Ecological Modelling最新文献

Stochastic disturbances and delays drive coexistence and extinction in competing populations

IF 2.6 3区环境科学与生态学 Q2 ECOLOGY

Ecological Modelling

Pub Date : 2025-04-26 DOI: 10.1016/j.ecolmodel.2025.111155

Tianyuan Chen , Huayong Zhang , Yihe Zhang , Zhongyu Wang

The coexistence and extinction of competing populations are influenced not only by primary competing species but also by environmental stochastic disturbances, time delays, and secondary competing species. Based on the Lotka-Volterra model, this study establishes a stochastic population competition model with S-type distributed delays, incorporating the influence factor q of secondary species and the environment. Intrinsic and interspecific disturbances are represented using Ornstein-Uhlenbeck processes and white noise. Theoretical analysis and numerical simulations were conducted as follows: (1) A Lyapunov function was constructed to prove the existence and uniqueness of the global positive solution of the model, and conditions for global asymptotic stability were derived based on Markov semigroup theory. (2) Under low-intensity stochastic disturbances, the population with stronger competitiveness increased in size, while the weaker population tended toward extinction. When there was no difference in competitive strength, both populations could coexist in the long term; Under medium-intensity disturbances, coexistence and extinction exhibited complex patterns; Under high-intensity disturbances, randomness became the dominant factor, leading to rapid population declines, abnormal fluctuations, and eventual extinction. Nevertheless, competitiveness and time delays further complicated population dynamics; Time delays alleviated population fluctuations and promoted system stability under low-intensity disturbances. However, under higher disturbances, they initially amplified fluctuations and introduced periodic dynamics but ultimately helped stabilize the system; The influence factor q moderated population fluctuations and improved the survival conditions of weaker populations under low-intensity disturbances but showed diminished effects under medium- and high-intensity disturbances. This study enhances the understanding of coexistence and extinction mechanisms in competing populations, offering significant insights into ecosystem management and conservation strategies.

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引用次数: 0

Elasmobranch vulnerability to global warming: insights from bioenergetic modelling of catsharks under climate scenarios

IF 2.6 3区环境科学与生态学 Q2 ECOLOGY

Ecological Modelling

Pub Date : 2025-04-25 DOI: 10.1016/j.ecolmodel.2025.111157

Noémie Coulon , Sophie Elliott , Thomas Barreau , Julie Lucas , Emma Gousset , Eric Feunteun , Alexandre Carpentier

Ectotherms are especially vulnerable to global warming due to their temperature-sensitive metabolic processes, impacting survival and reproductive success. Elasmobranchs, with slow life histories and low reproductive rates, may face amplified risks. In this study, we investigated two catshark species with distinct life traits and distributions: the Small-spotted Catshark (Scyliorhinus canicula) and the Nursehound (S. stellaris). Using newly calibrated bioenergetic models, we assessed changes in growth, sexual maturity, offspring production, and population dynamics under two CMIP6 climate scenarios projected for 2100: SSP2–4.5 (Middle of the Road) and SSP5–8.5 (Fossil-fueled Development), comparing these to historical data (1994–2015). Survival rates for early life stages remained similar under historical temperatures (80 %) and SSP2 (83 %) but dropped sharply under SSP5 to 33 % for S. canicula and 23 % for S. stellaris. Under both SSP2 and SSP5, S. canicula showed slight delays in maturation, yet the proportion of mature individuals ultimately exceeded historical levels in SSP2. Conversely, S. stellaris experienced progressively delayed maturation with warming. In SSP5, reduced growth, reproduction, and survival caused a population crash for S. stellaris, suggesting potential extinction. Our results reveal contrasting climate impacts on these species, underscoring the risk for late-maturing, low-fecundity, and narrowly distributed species. This emphasizes the urgency of conservation strategies tailored to mitigate their vulnerability to global warming.

