Pub Date : 2024-11-20DOI: 10.1016/j.ecolmodel.2024.110950
Antti Takolander , Louise Forsblom , Seppo Hellsten , Jari Ilmonen , Ari-Pekka Jokinen , Niko Kallio , Sampsa Koponen , Sakari Väkevä , Elina Virtanen
Species Distribution Models (SDMs) are frequently applied in ecological research, but geographic transferability of SDMs holds major uncertainties. Here, we assess the cross-realm (sea to lake) geographic transferability of four SDM methods: Generalized Linear Models (GLMs), Generalized Additive Models (GAMs), Boosted Regression Trees (BRTs), and Bayesian Additive Regression Trees (BARTs) predicting occurrences of freshwater macrophytes from brackish water sea area (Bothnian Bay) to a freshwater lake environment in Finland. We found that the SDM method applied did not affect model transferability, and majority of the variation in transferability performance was associated with species. For most species model transferability was low, but reasonably good on one third of the species modelled, which had similar prevalences in both marine and freshwater data. These were emergent species or species growing close to shoreline, which presumably share similar environmental niche in terms of growing depth and water turbidity between the two environments. Generally, models which had high interpolation performance, also had higher transferability, but this relationship was not dependent on the SDM method applied. Our results suggest that species prevalence and species-specific characteristics, such as growth form, life history traits and ecological niche, are main contributors to geographic transferability of SDMs.
{"title":"Cross-realm transferability of species distribution models–Species characteristics and prevalence matter more than modelling methods applied","authors":"Antti Takolander , Louise Forsblom , Seppo Hellsten , Jari Ilmonen , Ari-Pekka Jokinen , Niko Kallio , Sampsa Koponen , Sakari Väkevä , Elina Virtanen","doi":"10.1016/j.ecolmodel.2024.110950","DOIUrl":"10.1016/j.ecolmodel.2024.110950","url":null,"abstract":"<div><div>Species Distribution Models (SDMs) are frequently applied in ecological research, but geographic transferability of SDMs holds major uncertainties. Here, we assess the cross-realm (sea to lake) geographic transferability of four SDM methods: Generalized Linear Models (GLMs), Generalized Additive Models (GAMs), Boosted Regression Trees (BRTs), and Bayesian Additive Regression Trees (BARTs) predicting occurrences of freshwater macrophytes from brackish water sea area (Bothnian Bay) to a freshwater lake environment in Finland. We found that the SDM method applied did not affect model transferability, and majority of the variation in transferability performance was associated with species. For most species model transferability was low, but reasonably good on one third of the species modelled, which had similar prevalences in both marine and freshwater data. These were emergent species or species growing close to shoreline, which presumably share similar environmental niche in terms of growing depth and water turbidity between the two environments. Generally, models which had high interpolation performance, also had higher transferability, but this relationship was not dependent on the SDM method applied. Our results suggest that species prevalence and species-specific characteristics, such as growth form, life history traits and ecological niche, are main contributors to geographic transferability of SDMs.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"499 ","pages":"Article 110950"},"PeriodicalIF":2.6,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703338","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}
Pub Date : 2024-11-20DOI: 10.1016/j.ecolmodel.2024.110949
Camilo E. Martínez , Sergio A. Orrego , Jorge A. Giraldo , Jorge I. del Valle , Freddy Hernández-Barajas , Diego A. David
Growth depensation, the variation of size with age exhibited by populations, is attributed to biological, ecological, and environmental factors, as well as autocorrelation. Several studies have focused on the study of diameter growth of tropical trees to obtain information on ontogenic traits and silvicultural metrics of interest for ecology and forest management. However, few studies have rigorously and adequately considered autocorrelation as a primary factor contributing to growth depensation. The aim of this study was to investigate diameter growth in tree species from the Chocó biogeographic region. We used tree-ring data corresponding to 38 trees and 5 species. Our modeling approach included von Bertalanffy type equations to estimate diameter growth trajectories for each species using mixed effects models. ARIMA specifications were included in the residual terms to account for autocorrelation. The estimated parameters allowed us to calculate ontogenic traits and silvicultural metrics for each species. The results indicate that autocorrelation was a critical factor in growth depensation for all species studied, and was satisfactorily accounted for by the proposed modeling approach. Autocorrelation patterns on residuals showed a stochastic trend and were investigated by correlation structures of ARIMA(1,1,0) and ARIMA(2,1,0). Ontogenic traits and silvicultural metrics obtained for these species were biologically consistent, providing reliable and useful information to understand the population ecology of tropical trees and to inform management and conservation strategies of natural forests.
