Ecological Modelling最新文献

{"title":"A comparative analysis of univariate and multivariate spatial requirements modeling for habitat selection in freshwater fish: A case study of Oxynoemacheilus bergianus in the Jajroud River, Iran and implications for conservation and management","authors":"Saleh Mahmoudi,&nbsp;Asghar Abdoli","doi":"10.1016/j.ecolmodel.2025.111076","DOIUrl":"10.1016/j.ecolmodel.2025.111076","url":null,"abstract":"<div><div>Understanding the habitat requirements for fish in fluvial ecosystems is a key factor in conservation and making decisions for management. One of the main questions is what are the optimal ranges for each variable-velocity, depth, and substrate structure-that the species requires, and how do these ranges influence its development and survival? Given the scarcity of biological and ecological information on <em>Oxynoemacheilus bergianus</em> habitat selection at the mesoscale, this survey was designed to provide an answer to the aforementioned question. For this purpose, the effects of three main variables, including flow velocity, water depth, and substrate composition on the habitat selection of the species in a lotic ecosystem in northern Iran were evaluated. The results indicate that for the juvenile group, depths up to 20 cm, velocities of 15–20 cm.s-1, and a dominant substrate of fine and medium gravel are the most suitable ranges. For the adult group, depths of 20–30 cm, velocities of 15–30 cm.s-1, and small cobbles are preferred We addressed these questions using both univariate and multivariate approaches, which resulted in different variable importance, model accuracy, and uncertainty across methods. Specifically, flow velocity was identified as the most significant variable in the univariate analysis. The depth variable was more important in the multivariate approach. The minimum method (MI) and the arithmetic mean (AM) method had the lowest and highest error and uncertainty among the combined methods, respectively. The Generalized Linear Models (GLM) and Random Forest Models (RF) approaches showed the most accurate models in the Species Distribution Models (SDMs) for juvenile and adult groups, respectively. Utilizing these vital results will empower managers to make informed decisions aimed at conserving O. bergianus, ultimately leading to effective strategies that protect its habitat and ensure the species' long-term survival.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"504 ","pages":"Article 111076"},"PeriodicalIF":2.6,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Altitude differences in relationship between radial growth process and cambial phenology of Qinghai spruce (Picea crassifolia) on the Tibetan Plateau","authors":"Le Zhang ,&nbsp;Liang Jiao ,&nbsp;Ruhong Xue ,&nbsp;Peng Zhang ,&nbsp;Xin Yuan ,&nbsp;Qian Li ,&nbsp;Kuan Zhang","doi":"10.1016/j.ecolmodel.2025.111078","DOIUrl":"10.1016/j.ecolmodel.2025.111078","url":null,"abstract":"<div><div>Climate change profoundly affects tree radial growth dynamics and phenological changes, yet the relationships between radial growth and cambial phenology of dominant tree species at different altitudes on the Tibetan Plateau remain unclear under the background of climate change. In this study, we analyzed the characteristics and relationships between intra-annual growth rates and growth phenology of Qinghai spruce using tree-ring width data from 1973 to 2022 at different altitudes on the Tibetan Plateau based on a growth process model. The results showed that the inter-annual variations of radial growth at high altitude exhibited a gradual increasing trend, with intra-annual growth rates displaying a unimodal pattern. Additionally, there were no significant differences in growth rates dependence on temperature and soil moisture between wide and narrow rings. Inter-annual variations of radial growth at low altitude showed a gradual decreasing trend, with intra-annual growth rates exhibiting a bimodal pattern. Growth rates dependence on temperature did not differ significantly between wide and narrow rings, but the growth rates dependence on soil moisture was significantly different. Phenological characteristics are the key factors to determine inter-annual tree radial growth at high altitude, while both phenological characteristics and soil moisture are the main reasons to determine inter-annual and intra-annual tree radial growth at low altitude. The findings provide a theoretical basis for scientific management of forest ecosystems at different altitudes on the Tibetan Plateau and accurate prediction of forest growth dynamics under future climate change.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"504 ","pages":"Article 111078"},"PeriodicalIF":2.6,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Constructing time-series submerged aquatic vegetation by integrating process-based modeling and satellite images","authors":"Lingyan Qi ,&nbsp;Han Yin ,&nbsp;Zhengxin Wang ,&nbsp;Liuyi Dai ,&nbsp;Liangtao Ye ,&nbsp;Kejia Zhang ,&nbsp;Mingzhu Guo ,&nbsp;Haifeng Qi ,&nbsp;Jiacong Huang","doi":"10.1016/j.ecolmodel.2025.111074","DOIUrl":"10.1016/j.ecolmodel.2025.111074","url":null,"abstract":"<div><div>Submerged aquatic vegetation (SAV) plays a critical role in lake ecosystem health. However, quantifying the spatiotemporal patterns of SAV biomass remains challenging due to limited time-series data. To address this challenge, we integrated a process-based SAV dynamic model with a satellite-based SAV biomass estimation model to construct a time-series SAV dataset for Lake Zhanbei, a sub-lake within