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引用次数: 0

A system dynamics modeling framework to evaluate impacts on economic, environmental, and social quality components of a U.S. Midwestern agroecosystem transitioning from row crop agriculture to mixed farming systems

IF 2.6 3区环境科学与生态学 Q2 ECOLOGY

Ecological Modelling

Pub Date : 2025-04-22 DOI: 10.1016/j.ecolmodel.2025.111142

Athanasios (Thanos) N. Papanicolaou , Keshav Basnet , Peter L. O’Brien , Kenneth M. Wacha , Robert W. Malone , David W. Archer

Agroecosystems comprise environmental, economic, and social components with complex interactions that affect systemwide performance. Attempts to describe or predict how agroecosystems respond to management must account for these interconnected components, so approaches that are limited to a single discipline cannot capture the complexities necessary for a holistic understanding of performance. The goal of this research is to develop a system dynamics (SD) modeling framework that can provide quantitative measures of consequences of management on each component of an agroecosystem. A SD framework is proposed with a description of model components, as well as an illustration of methodological steps to evaluate model performance through calibration, validation, and sensitivity testing. The model structure is based on a complex web of (i) stocks that describe the system’s state, (ii) flows that represent the direction and rate of change, and (iii) auxiliary parameters that assign quantitative values to each component. The capacity of the model to adequately evaluate agroecosystem response is demonstrated using a case study investigating environmental, economic, and social indicators while manipulating multiple management practices, including cover crops, tillage, and integration of crop and livestock operations. Importantly, the SD model identified tradeoffs in the three indicators that accurately reflect producer experiences when making management decisions. For example, the integration of cash crops, cover crops, and livestock clearly improves economic and environmental endpoints while negatively impacting social quality with reduction in leisure time. These findings suggest the SD modeling framework provides a viable approach for the quantitative evaluation of management interventions that can be adapted to a range of complex agroecosystems.

农业生态系统由环境、经济和社会构成，其复杂的相互作用影响着整个系统的绩效。要描述或预测农业生态系统如何对管理做出反应，就必须考虑到这些相互关联的组成部分，因此局限于单一学科的方法无法捕捉到全面了解系统性能所需的复杂性。本研究的目标是开发一个系统动力学（SD）建模框架，该框架可对农业生态系统各组成部分的管理后果进行量化测量。本文提出了一个 SD 框架，对模型的各个组成部分进行了描述，并说明了通过校准、验证和敏感性测试来评估模型性能的方法步骤。模型结构基于一个复杂的网络：(i) 描述系统状态的存量，(ii) 代表变化方向和速率的流量，以及 (iii) 为每个组成部分分配定量值的辅助参数。该模型通过一项案例研究证明了其充分评估农业生态系统响应的能力，该案例研究调查了环境、经济和社会指标，同时对多种管理方法进行了操作，包括覆盖作物、耕作以及作物和畜牧业的整合。重要的是，可持续发展模型确定了三个指标的权衡，准确反映了生产者在做出管理决策时的经验。例如，经济作物、覆盖作物和畜牧业的整合明显改善了经济和环境的终点，但同时也减少了闲暇时间，对社会质量产生了负面影响。这些研究结果表明，可持续发展建模框架为定量评估管理干预措施提供了一种可行的方法，可适用于一系列复杂的农业生态系统。

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引用次数: 0

Study in the ecosystem structure and trophodynamics in the Kuroshio-Oyashio Extension area

IF 2.6 3区环境科学与生态学 Q2 ECOLOGY

Ecological Modelling

Pub Date : 2025-04-21 DOI: 10.1016/j.ecolmodel.2025.111152

Gan Chen , Wen Wang , Rongrong Zhao , Qiuyun Ma , Shaoqin Wang , Siquan Tian , Dongyan Han