{"title":"Autocorrelation as a critical factor of growth depensation of tropical trees in the Chocó biogeographic region","authors":"Camilo E. Martínez , Sergio A. Orrego , Jorge A. Giraldo , Jorge I. del Valle , Freddy Hernández-Barajas , Diego A. David","doi":"10.1016/j.ecolmodel.2024.110949","DOIUrl":"10.1016/j.ecolmodel.2024.110949","url":null,"abstract":"<div><div>Growth depensation, the variation of size with age exhibited by populations, is attributed to biological, ecological, and environmental factors, as well as autocorrelation. Several studies have focused on the study of diameter growth of tropical trees to obtain information on ontogenic traits and silvicultural metrics of interest for ecology and forest management. However, few studies have rigorously and adequately considered autocorrelation as a primary factor contributing to growth depensation. The aim of this study was to investigate diameter growth in tree species from the Chocó biogeographic region. We used tree-ring data corresponding to 38 trees and 5 species. Our modeling approach included von Bertalanffy type equations to estimate diameter growth trajectories for each species using mixed effects models. ARIMA specifications were included in the residual terms to account for autocorrelation. The estimated parameters allowed us to calculate ontogenic traits and silvicultural metrics for each species. The results indicate that autocorrelation was a critical factor in growth depensation for all species studied, and was satisfactorily accounted for by the proposed modeling approach. Autocorrelation patterns on residuals showed a stochastic trend and were investigated by correlation structures of ARIMA(1,1,0) and ARIMA(2,1,0). Ontogenic traits and silvicultural metrics obtained for these species were biologically consistent, providing reliable and useful information to understand the population ecology of tropical trees and to inform management and conservation strategies of natural forests.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"500 ","pages":"Article 110949"},"PeriodicalIF":2.6,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142721711","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}
Pub Date : 2024-11-19DOI: 10.1016/j.ecolmodel.2024.110921
Eline Le Moan , Laure Pecquerie , Laure Régnier-Brisson , Hélène Hégaret , Paulo F. Lagos , Léo Heyer , Salvador Emilio Lluch-Cota , Fred Jean , Jonathan Flye-Sainte-Marie
Pectinid species (scallops) hold significant economic value, but their filtration activity makes them vulnerable to harmful algal blooms, particularly Pseudo-nitzschia species producing domoic acid (DA). Domoic acid contamination can lead to amnesic shellfish poisoning in humans, causing prolonged fisheries closures and sales bans. This study aimed to compare several pectinid species to investigate if inter-specific differences in energetic traits could be linked to their ability to depurate the toxin. Using Dynamic Energy Budget (DEB) theory and the AmP multi-species estimation procedure, we analysed five species: two slow depurators (Pecten maximus and Placopecten magellanicus) and three hypothesised fast depurators (Argopecten purpuratus, Mimachlamys varia, and Nodipecten subnodosus). Results showed differences among species in assimilation rates, somatic maintenance rates, and reserve mobilisation rates but only the reserve mobilisation rates (i.e. the energy conductance parameter) consistently increased along the “slow-to-fast” depuration gradient. This research lays the groundwork for developing toxin kinetics models to quantify the processes affecting DA accumulation and depuration, and to assess the retention time of DA. Our approach and results will therefore not only be of interest to the DEB community in terms of multi-species approaches, but are likely to have applications in pectinid aquaculture and fisheries management.
果胶类（扇贝）具有重要的经济价值，但它们的过滤活性使其很容易受到有害藻类大量繁殖的影响，尤其是会产生多羧酸（DA）的假栉水母类（Pseudo-nitzschia）。多羧酸污染可导致人类失忆性贝类中毒，造成长期的渔业关闭和销售禁令。本研究旨在对几种果胶物种进行比较，以调查能量特征的种间差异是否与它们去除毒素的能力有关。利用动态能量预算（DEB）理论和 AmP 多物种估算程序，我们对五个物种进行了分析：两个慢速去毒者（Pecten maximus 和 Placopecten magellanicus）和三个假定的快速去毒者（Argopecten purpuratus、Mimachlamys varia 和 Nodipecten subnodosus）。结果表明，不同物种在同化率、体细胞维持率和储备动员率方面存在差异，但只有储备动员率（即能量传导参数）沿着 "慢-快 "去势梯度持续上升。这项研究为开发毒素动力学模型奠定了基础，以量化影响 DA 积累和净化的过程，并评估 DA 的滞留时间。因此，我们的方法和结果不仅在多物种方法方面引起了 DEB 界的兴趣，而且很可能在果胶水产养殖和渔业管理方面得到应用。
{"title":"Inter-species comparison of life traits related to amnesic shellfish toxin kinetic in five pectinid species","authors":"Eline Le Moan , Laure Pecquerie , Laure Régnier-Brisson , Hélène Hégaret , Paulo F. Lagos , Léo Heyer , Salvador Emilio Lluch-Cota , Fred Jean , Jonathan Flye-Sainte-Marie","doi":"10.1016/j.ecolmodel.2024.110921","DOIUrl":"10.1016/j.ecolmodel.2024.110921","url":null,"abstract":"<div><div>Pectinid species (scallops) hold significant economic value, but their filtration activity makes them vulnerable to harmful algal blooms, particularly <em>Pseudo-nitzschia</em> species producing domoic acid (DA). Domoic acid contamination can lead to amnesic shellfish poisoning in humans, causing prolonged fisheries closures and sales bans. This study aimed to compare several pectinid species to investigate if inter-specific differences in energetic traits could be linked to their ability to depurate the toxin. Using Dynamic Energy Budget (DEB) theory and the AmP multi-species estimation procedure, we analysed five species: two slow depurators (<em>Pecten maximus</em> and <em>Placopecten magellanicus</em>) and three hypothesised fast depurators (<em>Argopecten purpuratus</em>, <em>Mimachlamys varia</em>, and <em>Nodipecten subnodosus</em>). Results showed differences among species in assimilation rates, somatic maintenance rates, and reserve mobilisation rates but only the reserve mobilisation rates (<em>i.e.</em> the energy conductance parameter) consistently increased along the “slow-to-fast” depuration gradient. This research lays the groundwork for developing toxin kinetics models to quantify the processes affecting DA accumulation and depuration, and to assess the retention time of DA. Our approach and results will therefore not only be of interest to the DEB community in terms of multi-species approaches, but are likely to have applications in pectinid aquaculture and fisheries management.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"499 ","pages":"Article 110921"},"PeriodicalIF":2.6,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142704008","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}
