Готові списки джерел за темами / Joint species distribution models

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Добірка наукової літератури з теми "Joint species distribution models"

Автор: Grafiati

Опубліковано: 30 листопада 2024

Оновлено: 26 липня 2025

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Статті в журналах з теми "Joint species distribution models"

Zurell, Damaris, Niklaus E. Zimmermann, Helge Gross, Andri Baltensweiler, Thomas Sattler, and Rafael O. Wüest. "Testing species assemblage predictions from stacked and joint species distribution models." Journal of Biogeography 47, no. 1 (2019): 101–13. http://dx.doi.org/10.1111/jbi.13608.

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Wilkinson, David P., Nick Golding, Gurutzeta Guillera‐Arroita, Reid Tingley, and Michael A. McCarthy. "A comparison of joint species distribution models for presence–absence data." Methods in Ecology and Evolution 10, no. 2 (2018): 198–211. http://dx.doi.org/10.1111/2041-210x.13106.

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Yong, Juan, Guangshuang Duan, Shaozhi Chen, and Xiangdong Lei. "Environmental Response of Tree Species Distribution in Northeast China with the Joint Species Distribution Model." Forests 15, no. 6 (2024): 1026. http://dx.doi.org/10.3390/f15061026.

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The composition, distribution, and growth of native natural forests are important references for the restoration, structural adjustment, and close-to-nature transformation of artificial forests. The joint species distribution model is a powerful tool for analyzing community structure and interspecific relationships. It has been widely used in biogeography, community ecology, and animal ecology, but it has not been extended to natural forest conservation and restoration in China. Therefore, based on the 9th National Forest Inventory data in Jilin Province, combined with environmental factors an

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Ovaskainen, Otso, David B. Roy, Richard Fox, and Barbara J. Anderson. "Uncovering hidden spatial structure in species communities with spatially explicit joint species distribution models." Methods in Ecology and Evolution 7, no. 4 (2015): 428–36. http://dx.doi.org/10.1111/2041-210x.12502.

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D’Acunto, Laura E., Leonard Pearlstine, and Stephanie S. Romañach. "Joint species distribution models of Everglades wading birds to inform restoration planning." PLOS ONE 16, no. 1 (2021): e0245973. http://dx.doi.org/10.1371/journal.pone.0245973.

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Restoration of the Florida Everglades, a substantial wetland ecosystem within the United States, is one of the largest ongoing restoration projects in the world. Decision-makers and managers within the Everglades ecosystem rely on ecological models forecasting indicator wildlife response to changes in the management of water flows within the system. One such indicator of ecosystem health, the presence of wading bird communities on the landscape, is currently assessed using three species distribution models that assume perfect detection and report output on different scales that are challenging

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Hogg, Stephanie Elizabeth, Yan Wang, and Lewi Stone. "Effectiveness of joint species distribution models in the presence of imperfect detection." Methods in Ecology and Evolution 12, no. 8 (2021): 1458–74. http://dx.doi.org/10.1111/2041-210x.13614.

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König, Christian, Rafael O. Wüest, Catherine H. Graham, et al. "Scale dependency of joint species distribution models challenges interpretation of biotic interactions." Journal of Biogeography 48, no. 7 (2021): 1541–51. http://dx.doi.org/10.1111/jbi.14106.

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Gavin, Daniel G., Matthew C. Fitzpatrick, Paul F. Gugger, et al. "Climate refugia: joint inference from fossil records, species distribution models and phylogeography." New Phytologist 204, no. 1 (2014): 37–54. http://dx.doi.org/10.1111/nph.12929.

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Wagner, Tyler, Gretchen J. A. Hansen, Erin M. Schliep, et al. "Improved understanding and prediction of freshwater fish communities through the use of joint species distribution models." Canadian Journal of Fisheries and Aquatic Sciences 77, no. 9 (2020): 1540–51. http://dx.doi.org/10.1139/cjfas-2019-0348.