The Northwest Pacific (NWP) is not only the region with the highest fishery production in the world, but also the location of the Kuroshio-Oyashio Extension (KOE). Regular monitoring and assessment of marine ecosystem are essential for maintaining its stability and the sustainability of fishery products. Based on the survey data from the high-seas fishery resources survey in the KOE in 2023, the trophic structure and characteristics of open ocean ecosystem in this area were analyzed using the Ecopath with Ecosim model. A total of 25 functional groups were defined based on their ecological characteristics. The field sampling information was used as the biomass data to maximize the quality of the model. The results indicated that the trophic levels of these groups ranged from 1.00 to 4.35. Chub mackerel is a major economic species in the Northwest Pacific Ocean, and the ecotrophic efficiency of chub mackerel was lower than in previous studies (0.74 in 2019), indicating that the proportion of its production contributing to the ecosystem energy might have decreased. Mixed trophic impact results showed that the main interactions between functional groups are primarily predation and feeding competition. Total primary production/total respiration (TPP/TR), and total primary production/total biomass (TPP/TB) indicated the system maturity. Compared to previous studies in the KOE and its adjacent area ecosystems (the total system throughput was 3529.54 t·km^-2·year^-1 and the TR was 486.42 t·km^-2·year^-1), both the TST (1766.22 t·km^-2·year^-1) and the TR (151.27 t·km^-2·year^-1) were relatively lower, which revealed the low productivity characteristic of the KOE ecosystem. Combined with the high TPP/TR (7.31) and the low system omnivory index (0.20), these overall ecosystem characteristics suggested that the KOE ecosystem was structurally simple and vulnerable to disturbance from external activities. Sensitivity analysis indicated that the main output parameters of the model were highly sensitive to the changes in the biomass of the functional groups. This study provided a reference for ecosystem-based fisheries management in the open ocean waters of the KOE.

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引用次数: 0

Environmental system dynamics: Current development and applications 环境系统动力学：当前发展与应用

IF 2.6 3区环境科学与生态学 Q2 ECOLOGY

Ecological Modelling

Pub Date : 2025-04-21 DOI: 10.1016/j.ecolmodel.2025.111135

Sihui Xin , Zhouyuan Li , Junsong Nong , Jiaxin Wu , Xinwei Zou , Ruijin Wu , Shikui Dong , Rongling Wu , Shaopeng Wang

System Dynamics (SD) has emerged as a fundamental and powerful modeling methodology for understanding and simulating the behavior of both natural and social-economic systems. This review explores the historical development, key concepts, and broad applications of SD as a fundamental modeling approach. Tracing its evolution from the its inception since 1960s, the paper outlines the four major phases of SD's growth, from its initial conceptualization, through its methodological refinements, to its widespread application in ecosystems, and socio-economic systems in recent over the half century. The review highlights the development of SD communities across the globe, including the North American school, European clusters, and the growing body of work in China, and the progress in the global collaboration. We discuss and organize the foundational paired concepts of SD, including stock-flow relationships, the structure-behavior paradigm, the cause-effect process, and the loop-feedback paradigm. We summarize the SD modeling workflow protocol in the four stages, as conceptualization, visualization, quantification, and verification. It demonstrates good practices of SD modeling in various ecological contexts, spanning population, community, landscape, and macro-ecosystem levels, while emphasizing the method's adaptability and capacity for spatial modeling. Building on an extensive literature review and bibliometric analysis, the paper synthesizes key progress in SD modeling while offering insights into future perspectives and potential advancements. It concludes by reflecting on SD's ability to address multi-scale, multi-dimensional challenges and its compatibility with emerging novel approaches. Our goal is to bridge SD with contemporary ecological modeling practices by systematically reviewing the theoretical and practical advances of SD. This review provides insights for scholars and practitioners seeking to embed SD approach to the environmental and ecological systems simulation.

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引用次数: 0

System dynamics applied to the e-waste value chain: A brazilian case study

IF 2.6 3区环境科学与生态学 Q2 ECOLOGY

Ecological Modelling

Pub Date : 2025-04-18 DOI: 10.1016/j.ecolmodel.2025.111139

Emmanuelle Soares de Carvalho Freitas, Lúcia Helena Xavier

The reverse supply chain focuses on the reuse and recycling of products, components, and materials. In this context, urban mining (UM) plays a crucial role in recovering valuable materials through circular solutions from secondary sources. This study explores the application of system dynamics (SD) to analyze UM processes, specifically in managing WEEE. The research examines the influence of business models and regulatory frameworks on the recovery of materials. It also introduces the concept of the transition zone (TZ), an area that lies between different stages of development, which can either help move things forward or create setbacks, shaping the future of managing this type of waste. The findings reveal that WEEE recovery is regulated to varying degrees across regions, with Europe and North America having established frameworks, while other countries, including Brazil, are still developing regulations. The SD model highlights several business models for WEEE recycling, each at different stages of maturity. The study shows that creating tailored regulations can promote circular economy principles, improving efficiency in resource recovery. However, the lack of formal frameworks often leads to the informal sector's exclusion, hindering effective waste management. The research also emphasizes the importance of developing public policies that streamline cross-border regulations and further refine business models to optimize WEEE management. The findings provide valuable insights for future policy development and operational strategies to support urban mining and resource recovery from WEEE, with recommendations for integrating these principles into local and global systems.