Pub Date : 2024-11-19DOI: 10.1016/j.ecolmodel.2024.110909
Eryn K. Turney , Gregory C. Goodrum , W. Carl Saunders , Timothy E. Walsworth , Sarah E. Null
Aquatic habitat suitability models are increasingly coupled with water management models to estimate environmental effects of water management. Many types of habitat models exist, but there are no standard methods to compare predictive performance of habitat model types for use with water management models. In this study, we compared three common aquatic habitat model types: a hydraulic-habitat model, a habitat threshold model, and a geospatial model. Each of the models predicted native Bonneville Cutthroat Trout distribution in the Bear River Watershed (Utah, Idaho, and Wyoming, USA) at a monthly timestep. We compared the differences in predictive performance among models by validating 1) environmental predictors of the models with field observations from summer 2022, using the coefficient of determination (R²), Nash–Sutcliffe efficiency (NSE) index, and percent bias (PBIAS) and 2) habitat suitability estimates generated by each model with fish presence data and three accuracy metrics developed for this study. Validation of environmental predictors revealed observed conditions were not well represented by any of the three models—a function of either outdated, incorrect, or over-generalized input data. Validation of habitat suitability predictions using Bonneville Cutthroat Trout presence data showed the habitat threshold model most accurately classified fish presence observations in suitable habitat, but suitable habitat was likely overpredicted. While more precise habitat modeling methods may be useful to support generalized habitat estimates for native fish, overall, simple models, like the habitat threshold model, are promising for incorporating ecological objectives into water management models.
{"title":"Comparing commonly used aquatic habitat modeling methods for native fish","authors":"Eryn K. Turney , Gregory C. Goodrum , W. Carl Saunders , Timothy E. Walsworth , Sarah E. Null","doi":"10.1016/j.ecolmodel.2024.110909","DOIUrl":"10.1016/j.ecolmodel.2024.110909","url":null,"abstract":"<div><div>Aquatic habitat suitability models are increasingly coupled with water management models to estimate environmental effects of water management. Many types of habitat models exist, but there are no standard methods to compare predictive performance of habitat model types for use with water management models. In this study, we compared three common aquatic habitat model types: a hydraulic-habitat model, a habitat threshold model, and a geospatial model. Each of the models predicted native Bonneville Cutthroat Trout distribution in the Bear River Watershed (Utah, Idaho, and Wyoming, USA) at a monthly timestep. We compared the differences in predictive performance among models by validating 1) environmental predictors of the models with field observations from summer 2022, using the coefficient of determination (R²), Nash–Sutcliffe efficiency (NSE) index, and percent bias (PBIAS) and 2) habitat suitability estimates generated by each model with fish presence data and three accuracy metrics developed for this study. Validation of environmental predictors revealed observed conditions were not well represented by any of the three models—a function of either outdated, incorrect, or over-generalized input data. Validation of habitat suitability predictions using Bonneville Cutthroat Trout presence data showed the habitat threshold model most accurately classified fish presence observations in suitable habitat, but suitable habitat was likely overpredicted. While more precise habitat modeling methods may be useful to support generalized habitat estimates for native fish, overall, simple models, like the habitat threshold model, are promising for incorporating ecological objectives into water management models.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"499 ","pages":"Article 110909"},"PeriodicalIF":2.6,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142703337","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}
Pub Date : 2024-11-19DOI: 10.1016/j.ecolmodel.2024.110946
Hicham Fatnassi , Reda Errais , Christine Poncet
The increasing demand for sustainable biomass has made microalgae farming into the spotlight as a viable source of biofuels, nutraceuticals, and other valuable products. Raceway ponds are one of the most common systems in algaculture due to their simplicity and cost-effectiveness. However, their efficiency is significantly influenced by surrounding microclimate conditions. In this study, we present a Computational Fluid Dynamics (CFD) analysis aimed at optimizing greenhouse design to enhance microalgae production in a raceway pond housed within a controlled greenhouse environment. The research focuses on evaluating the influence of greenhouse microclimate parameters on water's thermal dynamics in the pond. Simulations were conducted to assess how different greenhouse geometries and ventilation configurations affect the heat exchange between the water surface and air within the greenhouse, as well as the internal flow dynamics, both of which are critical for optimal algae growth.