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Two primary goals in fisheries research are to (i) understand how habitat and environmental conditions influence the distribution of fishes across the landscape and (ii) make predictions about how fish communities will respond to environmental and anthropogenic change. In inland, freshwater ecosystems, quantitative approaches traditionally used to accomplish these goals largely ignore the effects of species interactions (competition, predation, mutualism) on shaping community structure, potentially leading to erroneous conclusions regarding habitat associations and unrealistic predictions abou

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Tikhonov, Gleb, Nerea Abrego, David Dunson, and Otso Ovaskainen. "Using joint species distribution models for evaluating how species‐to‐species associations depend on the environmental context." Methods in Ecology and Evolution 8, no. 4 (2017): 443–52. http://dx.doi.org/10.1111/2041-210x.12723.

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Дисертації з теми "Joint species distribution models"

Valiquette, Samuel. "Sur les données de comptage dans le cadre des valeurs extrêmes et la modélisation multivariée." Electronic Thesis or Diss., Université de Montpellier (2022-....), 2024. http://www.theses.fr/2024UMONS028.

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Cette thèse s’intéresse à certains aspects théoriques de la modélisation des données de comptage. Deux cadres distincts sont abordés : celui des valeurs extrêmes et celui de la modélisation multivariée. Notre première contribution explore, en termes des comportements extrêmes, les liens existants entre le mélange Poisson et sa loi de mélange. Ce travail permet de caractériser et séparer plusieurs familles de lois de mélanges Poisson selon leur comportement en queue. Bien que ce travail soit théorique, nous discutons de son utilité d’un point de vue pratique, notamment pour le choix de la loi d

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Venne, Simon. "Can Species Distribution Models Predict Colonizations and Extinctions?" Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/38465.

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Aim MaxEnt, a very popular species distribution modelling technique, has been used extensively to relate species’ geographic distributions to environmental variables and to predict changes in species’ distributions in response to environmental change. Here, we test its predictive ability through time (rather than through space, as is commonly done) by modeling colonizations and extinctions. Location Continental U.S. and southern Canada. Time period 1979-2009 Major taxa studied Twenty-one species of passerine birds. Methods We used MaxEnt to relate species’ geographic distribu

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Mugodo, James, and n/a. "Plant species rarity and data restriction influence the prediction success of species distribution models." University of Canberra. Resource, Environmental & Heritage Sciences, 2002. http://erl.canberra.edu.au./public/adt-AUC20050530.112801.

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There is a growing need for accurate distribution data for both common and rare plant species for conservation planning and ecological research purposes. A database of more than 500 observations for nine tree species with different ecological and geographical distributions and a range of frequencies of occurrence in south-eastern New South Wales (Australia) was used to compare the predictive performance of logistic regression models, generalised additive models (GAMs) and classification tree models (CTMs) using different data restriction regimes and several model-building strategies. Environme

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Rapacciuolo, Giovanni. "Predicting species' range shifts under global change : when can species distribution models be useful?" Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/18025.

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Predicting how species’ distributions will change in response to environmental changes is fundamental for many aspects of agriculture, ecosystem service provision, human and animal health, and wildlife conservation. Correlative species distribution models (SDMs) are the primary tool for making such predictions; however, assessing their predictive accuracy is notoriously difficult, since predicted events are yet to occur. In this thesis, I tested the temporal transferability of widely-used SDMs based on coarse climate and land cover variables by validating these against records of recently-obse

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Marshall, Charlotte Emily. "Species distribution modelling to support marine conservation planning." Thesis, University of Plymouth, 2012. http://hdl.handle.net/10026.1/1176.

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This thesis explores some important practical considerations concerning the use of species distribution models in marine conservation planning. Using geo-referenced gorgonian distribution data, together with explanatory environmental variables, predictive models have been used to map the spatial distribution of suitable gorgonian (sea fan) habitat in two study sites; Hatton Bank, in the Northeast Atlantic, and Lyme Bay on the south coast of Devon. Generalized Linear Models (GLMs), Generalized Additive Models (GAMs) and a Maximum Entropy (Maxent) model have been used to support critical investi

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ONGARO, SILVIA. "Ecology of Mediterranean lichens and plants: application of species distribution models." Doctoral thesis, Università degli Studi di Trieste, 2019. http://hdl.handle.net/11368/2962383.