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引用次数: 0

A multi-stochastic fractional programming for sustainable forestry ecological restoration: Managing uncertainties in Kashgar Region, Xinjiang

IF 2.6 3区环境科学与生态学 Q2 ECOLOGY

Ecological Modelling

Pub Date : 2025-04-17 DOI: 10.1016/j.ecolmodel.2025.111131

Yi Bai , Guohe Huang , Dencheng Han , Bin Luo , Yongping Li , Shan Zhao

Forest ecological restoration is becoming increasingly crucial in global sustainable development plans aimed at mitigating climate change and achieving carbon neutrality. Optimal management is now a key component in this process. To address the challenges and evolving demands of stakeholders in forest ecological restoration, this study integrates interval linear programming (ILP), chance-constrained programming (CCP), mixed-integer programming (MIP), and fractional planning (FP) within an optimization framework, developing an interval linear chance-constrained mixed integer fractional programming (ICCMFP) model. The model offers several key advantages in optimizing ecological, economic, and social challenges in forestry: (1) managing compound risks from uncertainties in land resources, price fluctuations, and water availability; (2) balancing conflicting objectives while enabling broader stakeholder participation in the management process; (3) supporting multi-scenario analyses to quantitatively evaluate optimal strategies and offer valuable insights for decision-makers. Taking the Xinjiang Kashgar region as a case study, the applicability of the proposed model has been evaluated under multiple objectives and scenarios. The results indicate that the ICCMFP model provides robust strategies across various water allocation scenarios, price fluctuations, and default risks. In the CB-C model, increased carbon benefits correspond to a greater willingness to expand, resulting in the total area of expansion growing from [18,524.0, 24,953.7] ha at the Chinese carbon price to [23,503.6, 30,626.0] ha at the European Union carbon price in the S1 (

p_{i}

= 0.01) scenario. Compared to the interval chance-constrained mixed integer programming (ICCMP) model, the ICCMFP model offers more flexible optimization solutions through fractional programming, demonstrating its adaptability and reliability. This model is expected to offer substantial support for decision-making in sustainable ecological restoration projects globally.

{"title":"A multi-stochastic fractional programming for sustainable forestry ecological restoration: Managing uncertainties in Kashgar Region, Xinjiang","authors":"Yi Bai , Guohe Huang , Dencheng Han , Bin Luo , Yongping Li , Shan Zhao","doi":"10.1016/j.ecolmodel.2025.111131","DOIUrl":"10.1016/j.ecolmodel.2025.111131","url":null,"abstract":"<div><div>Forest ecological restoration is becoming increasingly crucial in global sustainable development plans aimed at mitigating climate change and achieving carbon neutrality. Optimal management is now a key component in this process. To address the challenges and evolving demands of stakeholders in forest ecological restoration, this study integrates interval linear programming (ILP), chance-constrained programming (CCP), mixed-integer programming (MIP), and fractional planning (FP) within an optimization framework, developing an interval linear chance-constrained mixed integer fractional programming (ICCMFP) model. The model offers several key advantages in optimizing ecological, economic, and social challenges in forestry: (1) managing compound risks from uncertainties in land resources, price fluctuations, and water availability; (2) balancing conflicting objectives while enabling broader stakeholder participation in the management process; (3) supporting multi-scenario analyses to quantitatively evaluate optimal strategies and offer valuable insights for decision-makers. Taking the Xinjiang Kashgar region as a case study, the applicability of the proposed model has been evaluated under multiple objectives and scenarios. The results indicate that the ICCMFP model provides robust strategies across various water allocation scenarios, price fluctuations, and default risks. In the CB-C model, increased carbon benefits correspond to a greater willingness to expand, resulting in the total area of expansion growing from [18,524.0, 24,953.7] ha at the Chinese carbon price to [23,503.6, 30,626.0] ha at the European Union carbon price in the S1 (<span><math><msub><mi>p</mi><mi>i</mi></msub></math></span> = 0.01) scenario. Compared to the interval chance-constrained mixed integer programming (ICCMP) model, the ICCMFP model offers more flexible optimization solutions through fractional programming, demonstrating its adaptability and reliability. This model is expected to offer substantial support for decision-making in sustainable ecological restoration projects globally.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"506 ","pages":"Article 111131"},"PeriodicalIF":2.6,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143839275","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}