The results provide insights into the optimal greenhouse design parameters that maintain the optimal water temperatures in the pond while minimizing thermal fluctuations to enhance microalgae productivity. Specifically, a significant 5 °C temperature difference was observed between the pond's surface and bottom, mainly due to convective heat transfer. Key design factors, such as greenhouse height and ventilation rates, were shown to have a substantial impact on water temperature.
The insights gained are essential for optimizing greenhouse design and ventilation strategies to maximize algae growth and production efficiency. This preliminary modeling lays the foundation for future sensitivity analyses aimed at refining the system, ultimately improving algae cultivation in controlled environment agricultural systems.
对可持续生物质日益增长的需求使微藻类养殖成为生物燃料、营养保健品和其他有价值产品的可行来源。赛道池塘因其简单和成本效益高而成为最常见的藻类养殖系统之一。然而，其效率受周围小气候条件的影响很大。在本研究中，我们介绍了一项计算流体动力学（CFD）分析，旨在优化温室设计，以提高置于受控温室环境中的赛道池塘的微藻产量。研究重点是评估温室小气候参数对池塘水热动力学的影响。模拟评估了不同的温室几何形状和通风配置如何影响温室内水面和空气之间的热交换以及内部流动动力学，这两者对于水藻的最佳生长至关重要。具体而言，观察到池塘表面和底部之间存在 5 °C 的明显温差，这主要是由于对流传热造成的。研究表明，温室高度和通风率等关键设计因素会对水温产生重大影响。研究结果对于优化温室设计和通风策略，最大限度地提高藻类生长和生产效率至关重要。这一初步建模为未来的敏感性分析奠定了基础，旨在完善系统，最终改善受控环境农业系统中的水藻培养。
{"title":"Optimizing greenhouse design for enhanced microalgae production: A CFD Analysis of microclimate and water thermal dynamics in raceway ponds","authors":"Hicham Fatnassi , Reda Errais , Christine Poncet","doi":"10.1016/j.ecolmodel.2024.110946","DOIUrl":"10.1016/j.ecolmodel.2024.110946","url":null,"abstract":"<div><div>The increasing demand for sustainable biomass has made microalgae farming into the spotlight as a viable source of biofuels, nutraceuticals, and other valuable products. Raceway ponds are one of the most common systems in algaculture due to their simplicity and cost-effectiveness. However, their efficiency is significantly influenced by surrounding microclimate conditions. In this study, we present a Computational Fluid Dynamics (CFD) analysis aimed at optimizing greenhouse design to enhance microalgae production in a raceway pond housed within a controlled greenhouse environment. The research focuses on evaluating the influence of greenhouse microclimate parameters on water's thermal dynamics in the pond. Simulations were conducted to assess how different greenhouse geometries and ventilation configurations affect the heat exchange between the water surface and air within the greenhouse, as well as the internal flow dynamics, both of which are critical for optimal algae growth.</div><div>The results provide insights into the optimal greenhouse design parameters that maintain the optimal water temperatures in the pond while minimizing thermal fluctuations to enhance microalgae productivity. Specifically, a significant 5 °C temperature difference was observed between the pond's surface and bottom, mainly due to convective heat transfer. Key design factors, such as greenhouse height and ventilation rates, were shown to have a substantial impact on water temperature.</div><div>The insights gained are essential for optimizing greenhouse design and ventilation strategies to maximize algae growth and production efficiency. This preliminary modeling lays the foundation for future sensitivity analyses aimed at refining the system, ultimately improving algae cultivation in controlled environment agricultural systems.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"499 ","pages":"Article 110946"},"PeriodicalIF":2.6,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142704028","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}
Pub Date : 2024-11-16DOI: 10.1016/j.ecolmodel.2024.110943
Henry Amorocho-Daza , Janez Sušnik , Pieter van der Zaag , Jill H. Slinger
Problems manifested within social-ecological systems (SES) exhibit dynamic complexity and hold implications for current and future human well-being and environmental sustainability. The complexity of these issues, the ever-present uncertainty inherent to SES, and the multi-stakeholder settings in which they are discussed call for participatory modelling to support decision-making on socio-environmental issues. Yet, this challenging endeavour requires a structured approach — a modelling cycle — to facilitate engagement with the implications of participation and uncertainty as focal points for Good Modelling Practice (GMP). Here we propose an integrated policy analysis framework for SES modelling using System Dynamics (SD). This framework stems from integrating two existing modelling cycles that individually consider participation and uncertainty in SD modelling. Three global modelling phases and a set of tools to address the participation and uncertainty features in SES modelling are distinguished. The framework contributes to mainstreaming GMP, offering a structured model-based approach to enhance the robustness and social acceptance of policies on critical socio-environmental issues.