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Many studies include Species Distribution Modelling (SDM) techniques to define spatial biogeographic patterns of species and to explore ecological variability. As first, a study on the ecology of infrageneric taxa of genus Solenopsora is presented. The genus includes 25 species of foliose, rupicolous lichens, mostly occurring in temperate and subtropical regions. In Europe, only some taxa range from central Europe (with continental/Atlantic climate) to the Mediterranean, while others are restricted to Mediterranean area. The aim was to explore ecological variability of infrageneric taxa (with

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Wong, Po-shing, and 黃寶誠. "Some mixture models for the joint distribution of stock's return and trading volume." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1991. http://hub.hku.hk/bib/B31210065.

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Wong, Po-shing. "Some mixture models for the joint distribution of stock's return and trading volume /." [Hong Kong] : University of Hong Kong, 1991. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13009485.

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Scott-Hayward, Lindesay Alexandra Sarah. "Novel methods for species distribution mapping including spatial models in complex regions." Thesis, University of St Andrews, 2013. http://hdl.handle.net/10023/4514.

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Species Distribution Modelling (SDM) plays a key role in a number of biological applications: assessment of temporal trends in distribution, environmental impact assessment and spatial conservation planning. From a statistical perspective, this thesis develops two methods for increasing the accuracy and reliability of maps of density surfaces and provides a solution to the problem of how to collate multiple density maps of the same region, obtained from differing sources. From a biological perspective, these statistical methods are used to analyse two marine mammal datasets to produce accurate

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Galaiduk, Ronen. "Spatial ecology and ontogeny: incorporating fish size-classes into species distribution models." Thesis, Curtin University, 2016. http://hdl.handle.net/20.500.11937/51887.

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I use spatial modelling to investigate how relative abundance and body-length can be used to identify niche requirements and habitat partitioning between conspecific fishes. The models identified specific areas associated with juveniles and adults of same or multiple fish species. I investigate the performance of models using data collected from towed and baited video systems. The towed video models detected fine-scale environmental niche associations of fish, which could be missed by commonly used baited systems.

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Книги з теми "Joint species distribution models"

Guidolin, Massimo. An econometric model of nonlinear dynamics in the joint distribution of stock and bond returns. Federal Reserve Bank of St. Louis, 2005.

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Flood, Robert P. A model of the joint distribution of banking and exchange-rate crises. International Monetary Fund, Research Department, 2001.

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Bio, Ana M. F. Does vegetation suit our models?: Data and model assumption and the assessment of species distribution in space. Royal Dutch Geographical Society, 2000.

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Bio, Ana M. F. Does vegetation suit our models?: Data and model assumptions and the assessment of species distribution in space. The Royal Dutch Geographical Society, 2000.

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Peters, Matthew P. Integrating fine-scale soil data into species distribution models: Preparing soil survey geographic (SSURGO) data from multiple counties. U.S. Dept. of Agriculture, Forest Service, Northern Research Station, 2013.

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Borooah, Vani K. Was there a regional dimension to changes in income inequality in the UK over 1982-92?: An analysis based on a joint decomposition of income inequality by region and by employment status. [University of Cambridge, Department of Applied Economics], 1995.

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Bodenheimer, Peter. Numerical studies of collapsing interstellar clouds: NASA/Ames-University of California, Santa Cruz, Joint Research Interchange NAG 2-368 : final technical report, May 1, 1987. National Aeronautics and Space Administration, 1987.

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Kam-Pui, Lee, Gupta Roop N, and Langley Research Center, eds. Computer codes for the evaluation of thermodynamic properties, transport properties, and equilibrium constants of an 11-species air model. National Aeronautics and Space Administration, Langley Research Center, 1990.