China's largest freshwater lake, Lake Poyang. The integrated model effectively captured SAV biomass dynamics, with model performance of <em>R²</em>=0.60 and <em>RMSE</em>=0.24 kg/m² compared to measured data. Results showed that SAV was more abundant near floodplain areas. A significant decline of SAV biomass was observed from 0.76 kg/m² (2021) to 0.19 kg/m² (2022), primarily due to a drop in the annual average water level from 14.1 m (2021) to 13.4 m (2022) caused by extreme drought. Water level was the most sensitive driver of SAV biomass, while temperature also had a notable impact under optimal water levels. Our scenario simulations revealed that global warming could enhance SAV growth, while nutrients had minimal effects. Compared with <em>in-situ</em> measurements from previous publications, the integrated model offers a cost-effective and high-resolution approach to study SAV dynamics, with potential applications in other lakes.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"504 ","pages":"Article 111074"},"PeriodicalIF":2.6,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143549298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward a better understanding of forest spatial patterns:A generalisation of the uniform angle index","authors":"Yuankun Bu ,&nbsp;Weizhong Li ,&nbsp;Klaus von Gadow ,&nbsp;Jiangtao Wei ,&nbsp;Pengxiang Zhao ,&nbsp;Yanzheng Yang ,&nbsp;Chaofan Zhou ,&nbsp;Boheng Wang ,&nbsp;Xuan Zhao","doi":"10.1016/j.ecolmodel.2025.111070","DOIUrl":"10.1016/j.ecolmodel.2025.111070","url":null,"abstract":"<div><div>Spatial structure is important for characterizing a forest ecosystem. Among a myriad of spatial structure indices, the <em>Uniform Angle Index</em> (UAI) is rather special. The UAI quantifies a spatial pattern based on angles between neighbouring trees, thereby offering new insights into close range tree arrangements, competition, and stand dynamics. However, previous theoretical studies of the UAI have primarily relied on simulation stand and hence the uncertainty associated with them since its inception. Therefore, a mathematical derivation is still lacking. In this study, we present a theoretical framework for the UAI with the aim of broadening its applicability in quantifying the intensity of interactions among trees. Our theory is developed at two levels, the individual tree level and the stand level. The objective is to eliminate any simulation-induced uncertainty and bias and to enrich the theoretical foundation and applicability. We present a significant improvement of the UAI for estimating interaction strength among trees by the distance between an ideal and a real stand. This research highlights the opportunities for point pattern research in a new multidisciplinary science of forest ecology by growing knowledge and information along scientifically meaningful lines.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"503 ","pages":"Article 111070"},"PeriodicalIF":2.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143528800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Growing at the edge: Modelling sapling colonization, performance, and effective range of mountain birch (Betula pubescens ssp. tortuosa)","authors":"Anna Mariager Behrend ,&nbsp;Arne Pommerening","doi":"10.1016/j.ecolmodel.2025.111073","DOIUrl":"10.1016/j.ecolmodel.2025.111073","url":null,"abstract":"<div><div>Colonization of trees from existing woodlands into adjacent open lands is a critical process of passive restoration, leading to the formation of secondary woodlands. Important drivers of this process include sheltering from surrounding woodlands, which can affect both the spatial range of colonization and the performance of individual saplings. In this study we analysed the effects of sheltering and canopy height on the patterns of natural colonization and individual sapling performance of mountain birch (<em>Betula pubescens</em> ssp. <em>tortuosa</em>) in different regions of Iceland. We measured sapling densities and individual sapling morphology along transects, and modelled colonization using hyperbolic kernel functions. We subsequently used these colonization kernels to define and calculate the effective spatial range for mountain birch colonization. The results showed a clear effect of regional environments on the performance of mountain birch saplings. The effective spatial range of colonization varied greatly between regions, ranging from 16.6 m in areas with birch of low stature, to 67.4 m in the region with the tallest, straightest stems. We furthermore saw that individual sapling performance was a direct product of sheltering, as one kernel function parameter was significantly correlated with the tree morphology index used in this study. Our results highlighted the importance of sheltering from surrounding woodlands on both colonization patterns and on individual sapling performance, though sheltering effects are generally low in Iceland. This should be considered in research as well as practice by combining natural colonization with efficient localized planting. The effective spatial range can aid in finding an appropriate balance between these two restoration methods.