引用次数: 0

Estimating stomatal conductance under drought: Parameterizing a phenomenological model and evaluating roles of the energy balance equation

IF 2.6 3区环境科学与生态学 Q2 ECOLOGY

Ecological Modelling

Pub Date : 2025-04-14 DOI: 10.1016/j.ecolmodel.2025.111133

Qian Liu , Fangmin Zhang , Xinyou Yin

Accurate estimation of stomatal conductance (g_s) is fundamental for modeling coupled photosynthesis-transpiration responses to climate change, yet current approaches face limitations under drought conditions. To predict g_s under drought, the widely-used Ball-Woodrow-Berry (BWB) model relies on empirical soil moisture functions (f_w) with uncertain validity. As a physically-based alternative, inverted Penman-Monteith (PM) equation derived from leaf energy balance principles offers a mechanistic solution. To evaluate the implicit assumption that BWB model parameters (excluding f_w) remain not altered by drought and the predictive capability of the PM-based energy balance approach, a two-year field experiment in the nationally-planted oil crops—soybean (Glycine max L.) and oilseed rape (Brassica napus L.) was conducted. Our results revealed that crop-specific responses in BWB parameter variations during water stress, with significant predictive errors occurring if responses of g_s to vapor pressure deficit were not considered. While the PM-based energy balance approach performed well for g_s of oilseed rape, it required modification for soybean to account for greater leaf temperature fluctuations (ΔT_leaf) under water-deficit relative to well-watered conditions caused by more variable water deficits. Our study demonstrated that integrating an inversed PM equation for g_s with the CO₂-diffusion law and a biochemical photosynthesis model accounting for ΔT_leaf is an effective approach to predict both photosynthetic rate and g_s under water stress without introducing empirical functions.

{"title":"Estimating stomatal conductance under drought: Parameterizing a phenomenological model and evaluating roles of the energy balance equation","authors":"Qian Liu , Fangmin Zhang , Xinyou Yin","doi":"10.1016/j.ecolmodel.2025.111133","DOIUrl":"10.1016/j.ecolmodel.2025.111133","url":null,"abstract":"<div><div>Accurate estimation of stomatal conductance (<em>g</em><sub>s</sub>) is fundamental for modeling coupled photosynthesis-transpiration responses to climate change, yet current approaches face limitations under drought conditions. To predict <em>g</em><sub>s</sub> under drought, the widely-used Ball-Woodrow-Berry (BWB) model relies on empirical soil moisture functions (<em>f</em><sub>w</sub>) with uncertain validity. As a physically-based alternative, inverted Penman-Monteith (PM) equation derived from leaf energy balance principles offers a mechanistic solution. To evaluate the implicit assumption that BWB model parameters (excluding <em>f</em><sub>w</sub>) remain not altered by drought and the predictive capability of the PM-based energy balance approach, a two-year field experiment in the nationally-planted oil crops—soybean (<em>Glycine max</em> L.) and oilseed rape (<em>Brassica napus</em> L.) was conducted. Our results revealed that crop-specific responses in BWB parameter variations during water stress, with significant predictive errors occurring if responses of <em>g</em><sub>s</sub> to vapor pressure deficit were not considered. While the PM-based energy balance approach performed well for <em>g</em><sub>s</sub> of oilseed rape, it required modification for soybean to account for greater leaf temperature fluctuations (Δ<em>T</em><sub>leaf</sub>) under water-deficit relative to well-watered conditions caused by more variable water deficits. Our study demonstrated that integrating an inversed PM equation for <em>g</em><sub>s</sub> with the CO<sub>2</sub>-diffusion law and a biochemical photosynthesis model accounting for Δ<em>T</em><sub>leaf</sub> is an effective approach to predict both photosynthetic rate and <em>g</em><sub>s</sub> under water stress without introducing empirical functions.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"505 ","pages":"Article 111133"},"PeriodicalIF":2.6,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826251","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}