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C, Bridger Alison F., Haberle Robert M, and United States. National Aeronautics and Space Administration., eds. Mars Global Surveyor: Aerobraking and observations support using a Mars global circulation model : a NASA Ames Research Center Joint Research Interchange, final report : university consortium agreement NCC2-5148; project duration, 25 July 1995-24 October 1997. National Aeronautics and Space Administration, 1997.

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Частини книг з теми "Joint species distribution models"

Ovaskainen, Otso. "Species distribution models." In Handbook of Environmental and Ecological Statistics. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9781315152509-12.

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Miller, Jennifer A., and Janet Franklin. "Incorporating Spatial Autocorrelation in Species Distribution Models." In Handbook of Applied Spatial Analysis. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03647-7_32.

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Wu, Ximing, Andreas Savvides, and Thanasis Stengos. "The Global Joint Distribution of Income and Health." In Recent Advances in Estimating Nonlinear Models. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8060-0_12.

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Lawler, Josh J., Yolanda F. Wiersma, and Falk Huettmann. "Using Species Distribution Models for Conservation Planning and Ecological Forecasting." In Predictive Species and Habitat Modeling in Landscape Ecology. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7390-0_14.

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Borba, Cleverton, and Pedro Luiz Pizzigatti Correa. "Application of Metadata Standards for Interoperability Between Species Distribution Models." In Communications in Computer and Information Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-24129-6_10.

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Deneu, Benjamin, Maximilien Servajean, Christophe Botella, and Alexis Joly. "Evaluation of Deep Species Distribution Models Using Environment and Co-occurrences." In Lecture Notes in Computer Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28577-7_18.

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Eckstein, Felix, Beat Merz, and Christopher R. Jacobs. "Basis for the Design of the Computer Models." In Effects of Joint Incongruity on Articular Pressure Distribution and Subchondral Bone Remodeling. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57184-8_2.

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Warren, Dan L., Lukas Baumbach, Jamie M. Kass, and Alke Voskamp. "Uncertainty in Ecological Models." In Uncertainty in Climate Change Research. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-85542-9_8.

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Abstract Estimating long-term trends in ecological communities requires that we have some model of how organisms relate to changes in environmental factors such as temperature, precipitation, and land use. Experimental approaches to develop these estimates are often cost-prohibitive or are logistically impractical. As a result, a large and active literature has arisen that attempts to model the suitability of habitat for species and communities based on statistical analysis of current patterns of their occurrence and co-occurrence at large geographic scales. Despite being instrumental to many

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Hudson, Irene L., Susan W. Kim, and Marie R. Keatley. "Modelling the Flowering of Four Eucalypt Species Using New Mixture Transition Distribution Models." In Phenological Research. Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-3335-2_14.

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Pinto-Ledezma, Jesús N., and Jeannine Cavender-Bares. "Using Remote Sensing for Modeling and Monitoring Species Distributions." In Remote Sensing of Plant Biodiversity. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-33157-3_9.

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AbstractInterpolated climate surfaces have been widely used to predict species distributions and develop environmental niche models. However, the spatial coverage and density of meteorological sites used to develop these surfaces vary among countries and regions, such that the most biodiverse regions often have the most sparsely sampled climatic data. We explore the potential of satellite remote sensing (S-RS) products—which have consistently high spatial and temporal resolution and nearly global coverage—to quantify species-environment relationships that predict species distributions. We prop

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Тези доповідей конференцій з теми "Joint species distribution models"

Ortiz, A., A. Ruiz-García, J. Genescá, and R. Montoya. "Acidification of the Electrolyte in the Carbon Steel/ Aluminum Alloys Galvanic Couple: Modeling and Experimental Study." In CORROSION 2021. AMPP, 2021. https://doi.org/10.5006/c2021-16334.

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Abstract An electrochemical model was developed to predict the transient distribution of species generated during corrosion of carbon steel (CS) /aluminum alloy (AA) galvanic couples under thin NaCl electrolyte films at room temperature (24 °C). Using specific geometrical configurations, strong acidification of the electrolyte, localized above the AA surface and close to the carbon steel electrode, was predicted. However, a small zone evolved (also above the AA surface) between the strong acidified area and the AA/CS joint, where the pH was neutral due to the OH- production on the CS surface.