社会生态系统（SES）中出现的问题具有动态复杂性，对当前和未来的人类福祉和环境可持续性都有影响。这些问题的复杂性、社会生态系统固有的不确定性，以及讨论这些问题的多方利益相关者环境，都需要参与式建模来支持有关社会环境问题的决策。然而，这项具有挑战性的工作需要一个结构化的方法--建模周期--以促进参与和不确定性的影响，并将其作为良好建模实践（GMP）的焦点。在此，我们提出了一个利用系统动力学（SD）进行 SES 建模的综合政策分析框架。该框架整合了现有的两个建模周期，分别考虑了 SD 建模中的参与性和不确定性。它区分了三个全球建模阶段和一套工具，以解决 SES 建模中的参与性和不确定性问题。该框架有助于将全球环境管理计划纳入主流，提供了一种基于模型的结构化方法，以提高有关重大社会环境问题的政策的稳健性和社会接受度。
{"title":"A model-based policy analysis framework for social-ecological systems: Integrating uncertainty and participation in system dynamics modelling","authors":"Henry Amorocho-Daza , Janez Sušnik , Pieter van der Zaag , Jill H. Slinger","doi":"10.1016/j.ecolmodel.2024.110943","DOIUrl":"10.1016/j.ecolmodel.2024.110943","url":null,"abstract":"<div><div>Problems manifested within social-ecological systems (SES) exhibit dynamic complexity and hold implications for current and future human well-being and environmental sustainability. The complexity of these issues, the ever-present uncertainty inherent to SES, and the multi-stakeholder settings in which they are discussed call for participatory modelling to support decision-making on socio-environmental issues. Yet, this challenging endeavour requires a structured approach — a modelling cycle — to facilitate engagement with the implications of participation and uncertainty as focal points for Good Modelling Practice (GMP). Here we propose an integrated policy analysis framework for SES modelling using System Dynamics (SD). This framework stems from integrating two existing modelling cycles that individually consider participation and uncertainty in SD modelling. Three global modelling phases and a set of tools to address the participation and uncertainty features in SES modelling are distinguished. The framework contributes to mainstreaming GMP, offering a structured model-based approach to enhance the robustness and social acceptance of policies on critical socio-environmental issues.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"499 ","pages":"Article 110943"},"PeriodicalIF":2.6,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659298","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}
Pub Date : 2024-11-15DOI: 10.1016/j.ecolmodel.2024.110942
Sara Sharon Jones , Maksym Matsala , Emily Viola Delin , Narayanan Subramanian , Urban Nilsson , Emma Holmström , Igor Drobyshev
Recent increases in fire activity in Sweden call for the quantification of forest fire susceptibility, in order to develop management strategies to mitigate fire risk. Using the data from 100 large Swedish forest fires (>10 ha), mapped from sentinel-2 images from 2016 to 2022, we explored the predictive power of vegetation properties in estimating relative likelihood of fires within a landscape using logistic regression. To model spatially explicit fire susceptibility within a given landscape, we used the outcome of logistic regression as an input into a cellular automata model (CA model), which simulates fire spread in a 2D grid.
The CA was model calibrated on three fires that occurred between 2016 and 2022, then verified on six 2023 fires and featured a mean sensitivity of 0.74 and specificity of 0.79. The logistic regression model had an accuracy of 54 %, showing increased fire susceptibility from high Scots pine volume (p-value = 0.02), and decreased fire susceptibility from high volumes of deciduous trees and wet soil. Realistic outcomes of the CA model and reliance of our approach on publicly available data with nation-wide coverage of vegetation cover in Sweden allows for the development of an automated protocol of fire susceptibility assessment at the operational level and its integration in existing decision support systems. This would allow forest owners to obtain estimates of forest fire susceptibility for different forest management strategies.