引用次数: 0

Improving process-based modeling of crop production in the DayCent ecosystem model with solar-induced chlorophyll fluorescence

IF 2.6 3区环境科学与生态学 Q2 ECOLOGY

Ecological Modelling

Pub Date : 2025-04-13 DOI: 10.1016/j.ecolmodel.2025.111116

Wenguang Sun , Stephen M. Ogle , Yao Zhang , Andrew E. Schuh , Ian T Baker , Troy S. Magney , Francis Ulep , Shahriar S. Heydari

Solar-induced chlorophyll fluorescence (SIF), as the red and far‐red light emitted from excited chlorophyll‐a molecules during photosynthesis, has been increasingly used for estimating gross primary production (GPP). DayCent is a process-based ecosystem model that mechanistically simulates time-dependent biogeochemical processes of the plant and soil system at a daily time-step. The present study explored a series of key modifications to develop photosynthetic equations with the Mechanistic Light Response (MLR) framework. We used published ground‐based measurements derived from five cropland sites with multiple years of data in the central region of United States to calibrate and evaluate the MLR framework in DayCent. Three versions of the DayCent SIF model were developed and tested based on variation in algorithms and main parameters in MLR equation. The best fit model version for predicting seasonal GPP rates used temperature to capture the seasonal variation of the maximum photochemical efficiency of photosystem II (Φ_PSIImax) and directly calculated the intercellular CO₂ concentration (C_i) based on Eco-Evolutionary Optimality (EEO) theory, with index of agreement (IA) varying between 0.76 and 0.88 and root mean square error (RMSE) between 3.93 and 6.76 g C m⁻² d^-1. This version of the model also has significantly better agreement with measured GPP, as demonstrated by higher IA value and lower RMSE value when compared to conventional Radiation Use Efficiency (RUE) approaches, even when informed by the MODIS Enhanced Vegetation Index (EVI). This study demonstrates that a mechanistic modeling framework informed by SIF observations can improve process-based modeling of crop production.

太阳诱导叶绿素荧光（SIF）是光合作用过程中激发的叶绿素-a 分子发出的红光和远红光，越来越多地被用于估算总初级生产力（GPP）。DayCent 是一个以过程为基础的生态系统模型，从机理上模拟了植物和土壤系统以日为时间单位的生物地球化学过程。本研究探索了一系列关键的修改，以利用光响应机制（MLR）框架开发光合作用方程。我们使用了从美国中部地区五个耕地站点获得的多年数据，对 DayCent 中的 MLR 框架进行了校准和评估。根据算法和 MLR 方程中主要参数的变化，我们开发并测试了三个版本的 DayCent SIF 模型。预测季节性 GPP 速率的最佳拟合模型版本使用温度来捕捉光系统 II 最大光化学效率（ΦPSIImax）的季节性变化，并根据生态进化优化（EEO）理论直接计算胞间 CO2 浓度（Ci），其一致指数（IA）在 0.76 和 0.88 之间变化，均方根误差（RMSE）在 3.93 和 6.76 g C m-2 d-1 之间变化。与传统的辐射利用效率（RUE）方法相比，这一版本的模型与测量的 GPP 的一致性也明显更好，表现为更高的 IA 值和更低的 RMSE 值，即使以 MODIS 增强植被指数（EVI）为参考也是如此。这项研究表明，以 SIF 观测数据为依据的机理建模框架可以改进基于过程的作物生产建模。