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Proksch-Weilguni, Clemens, Marion Decker, and Johann Kollegger. "Validation of a novel mechanical model for geometrically and passively confined concrete." In IABSE Congress, San José 2024: Beyond Structural Engineering in a Changing World. International Association for Bridge and Structural Engineering (IABSE), 2024. https://doi.org/10.2749/sanjose.2024.0565.

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<p>Investigating the load-bearing characteristics of the joint region of precast concrete elements under compression is crucial for practical applications, such as in tunnel linings. The study introduces a novel mechanical model to predict the load-bearing capacity of load transfer zones with both geometric confinement caused by load distribution and passive confinement caused by transverse reinforcement. Two design approaches according to the current draft of the Eurocode 2 (EC2) and the novel mechanical model are used for a comparative validation based on experimental tests done at TU

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Amora, Epifelward Niño O. "Comparative Analysis of Machine Learning Models for Predicting Species Distribution in Fishing Data." In 2025 International Conference on Electronics and Renewable Systems (ICEARS). IEEE, 2025. https://doi.org/10.1109/icears64219.2025.10940562.

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Chen, Di, Yexiang Xue, Daniel Fink, Shuo Chen, and Carla P. Gomes. "Deep Multi-species Embedding." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/509.

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Understanding how species are distributed across landscapes over time is a fundamental question in biodiversity research. Unfortunately, most species distribution models only target a single species at a time, despite strong ecological evidence that species are not independently distributed. We propose Deep Multi-Species Embedding (DMSE), which jointly embeds vectors corresponding to multiple species as well as vectors representing environmental covariates into a common high-dimensional feature space via a deep neural network. Applied to bird observational data from the citizen science project

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Kong, Shufeng, Junwen Bai, Jae Hee Lee, et al. "Deep Hurdle Networks for Zero-Inflated Multi-Target Regression: Application to Multiple Species Abundance Estimation." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/603.

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A key problem in computational sustainability is to understand the distribution of species across landscapes over time. This question gives rise to challenging large-scale prediction problems since (i) hundreds of species have to be simultaneously modeled and (ii) the survey data are usually inflated with zeros due to the absence of species for a large number of sites. The problem of tackling both issues simultaneously, which we refer to as the zero-inflated multi-target regression problem, has not been addressed by previous methods in statistics and machine learning. In this paper, we propose

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Engdar, Ulf, Per Nilsson, and Jens Klingmann. "Investigation of Turbulence Models Applied to Premixed Combustion Using a Level-Set Flamelet Library Approach." In ASME Turbo Expo 2003, collocated with the 2003 International Joint Power Generation Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/gt2003-38331.

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Most of the common modeling approaches to premixed combustion in engineering applications are either based on the assumption of infinitely fast chemistry or the flamelet assumption with simple chemistry. The level-set flamelet library approach (FLA) has shown great potential in predicting major species and heat release, as well as intermediate and minor species, where more simple models often fail. In this approach, the mean flame surface is tracked by a level-set equation. The flamelet libraries are generated by an external code, which employs a detailed chemical mechanism. However, a model f

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Abyaneh, M. H. J., та M. H. Saidi. "Velocity Distributions in (r,θ) Directions for Laminar Flow of a Film Around Horizontal Circular Tube". У ASME 2006 2nd Joint U.S.-European Fluids Engineering Summer Meeting Collocated With the 14th International Conference on Nuclear Engineering. ASMEDC, 2006. http://dx.doi.org/10.1115/fedsm2006-98087.