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"503 ","pages":"Article 111073"},"PeriodicalIF":2.6,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143527375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Climate warming will significantly affect future restoration and level of ecosystem services in Lake Erhai","authors":"Bo Qin ,&nbsp;Min Xu ,&nbsp;Kexin Zhu ,&nbsp;Yanjie Zhao ,&nbsp;Enlou Zhang ,&nbsp;Rong Wang","doi":"10.1016/j.ecolmodel.2025.111067","DOIUrl":"10.1016/j.ecolmodel.2025.111067","url":null,"abstract":"<div><div>Freshwater ecosystems have been degraded under the recent impacts of global warming and human activities. Reducing external nutrient loadings is the primary strategy for restoring lake state and ecosystem services, but overlooking the impact of warming may hinder its long-term effectiveness. In order to investigate such an impact, this study simulated potential ecosystem responses between 2020 and 2050 using the PCLake model in a typical lake under restoration (Lake Erhai) in southwestern China. Calibrated based on observations from 1990 to 2020, the model could well simulate the long-term changes in Lake Erhai, including the regime shift around 2002. Under further bivariate scenarios, results of current nutrient input showed that warming above 1.2 °C would cause declines of macrophyte coverage 0–7 years in advance. In 2050, the overall change of ecosystem services would be positive if warming remains below 1.2 °C but negative if warming exceeds 2.2 °C. The above warming levels could be viewed as delineations of the safe and dangerous warming zones for ecosystem status and service in Lake Erhai under current restoration strength. The impact of warming would be more intuitive under the absence of nutrient control, i.e., both slow and fast warming would advance macrophyte decline and decrease overall ecosystem services. This study combined perspectives of regime shift and ecosystem service loss to highlight the need for climate-adaptive management, which may provide a new research paradigm to evaluate warming impacts on lake restorations beyond the study site.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"503 ","pages":"Article 111067"},"PeriodicalIF":2.6,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143519000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Canary palms in rural areas as invasion bridges: Exploring simulated red palm weevil spread across date palm plantations","authors":"Eitan Goldshtein ,&nbsp;Victoria Soroker ,&nbsp;Asaf Sadeh ,&nbsp;Yafit Cohen","doi":"10.1016/j.ecolmodel.2025.111071","DOIUrl":"10.1016/j.ecolmodel.2025.111071","url":null,"abstract":"<div><div>The red palm weevil, <em>Rhynchophorus ferrugineus</em>, (RPW) is an invasive pest that causes significant damage to date palms (<em>Phoenix dactylifera</em> L.) in agricultural plantations and to Canary palms (<em>P. canariensis</em>) in residential areas. Canary palms provide a higher-quality habitat for RPW than date palms. However, little is known about how RPW spreads between these palm species —whether it disperses randomly or host oriented. To explore how variation in Canary palm density affects RPW spread, we developed a coupled map lattice simulation model in artificial landscapes with alternating date palm plantations and villages, represented as patches with varying densities of Canary palms that enhance habitat connectivity between the date plantations. Dispersal between cells occurs based on cell scores that account for host abundance, dispersal behavior, and RPW attraction to palm hosts (oriented dispersal). Our results show that RPW spread rates are influenced by both cell scores and Canary palm densities. In landscapes with low Canary palm density, RPW spreads were limited under random dispersal. However, with a low degree of oriented dispersal, spread rates increase sharply with increasing Canary palm densities, and leveling off at the highest densities, suggesting that RPW uses these palms as stepping-stones to reach distant date plantations. At higher degrees of oriented dispersal, spread rates remain stable at low Canary palm densities, then increase linearly at higher densities. The sensitivity analysis highlighted key knowledge gaps on RPW dispersal, emergence patterns from different palm species, and the relative susceptibility of these species to infestation.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"503 ","pages":"Article 111071"},"PeriodicalIF":2.6,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143527374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bush encroachment with climate change in protected and communal areas: A species distribution modelling approach","authors":"Thabang Maphanga ,&nbsp;Cletah Shoko ,&nbsp;Mbulisi Sibanda ,&nbsp;Blessing Kavhu ,&nbsp;Corli Coetsee ,&nbsp;Timothy Dube","doi":"10.1016/j.ecolmodel.2025.111056","DOIUrl":"10.1016/j.ecolmodel.2025.111056","url":null,"abstract":"<div><div>Savanna rangelands have experienced widespread degradation due to bush encroachment, raising significant concerns among conservationists and rural communities. In the context of climate change, these ecosystem shifts are likely to intensify, especially in South Africa's semi-arid regions. Understanding the impacts of climate variability and change on species distribution within these rangelands is crucial for mitigating further ecosystem disruption. Environmental factors, along with climatic variables, can accelerate the process of bush encroachment, threatening both biodiversity and land use. Early identification of areas vulnerable to invasion is key to developing effective and cost-efficient management strategies. This study aims to model the distribution of invasive species across protected and communal landscapes under long-term climate change projections. A Random Forest (RF) model produced the highest accuracy metrics for Area under the curve (AUC) = 0.99 and True Skill Statistic (TSS)=0.97, while a