{"title":"Improving process-based modeling of crop production in the DayCent ecosystem model with solar-induced chlorophyll fluorescence","authors":"Wenguang Sun , Stephen M. Ogle , Yao Zhang , Andrew E. Schuh , Ian T Baker , Troy S. Magney , Francis Ulep , Shahriar S. Heydari","doi":"10.1016/j.ecolmodel.2025.111116","DOIUrl":"10.1016/j.ecolmodel.2025.111116","url":null,"abstract":"<div><div>Solar-induced chlorophyll fluorescence (SIF), as the red and far‐red light emitted from excited chlorophyll‐a molecules during photosynthesis, has been increasingly used for estimating gross primary production (GPP). DayCent is a process-based ecosystem model that mechanistically simulates time-dependent biogeochemical processes of the plant and soil system at a daily time-step. The present study explored a series of key modifications to develop photosynthetic equations with the Mechanistic Light Response (MLR) framework. We used published ground‐based measurements derived from five cropland sites with multiple years of data in the central region of United States to calibrate and evaluate the MLR framework in DayCent. Three versions of the DayCent SIF model were developed and tested based on variation in algorithms and main parameters in MLR equation. The best fit model version for predicting seasonal GPP rates used temperature to capture the seasonal variation of the maximum photochemical efficiency of photosystem II (Φ<sub>PSIImax</sub>) and directly calculated the intercellular CO<sub>2</sub> concentration (C<sub>i</sub>) based on Eco-Evolutionary Optimality (EEO) theory, with index of agreement (IA) varying between 0.76 and 0.88 and root mean square error (RMSE) between 3.93 and 6.76 g C <em>m</em><sup>−2</sup> d<sup>-1</sup>. This version of the model also has significantly better agreement with measured GPP, as demonstrated by higher IA value and lower RMSE value when compared to conventional Radiation Use Efficiency (RUE) approaches, even when informed by the MODIS Enhanced Vegetation Index (EVI). This study demonstrates that a mechanistic modeling framework informed by SIF observations can improve process-based modeling of crop production.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"505 ","pages":"Article 111116"},"PeriodicalIF":2.6,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823449","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}

引用次数: 0

Explicit predictions of species richness from net primary productivity: setting and discussion

IF 2.6 3区环境科学与生态学 Q2 ECOLOGY

Ecological Modelling

Pub Date : 2025-04-13 DOI: 10.1016/j.ecolmodel.2025.111111

Allen G. Hunt

Critical problems in ecology, such as plant species richness and net primary productivity, NPP, are linked with the principal water fluxes of hydrologic sciences, evapotranspiration (plant growth), and run-off (chemical weathering and soil formation). Each of these links is established using modern physics approaches based on percolation theory from complexity studies with the resulting spatio-temporal scaling functions ultimately derived from renormalization-based methods. Approaching such problems from the perspective of the hydrologic fluxes, rather than, e.g., soil moisture content, and using such methods of physics allows application of a direct ecological optimality hypothesis (Darwin-based) regarding maximization of NPP with respect to the fluxes. This procedure opens up possibilities for a wide range of (verified) predictions in (eco-)hydrology as well as a range of discussions on Darwinian and Newtonian perspectives, the value of generalizations from thermodynamics vs. statistical mechanics, simplifications arising from focus on fluxes, rather than state variables, etc., and may provide a foundation for advancing species richness theory as well.

{"title":"Explicit predictions of species richness from net primary productivity: setting and discussion","authors":"Allen G. Hunt","doi":"10.1016/j.ecolmodel.2025.111111","DOIUrl":"10.1016/j.ecolmodel.2025.111111","url":null,"abstract":"<div><div>Critical problems in ecology, such as plant species richness and net primary productivity, <em>NPP</em>, are linked with the principal water fluxes of hydrologic sciences, evapotranspiration (plant growth), and run-off (chemical weathering and soil formation). Each of these links is established using modern physics approaches based on percolation theory from complexity studies with the resulting spatio-temporal scaling functions ultimately derived from renormalization-based methods. Approaching such problems from the perspective of the hydrologic fluxes, rather than, e.g., soil moisture content, and using such methods of physics allows application of a direct ecological optimality hypothesis (Darwin-based) regarding maximization of <em>NPP</em> with respect to the fluxes. This procedure opens up possibilities for a wide range of (verified) predictions in (eco-)hydrology as well as a range of discussions on Darwinian and Newtonian perspectives, the value of generalizations from thermodynamics vs. statistical mechanics, simplifications arising from focus on fluxes, rather than state variables, etc., and may provide a foundation for advancing species richness theory as well.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"505 ","pages":"Article 111111"},"PeriodicalIF":2.6,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823450","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}

引用次数: 0