{"title":"Forest structure, roads and soil moisture provide realistic predictions of fire spread in modern Swedish landscape","authors":"Sara Sharon Jones , Maksym Matsala , Emily Viola Delin , Narayanan Subramanian , Urban Nilsson , Emma Holmström , Igor Drobyshev","doi":"10.1016/j.ecolmodel.2024.110942","DOIUrl":"10.1016/j.ecolmodel.2024.110942","url":null,"abstract":"<div><div>Recent increases in fire activity in Sweden call for the quantification of forest fire susceptibility, in order to develop management strategies to mitigate fire risk. Using the data from 100 large Swedish forest fires (>10 ha), mapped from sentinel-2 images from 2016 to 2022, we explored the predictive power of vegetation properties in estimating relative likelihood of fires within a landscape using logistic regression. To model spatially explicit fire susceptibility within a given landscape, we used the outcome of logistic regression as an input into a cellular automata model (CA model), which simulates fire spread in a 2D grid.</div><div>The CA was model calibrated on three fires that occurred between 2016 and 2022, then verified on six 2023 fires and featured a mean sensitivity of 0.74 and specificity of 0.79. The logistic regression model had an accuracy of 54 %, showing increased fire susceptibility from high Scots pine volume (<em>p</em>-value = 0.02), and decreased fire susceptibility from high volumes of deciduous trees and wet soil. Realistic outcomes of the CA model and reliance of our approach on publicly available data with nation-wide coverage of vegetation cover in Sweden allows for the development of an automated protocol of fire susceptibility assessment at the operational level and its integration in existing decision support systems. This would allow forest owners to obtain estimates of forest fire susceptibility for different forest management strategies.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"499 ","pages":"Article 110942"},"PeriodicalIF":2.6,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659297","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}
Physiologically-based models are a valuable tool to describe the biology of terrestrial arthropods, as it is the case of insects. These models represent the division of the life cycle in various discrete stages and provide explicit connections with the external environment, making them good candidates for decision support system tools. However, despite the current literature offering good theoretical frameworks, most of them lack of a description of the minimum time required by the organisms to develop to the next life stage. This problem leads to an overestimation of the population and to a compression of the peaks of the generations, hindering their application in real scenarios. In this study we provide a new general model based on Delay Differential Equations (DDE) that overcomes the problem of the minimum development time by introducing time-dependent delays. Those delays generally depend not only on the biology of the species, but on time and on the environmental conditions. This theoretical extension has new implications from the parameter estimation point of view, which are discussed with the support of a case study of agronomic relevance: the brown marmorated stink bug Halyomorpha halys. Besides supporting the description of the model, the case of H. halys was also considered to validate the model using datasets from two geographical locations, for an overall of 5 fields. Simulations showed that the DDE model describes the experimental data better than its previous version based on ordinary differential equations. The model represents an overall step forward in theory development and can be of great support to describe multivoltine species.
以生理为基础的模型是描述陆生节肢动物生物学的重要工具，昆虫也是如此。这些模型将生命周期划分为不同的离散阶段，并提供了与外部环境的明确联系，使其成为决策支持系统工具的良好候选者。然而，尽管目前的文献提供了很好的理论框架，但其中大多数缺乏对生物体发育到下一个生命阶段所需的最短时间的描述。这个问题导致了对种群的高估和对世代峰值的压缩，阻碍了它们在实际场景中的应用。在本研究中，我们提供了一种基于延迟微分方程（DDE）的新通用模型，通过引入随时间变化的延迟来克服最短发育时间的问题。这些延迟一般不仅取决于物种的生物学特性，还取决于时间和环境条件。从参数估计的角度来看，这一理论扩展具有新的意义，我们将通过一个与农艺相关的案例研究：褐狨蝽（Halyomorpha halys）对其进行讨论。除了支持对模型的描述外，还考虑了 H. halys 的情况，利用来自两个地理位置的数据集对 5 块田地的总体情况进行了验证。模拟结果表明，与之前基于常微分方程的模型相比，DDE 模型能更好地描述实验数据。该模型代表了理论发展的整体进步，对描述多伏特物种有很大帮助。
{"title":"A general DDE framework to describe insect populations: Why delays are so important?","authors":"Luca Rossini , Nicolás Bono Rosselló , Ouassim Benhamouche , Mario Contarini , Stefano Speranza , Emanuele Garone","doi":"10.1016/j.ecolmodel.2024.110937","DOIUrl":"10.1016/j.ecolmodel.2024.110937","url":null,"abstract":"<div><div>Physiologically-based models are a valuable tool to describe the biology of terrestrial arthropods, as it is the case of insects. These models represent the division of the life cycle in various discrete stages and provide explicit connections with the external environment, making them good candidates for decision support system tools. However, despite the current literature offering good theoretical frameworks, most of them lack of a description of the minimum time required by the organisms to develop to the next life stage. This problem leads to an overestimation of the population and to a compression of the peaks of the generations, hindering their application in real scenarios. In this study we provide a new general model based on Delay Differential Equations (DDE) that overcomes the problem of the minimum development time by introducing time-dependent delays. Those delays generally depend not only on the biology of the species, but on time and on the environmental conditions. This theoretical extension has new implications from the parameter estimation point of view, which are discussed with the support of a case study of agronomic relevance: the brown marmorated stink bug <em>Halyomorpha halys</em>. Besides supporting the description of the model, the case of <em>H. halys</em> was also considered to validate the model using datasets from two geographical locations, for an overall of 5 fields. Simulations showed that the DDE model describes the experimental data better than its previous version based on ordinary differential equations. The model represents an overall step forward in theory development and can be of great support to describe multivoltine species.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"499 ","pages":"Article 110937"},"PeriodicalIF":2.6,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659537","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}