MaxEnt model recorded the second highest AUC (0.98) and TSS (0.97). The results show a clear difference between the current and future scenarios of the spatial distribution in all the models. Applying a species distribution model (SDM) using both MaxEnt and RF produced a higher degree of prediction accuracy because RF is susceptible to overfitting training data while MaxEnt can produce predictable and complex results. Moreover, the overall predictions using the ensemble model demonstrated an increase in areas suitable for encroachment under RCP 8.5 but a decrease in the bush encroachment rate under RCP 2.6. These findings underscore the critical need for proactive management strategies to mitigate bush encroachment, particularly under high-emission scenarios, ensuring the sustainability of semi-arid savanna rangelands in the face of climate change.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"503 ","pages":"Article 111056"},"PeriodicalIF":2.6,"publicationDate":"2025-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hybrid modeling approaches for accurate greenhouse climate prediction: Combining mechanistic models and LSTM neural networks","authors":"Yuanhong Xiong ,&nbsp;Yuanping Su","doi":"10.1016/j.ecolmodel.2025.111059","DOIUrl":"10.1016/j.ecolmodel.2025.111059","url":null,"abstract":"<div><div>An accurate greenhouse climate model is crucial for controller design, energy consumption, and crop yield prediction. However, for a given greenhouse, considerable cost and time are required to study the thermal and mass transfer processes needed to construct an accurate greenhouse climate mechanistic model. To explore highly efficient modeling methods for greenhouse climate, this study proposes two hybrid modeling methods that combine mechanistic modeling with neural networks. The first method establishes a residual dataset for the greenhouse environment using mechanistic models and trains this residual model with an LSTM neural network. The second method employs LSTM neural networks and mechanistic models to predict greenhouse climate, then weights and combines the predictions from both models to achieve more accurate forecasting of greenhouse climate. In these two hybrid models, the mechanistic models use optimization algorithms for parameter identification and are validated with data from four different periods. A comparison of the results from the mechanistic model and the LSTM greenhouse climate prediction model shows that the neural network residual correction model exhibits better prediction accuracy and generalization capability in handling uncertain climate environment data. In contrast, the weighted fusion model places higher demands on the base models and shows considerable uncertainty in adaptability to different environments. The developed models in this study not only improve the prediction accuracy of greenhouse climate but also enhance the capability to handle complex and changing climatic conditions, thereby providing reliable decision-making support for greenhouse management and agricultural production.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"503 ","pages":"Article 111059"},"PeriodicalIF":2.6,"publicationDate":"2025-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling system dynamics as a socio-ecological perspective to support human-beaver interactions","authors":"Anna Treves ,&nbsp;Giovanni Zenezini ,&nbsp;Elena Comino","doi":"10.1016/j.ecolmodel.2025.111057","DOIUrl":"10.1016/j.ecolmodel.2025.111057","url":null,"abstract":"<div><div>Beavers are semi-aquatic mammals that significantly impact on freshwater ecosystems, creating benefits and challenges, particularly in areas with close human interaction. Managing human-beaver interactions is a multifaceted issue due to the many variables involved, but the complexity of these interactions can be analysed effectively using system dynamics models. These models are used in many contexts, including wildlife management, to simulate a variety of management policies and assess their effects. The present study addressed gaps in the literature by developing a system dynamics model that examined both the benefits and conflicts that arise from human-beaver interactions. The model, implemented using Vensim PLE software, synthesised qualitative and quantitative data to simulate four simulation scenarios: ecological, social, economic, and policy making. The study examined the dynamics of beaver populations, ecosystem service provision, social perceptions, and management strategies in a case study of the Ivrea lakes area in the Piedmont region (Italy). Model predictions highlights that beaver populations stabilized logistically, influencing ecosystem services and residual capital, while social acceptance stongly reduced management costs and social pressure. Optimal budget allocation and combined strategies emerged as key to sustainable management and conflict mitigation. Overall, predictions suggest that an integrated approach that prioritises prevention and actively engages local communities can improve both ecological outcomes and social acceptance of beavers. The model is a useful decision and discussion tool for assessing management strategies and facilitating stakeholder involvement. Future studies should expand on these results by exploring additional beaver-related conflicts and benefits in diverse contexts.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"503 ","pages":"Article 111057"},"PeriodicalIF":2.6,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143463513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}