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Velocity distributions in (r,θ) directions are evaluated by solving simultaneous simplified Navier-Stokes equations (NSE) and continuity equation (CE) in polar coordinate. The analysis is based on steady state laminar flow of thin falling liquid film on a horizontal circular tube, for cases in which traction on the film surface is considered negligible. It is a common geometry for part of engineering problems such as evaporator, condenser, absorber, generator of absorption chillers and other similar units in mechanical and chemical engineering. Knowledge of the velocity profiles is usually nee

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Chen, Lu, and Francine Battaglia. "Computational Study Comparing Reduced Chemical Mechanisms With the PDF Method in Non-Premixed Flames." In ASME 2016 Fluids Engineering Division Summer Meeting collocated with the ASME 2016 Heat Transfer Summer Conference and the ASME 2016 14th International Conference on Nanochannels, Microchannels, and Minichannels. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/fedsm2016-7543.

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Reactive flow simulations involving turbulence-chemistry interactions can be very challenging because of the strong non-linear coupling between chemistry and fluid dynamics. Furthermore, the chemistry is described with hundreds of reactions, which is prohibitive to solve using computational fluid dynamics (CFD). Using a reduced set of mechanisms that contains a subset of the important species is more practical. However, the species modeled must capture the key combustion characteristics of interest, such as ignition, species distributions and major pollutant formation. Previously, the authors

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Arai, Norio, Takahisa Yamamoto, and Tomohiko Furuhata. "Numerical Simulation of Low Heating Value Fuel Turbulent Diffusion Combustion." In 2002 International Joint Power Generation Conference. ASMEDC, 2002. http://dx.doi.org/10.1115/ijpgc2002-26113.

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In this study, in order to obtain fundamental data for designing the practical gas turbine combustors in the chemical gas turbine (Ch/GT) combined cycle system and/or other gas turbine systems which utilize low heating value fuel such as coal and biomass gasification syngas, we have simulated low heating value fuel–air turbulent diffusion combustion. The simulated results for the profiles of temperature and species concentrations have been compared with the measured ones. As a reaction model, the flamelet model has been applied to predict the turbulent diffusion combustion characteristics. A f

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Igi, Satoshi, Takahiro Kubo, and Masayoshi Kurihara. "Ductile Fracture Evaluation of Welded Joints With a Surface Flaw Under Large Deformation." In ASME 2005 Pressure Vessels and Piping Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/pvp2005-71521.

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Tensile tests using welded joint specimens with a surface flaw were conducted in order to study the large deformation behavior and ductile fracture of welded structural component with a flaw. Two types of 490MPa class steel plates with different yield strength are prepared for this study. The surface flaw was introduced at the center of welded metal of welded joint specimen. Strain distribution during loading and the maximum strain at ductile fracture of specimen were measured in order to investigate the influence of stress-strain properties on ductile fracture behavior of the welded joint. Th

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Звіти організацій з теми "Joint species distribution models"

Aiello-Lammens, Matthew E., Robert Anderson, Mary E. Blair, et al. Species Distribution Modeling for Conservation Educators and Practitioners. American Museum of Natural History, 2023. http://dx.doi.org/10.5531/cbc.ncep.0184.

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Models that predict distributions of species by combining known occurrence records with digital layers of environmental variables have much potential for application in conservation. Through using this module, teachers will enable students to develop species distribution models, to apply the models across a series of analyses, and to interpret predictions accurately. In addition to its original components, this module features an updated and condensed synthesis document ("A Brief Introduction to Species Distribution Modeling for Conservation Educators and Practitioners," which provides theoret

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Kenchington, E., L. Beazley, C. Lirette, F. J. Murillo, and J. Guijarro. Delineation of significant benthic areas in eastern Canada using kernel density analysis and species distribution models. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2017. http://dx.doi.org/10.4095/305872.

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Riordan, Erin C., Arlee M. Montalvo, and Jan L. Beyers. Using species distribution models with climate change scenarios to aid ecological restoration decisionmaking for southern California shrublands. U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station, 2018. http://dx.doi.org/10.2737/psw-rp-270.