Pub Date : 2024-11-13DOI: 10.1016/j.ecolmodel.2024.110941
Te. Curk , W. Rast , R. Portas , J. Kohles , G. Shatumbu , C. Cloete , Ti. Curk , V. Radchuk , O. Aschenborn , J. Melzheimer
Utilizing social information during foraging, wherein individuals observe how others interact with their environment rather than relying solely on individually acquired information, is a widely used strategy across the animal kingdom. Nevertheless, our understanding of how different environments shape the extent of social information use remains limited. Here, we assessed the advantages and disadvantages of contrasting foraging strategies in different environments in terms of vulture and carcass density, at the individual, population and ecosystem level. We built an agent-based model to simulate three foraging strategies of African white-backed vultures in Namibia: nonsocial, local enhancement, and chains of vultures. This model incorporated field-derived parameters including vulture and carcass density, and flight characteristics of foraging vultures. From the model outputs, we calculated searching efficiency, competition for resources, and scavenging efficiency and compared the results with observed field data. The results highlight social foraging strategies as overall more advantageous than the nonsocial strategy. The chains of vultures strategy outperformed local enhancement only in terms of searching efficiency under high vulture densities. Furthermore, our findings suggest that vultures in our study area likely adopt diverse foraging strategies influenced by variations in vulture and carcass density. The model developed in this study is potentially applicable beyond the specific study site, rendering it a versatile tool for investigating diverse species and environments. Exploring the role of social foraging holds significant implications for the long-term sustainability of populations and ecosystem processes.
{"title":"Advantages and disadvantages of using social information for carcass detection–A case study using white-backed vultures","authors":"Te. Curk , W. Rast , R. Portas , J. Kohles , G. Shatumbu , C. Cloete , Ti. Curk , V. Radchuk , O. Aschenborn , J. Melzheimer","doi":"10.1016/j.ecolmodel.2024.110941","DOIUrl":"10.1016/j.ecolmodel.2024.110941","url":null,"abstract":"<div><div>Utilizing social information during foraging, wherein individuals observe how others interact with their environment rather than relying solely on individually acquired information, is a widely used strategy across the animal kingdom. Nevertheless, our understanding of how different environments shape the extent of social information use remains limited. Here, we assessed the advantages and disadvantages of contrasting foraging strategies in different environments in terms of vulture and carcass density, at the individual, population and ecosystem level. We built an agent-based model to simulate three foraging strategies of African white-backed vultures in Namibia: nonsocial, local enhancement, and chains of vultures. This model incorporated field-derived parameters including vulture and carcass density, and flight characteristics of foraging vultures. From the model outputs, we calculated searching efficiency, competition for resources, and scavenging efficiency and compared the results with observed field data. The results highlight social foraging strategies as overall more advantageous than the nonsocial strategy. The chains of vultures strategy outperformed local enhancement only in terms of searching efficiency under high vulture densities. Furthermore, our findings suggest that vultures in our study area likely adopt diverse foraging strategies influenced by variations in vulture and carcass density. The model developed in this study is potentially applicable beyond the specific study site, rendering it a versatile tool for investigating diverse species and environments. Exploring the role of social foraging holds significant implications for the long-term sustainability of populations and ecosystem processes.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"499 ","pages":"Article 110941"},"PeriodicalIF":2.6,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659296","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}
Pub Date : 2024-11-13DOI: 10.1016/j.ecolmodel.2024.110920
Jack Boyce , Lucian Elles , Stefanie Henkel , Hans D. Kasperidus , Andreas Padberg , Mathias Scholz , Markus E. Schorn , Andreas Sickert , Michael Vieweg , Nadja Rüger
Like many temperate floodplain forests in Europe, the Leipzig Floodplain Forest (LFF) has been impacted by anthropogenic disturbances, such as historical forestry practices and hydrological alterations. As a result, the forest's tree composition has changed, as evidenced by the declining abundance of typical floodplain species—like pedunculate oak (Quercus robur)—which play an important role in maintaining biodiversity. Notably, oak is not naturally regenerating in the mature forest, situating a need for management intervention to assist oak regeneration. One such management intervention is to plant oak in femels, i.e. small-scale clearings, or canopy gaps. However, it remains unclear whether small femels (<0.5 ha) can ensure effective oak regeneration. Moreover, city foresters aim at reaching 40 % average oak cover in the forest overstory by planting oaks in femels, but uncertainty remains regarding how much of the area would have to be planted with oaks per year to reach this goal.
