surges in the PRD region in the past 30 years,the return periods of 12 tide-gauge stations for storm surges were calculated separately with the methods of Gumbel and Pearson-III.The data of another six tide-gauge stations in Guangdong Coast was quoted to depict the overall features of storm surges in Guangdong.Using least-square method,the spatial distribution models of storm surges in different return periods were established to reveal the distribution rule of the set-up values of storm surges.The spatial distribution curves of storm surges in different return periods in the PRD Region were drawn up based on the models and the terrain of Guangdong Coast.According to the curves,the extreme set-up values of storm surges in 1 000,100,10 a return periods were determined on each spot of Guangdong Coast.Applying the spatial analysis technology of ArcGIS,with the topography data of the PRD Region,the submerged scopes of flood caused by storm surge in 1 000,100,10 a return periods were drawn up.The loss caused by storm surges was estimated.Results showed that the storm surges and the topography of PRD region jointly led to the serious flood in the PRD region.This assessment would be useful for the planning and design department to make decision and provide government scientific basis for storm surge prediction,coastal engineering designing and the prevention of storm surge disaster.
文摘Brazil is one of the countries with the greatest biodiversity, being covered by diverse ecosystems. Native trees commercially planted generate numerous benefits for communities, providing cultural, recreational, tourism riches, as well as ecological benefits, such as nutrient regulation and carbon sequestration. Thus, this work aimed to generate potential distribution modeling for the Brazilian forest species, to provide information that will serve as a strategy for conservation, restoration and commercial plantation of them, that is, encouraging the use of legal native species in the forest sector. Eleven tree species and 19 bioclimatic variables were selected. The software Maxent 3.3.3 was applied in the generation of the distribution models and the area under the curve of receiver operating characteristic （AUC） was used to analyze the model. The Jackknife test contributed to identify which bioclimatic variables are most important or influential in the model. The models showed AUC values ranged from 0.857 to 0.983. The species with higher AUC values were Araucaria angustifolia, Mimosa scabrella and Euterpe edulis, respectively. The maximum temperature of warmest month showed the highest influence for the most species, followed by the mean diurnal range and annual precipitation. It was observed that for some species, there were restricted areas of environmental suitability, such as Araucaria angustifolia, Ilex paraguariensis and Mimosa scabrella. The models used could trace the potential distribution areas using the environmental variables, and these models contribute significantly to sustainable forest management.
基金supported by ScientificResearch Fund of National Health Commission of the People’s Republic of China-Major Science and Technology Program for Medicine and Health in Zhejiang Province(WKJ-ZJ-2406).
文摘Objectives This study aimed to explore the lagged and cumulative effects of risk factors on disability in older adults using distributed lag non-linear models(DLNMs).Methods We utilized data from the China Health and Retirement Longitudinal Study(CHARLS).After feature selection via Elastic Net Regularization,we applied DLNMs to evaluate the lagged effects of risk factors.Disability was defined as the presence of any difficulties in basic activities of daily living(BADL).The cumulative relative risk(CRR)was calculated by summing the lag-specific risk estimates,representing the cumulative disability risk over the specified lag period.Effect modifications and sensitivity analyses were also performed.Results This study included a total of 2,318 participants.Early-phase lag factors,such as the difficulty in stooping(CRR=3.58;95%CI:2.31-5.55;P<0.001)and walking(CRR=2.77;95%CI:1.39-5.55;P<0.001),exerted the strongest effects immediately upon occurrence.Mid-phase lag factors,such as arthritis(CRR=1.51;95%CI:1.10-2.06;P=0.001),showed a resurgence in disability risk within 2-3 years.Late-phase lag factors,including depressive symptoms(CRR=2.38;95%CI:1.30-4.35;P<0.001)and elevated systolic blood pressure(CRR=1.64;95%CI:1.06-2.79;P=0.02),exhibited significant long-term cumulative risks.Conversely,grip strength(CRR=0.80;95%CI:0.54-0.95;P=0.02)and social participation(CRR=0.89;95%CI:0.73-0.99;P=0.04)were significant protective factors.Conclusions The findings underscore the importance of tailored interventions that account for various lag characteristics of different factors to effectively mitigate disability risk.Future studies should explore the underlying biological and sociological mechanisms of these lagged effects,identify intervention strategies that target risk factors with different lagged patterns,and evaluate their effectiveness.
基金The National Natural Science Foundation of China (No.70671021)
文摘Due to the fact that the emergency medicine distribution is vital to the quick response to urgent demand when an epidemic occurs, the optimal vaccine distribution approach is explored according to the epidemic diffusion rule and different urgency degrees of affected areas with the background of the epidemic outbreak in a given region. First, the SIQR （susceptible, infected, quarantined,recovered） epidemic model with pulse vaccination is introduced to describe the epidemic diffusion rule and obtain the demanded vaccine in each pulse. Based on the SIQR model, the affected areas are clustered by using the self-organizing map （SOM） neutral network to qualify the results. Then, a dynamic vaccine distribution model is formulated, incorporating the results of clustering the affected areas with the goals of both reducing the transportation cost and decreasing the unsatisfied demand for the emergency logistics network. Numerical study with twenty affected areas and four distribution centers is carried out. The corresponding numerical results indicate that the proposed approach can make an outstanding contribution to controlling the affected areas with a relatively high degree of urgency, and the comparison results prove that the performance of the clustering method is superior to that of the non-clustering method on controlling epidemic diffusion.
基金This work was supported by the major science and technology projects of CNPC during the“14th five-year plan”(Grant number 2021DJ0101)。
文摘The classical source-to-trap petroleum system concept only considers the migration and accumulation of conventional oil and gas in traps driven dominantly by buoyance in a basin,although revised and improved,even some new concepts as composite petroleum system,total petroleum system,total composite petroleum system,were proposed,but they do not account for the vast unconventional oil and gas reservoirs within the system,which is not formed and distributed in traps dominantly by buoyancedriven.Therefore,the petroleum system concept is no longer adequate in dealing with all the oil and gas accumulations in a basin where significant amount of the unconventional oil and gas resources are present in addition to the conventional oil and gas accumulations.This paper looked into and analyzed the distribution characteristics of conventional and unconventional oil/gas reservoirs and their differences and correlations in petroliferous basins in China and North America,and then proposed whole petroleum system(WPS)concept,the WPS is defined as a natural system that encompasses all the conventional and unconventional oil and gas,reservoirs and resources originated from organic matter in source rocks,the geological elements and processes involving the formation,evolution,and distribution of these oil and gas,reservoirs and resources.It is found in the WPS that there are three kinds of hydrocarbons dynamic fields,three kinds of original hydrocarbons,three kinds of reservoir rocks,and the coupling of these three essential elements lead to the basic ordered distribution model of shale oil/gas reservoirs contacting or interbeded with tight oil/gas reservoirs and separated conventional oil/gas reservoirs from source rocks upward,which is expressed as“S\T-C”.Abnormal conditions lead to other three special ordered distribution models:The first is that with shale oil/gas reservoirs separated from tight oil/gas reservoirs.The second is that with two direction ordered distributions from source upward and downward.The third is with lateral distribution from source outside.