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Peters, Matthew P., Louis R. Iverson, Anantha M. Prasad, and Steve N. Matthews. Integrating fine-scale soil data into species distribution models: preparing Soil Survey Geographic (SSURGO) data from multiple counties. U.S. Department of Agriculture, Forest Service, Northern Research Station, 2013. http://dx.doi.org/10.2737/nrs-gtr-122.

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Weldon, James, and Carlotta Meriggi. Modelling the risks of invasive aquatic species spread in Swedish lakes. Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, 2023. http://dx.doi.org/10.54612/a.r68r25qcb1.

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Species distribution modelling is a valuable tool for identifying areas most at risk of the spread of invasive species. Here we model the environmental factors governing the distributions of two invasive species of concern that are currently found in Sweden at only a limited number of locations: the aquatic macrophyte Elodea nuttallii (Nuttall’s waterweed / smal vattenpest) and the bivalve Dreissena polymorpha (Zebra mussel / vandrarmussla). For E.nuttallii, the greatest risk factors are connectivity with other water bodies (facilitating dispersion), human population density and length of grow

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Guilfoyle, Michael, Ruth Beck, Bill Williams, et al. Birds of the Craney Island Dredged Material Management Area, Portsmouth, Virginia, 2008-2020. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45604.

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This report presents the results of a long-term trend analyses of seasonal bird community data from a monitoring effort conducted on the Craney Island Dredged Material Management Area (CIDMMA) from 2008 to 2020, Portsmouth, VA. The USACE Richmond District collaborated with the College of William and Mary and the Coastal Virginia Wildlife Observatory, Waterbird Team, to conduct year-round semimonthly area counts of the CIDMMA to examine species presence and population changes overtime. This effort provides information on the importance of the area to numerous bird species and bird species’ grou

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Méndez-Vizcaíno, Juan C., Alexander Guarín, César Anzola-Bravo, and Anderson Grajales-Olarte. Characterizing and Communicating the Balance of Risks of Macroeconomic Forecasts: A Predictive Density Approach for Colombia. Banco de la República, 2021. http://dx.doi.org/10.32468/be.1178.

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Since July 2021, Banco de la República strengthened its forecasting process and communication instruments, by involving predictive densities on the projections of its models, PATACON and 4GM. This paper presents the main theoretical and empirical elements of the predictive density approach for macroeconomic forecasting. This model-based methodology allows to characterize the balance of risks of the economy, and quantify their effects through a joint probability distribution of forecasts. We estimate this distribution based on the simulation of DSGE models, preserving the general equilibrium re

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Brandt, Leslie A., Cait Rottler, Wendy S. Gordon, et al. Vulnerability of Austin’s urban forest and natural areas: A report from the Urban Forestry Climate Change Response Framework. U.S. Department of Agriculture, Northern Forests Climate Hub, 2020. http://dx.doi.org/10.32747/2020.7204069.ch.

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The trees, developed green spaces, and natural areas within the City of Austin’s 400,882 acres will face direct and indirect impacts from a changing climate over the 21st century. This assessment evaluates the vulnerability of urban trees and natural and developed landscapes within the City Austin to a range of future climates. We synthesized and summarized information on the contemporary landscape, provided information on past climate trends, and illustrated a range of projected future climates. We used this information to inform models of habitat suitability for trees native to the area. Pro

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Waigner, Lisa, Solange Filoso, Kim Gazenski, Elizabeth Murray, Charles Theiling, and Shawn Komlos. Applying the ecosystem goods and services (EGS) framework : Meramec case study. Engineer Research and Development Center (U.S.), 2025. https://doi.org/10.21079/11681/49520.

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This technical report explores ecosystem goods and services (EGS) assessment to support US Army Corps of Engineers (USACE) decision-making by applying the recently published proposed EGS framework (Wainger et al. 2020) to a case study. A joint effort of the Environmental Protection Agency (EPA) and USACE, the Meramec River Basin Ecosystem Restoration Feasibility Study provides an opportunity to investigate the practicality of EGS analysis and how it might determine complementarity or antagonism among study partner goals. The EPA seeks primarily to protect hu-man health, while USACE aims to res

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