To explore these questions, we collected forest inventory data from oak femels ranging from 0.1 to 0.6 ha in size and compared oak density, size, growth, and mortality across femel sizes. Furthermore, we used the demographic Perfect Plasticity Approximation (PPA) model to simulate oak overstory cover over time under a femel management regime to assess the percentage of the forest area that should be planted with oaks per year accounting for different groundwater conditions. To parameterise the model, we used forest inventory data to quantify growth rates of oaks in the femels and growth, mortality, and recruitment rates of all common tree species in the Leipzig Floodplain Forest that may regenerate under the oak canopy over time.
Oak density, size, growth, and mortality were similar across femel sizes, indicating that smaller femels are as effective as larger ones in promoting oak regeneration, while minimising the impact on the forest structure. To reach the foresters’ goal of 40 % average oak overstory cover, it is recommended that approximately 0.3 % of the hardwood floodplain forest area is planted with oaks each year, independent of the groundwater conditions. This study illustrates how ecological modeling can assist conservation planning in the context of forest management decision-making and these results may also be relevant for other European floodplain forests where oak regeneration requires support through active management to conserve long-standing biodiversity.
{"title":"How can oak regeneration in the Leipzig Floodplain Forest be effectively supported by femel plantations? Application of a demographic forest model","authors":"Jack Boyce , Lucian Elles , Stefanie Henkel , Hans D. Kasperidus , Andreas Padberg , Mathias Scholz , Markus E. Schorn , Andreas Sickert , Michael Vieweg , Nadja Rüger","doi":"10.1016/j.ecolmodel.2024.110920","DOIUrl":"10.1016/j.ecolmodel.2024.110920","url":null,"abstract":"<div><div>Like many temperate floodplain forests in Europe, the Leipzig Floodplain Forest (LFF) has been impacted by anthropogenic disturbances, such as historical forestry practices and hydrological alterations. As a result, the forest's tree composition has changed, as evidenced by the declining abundance of typical floodplain species—like pedunculate oak <em>(Quercus robur)</em>—which play an important role in maintaining biodiversity. Notably, oak is not naturally regenerating in the mature forest, situating a need for management intervention to assist oak regeneration. One such management intervention is to plant oak in femels, i.e. small-scale clearings, or canopy gaps. However, it remains unclear whether small femels (<0.5 ha) can ensure effective oak regeneration. Moreover, city foresters aim at reaching 40 % average oak cover in the forest overstory by planting oaks in femels, but uncertainty remains regarding how much of the area would have to be planted with oaks per year to reach this goal.</div><div>To explore these questions, we collected forest inventory data from oak femels ranging from 0.1 to 0.6 ha in size and compared oak density, size, growth, and mortality across femel sizes. Furthermore, we used the demographic Perfect Plasticity Approximation (PPA) model to simulate oak overstory cover over time under a femel management regime to assess the percentage of the forest area that should be planted with oaks per year accounting for different groundwater conditions. To parameterise the model, we used forest inventory data to quantify growth rates of oaks in the femels and growth, mortality, and recruitment rates of all common tree species in the Leipzig Floodplain Forest that may regenerate under the oak canopy over time.</div><div>Oak density, size, growth, and mortality were similar across femel sizes, indicating that smaller femels are as effective as larger ones in promoting oak regeneration, while minimising the impact on the forest structure. To reach the foresters’ goal of 40 % average oak overstory cover, it is recommended that approximately 0.3 % of the hardwood floodplain forest area is planted with oaks each year, independent of the groundwater conditions. This study illustrates how ecological modeling can assist conservation planning in the context of forest management decision-making and these results may also be relevant for other European floodplain forests where oak regeneration requires support through active management to conserve long-standing biodiversity.</div></div>","PeriodicalId":51043,"journal":{"name":"Ecological Modelling","volume":"499 ","pages":"Article 110920"},"PeriodicalIF":2.6,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142659300","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}
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