2024 ARCHIVES|Special Symposia
The following organized symposia was included in the program at the 2024 IALE-North American Annual Meeting.
An Organized Symposium is a series of integrated presentations that address aspects of a single topic or theme. Symposia are the scientific centerpiece of the meeting and will run concurrently with other technical sessions.
An Organized Symposium is a series of integrated presentations that address aspects of a single topic or theme. Symposia are the scientific centerpiece of the meeting and will run concurrently with other technical sessions.
S-01. Landscape Sustainability Science: Linking Landscape Pattern, Ecosystem Services, and Human Well-being
Contact: Xin Wang, PhD student, Arizona State University, [email protected]
Co-Organizers: Josh Gilman, School of Life Sciences, Arizona State University; Chenwei Shang, School of Ecology and the Environment, Inner Mongolia University, China; Jianguo (Jingle) Wu, School of Life Sciences and School of Sustainability, Arizona State University
Overview:
Sustainability has become an increasingly compelling topic in the Anthropocene. Landscape, as a basic spatial unit of human-nature interactions, is considered as the most pivotal scale domain to address sustainability problems. The science of landscape sustainability – the capacity of a landscape to consistently provide long-term, landscape-specific ecosystem services essential for maintaining and improving human wellbeing – has emerged and been developing rapidly. Aiming to understand the relationships between landscape pattern, ecosystem services and human wellbeing, landscape sustainability science borrows the knowledge and approaches from, and provides the ultimate goal for, landscape ecology. However, the topic of sustainability has not received sufficient attention at the recent meetings of IALE-NA. In the 2023 Annual Meeting, for example, only 2 oral presentations and 1 poster presentation mentioned sustainability or sustainable development in their titles. The goal of this symposium is to promote the theoretical development and practical applications of landscape sustainability science, with a focus on the pattern-service-wellbeing relationship nexus. We will invite scientists to present their insights on landscape sustainability science from theoretical work or empirical case studies of various landscapes around the world.
S-02. Remote Sensing of Landscape Change and Disturbance
Contact: Jitendra Kumar, R&D Staff, Oak Ridge National Laboratory, [email protected]
Co-Organizers: Jitendra Kumar, Oak Ridge National Laboratory; Steven P. Norman, USDA Forest Service Southern Research Station; William W. Hargrove, USDA Forest Service Southern Research Station; Forrest M. Hoffman, Oak Ridge National Laboratory; Shashank Konduri, National Ecological Observation Network; Alyson East, ORISE Fellow, USDA Forest Service Southern Research Station
Overview:
Remote sensing has been a foundational tool for landscape ecology for decades, and it has been critical for tracking disturbance and change over time. From providing national products and datasets, to monitoring landscape dynamics in near-real-time, to the integration with other datasets, remote sensing has carved out a pivotal role. Development of new platforms and sensors having increasing spatial, temporal and spectral resolution and new sensor modalities offers unprecedented opportunities to better understand the locations, severity and rates of disturbance and change that are increasingly reshaping landscapes in both predictable and novel ways. Emerging machine learning and big data analytics algorithms, computational methods and improved access to high performance and cloud computing resources have enabled novel use and application of voluminous remote sensing datasets. Technical and methodological advances have led to a substantial increase in data availability, to the extent that the sheer abundance of data products can create a challenge. While routine adoption of tools, approaches and technologies continues to lag cutting edge research, this application divide itself presents opportunities for further research and collaboration. This open IALE-NA symposium invites all practitioners to share their approaches and experiences using remote sensing methods to understand, detect, describe and monitor landscape change and disturbances through time.
S-03. 3D Spatial Data Science for Landscape Ecology
Contact: Mark Lindquist, Associate Professor, University of Michigan, [email protected]
Co-Organizers: Dr. Ramiro Serrano Vergel, University of Michigan
Overview:
This symposium extends the overarching theme of the conference ""Data Science in Landscape Ecology,"" to explore the transformative potential of leveraging 3D spatial data across all scales of inquiry. With the rapid advancements in 3D data collection technology at ever finer scales the increasing influx of 3D data is reshaping opportunities for landscape ecology. In addition, 3D spatial data and data collection tools are becoming increasingly accessible and democratized leading to a new paradigm emerging. This paradigm can empower numerous stakeholders by providing access to, analysis, and visualization of 3D spatial data at an unimaginable speed and scale until now. This advancement provides new opportunities to understand the ecological and sociocultural functions of landscapes, as well as their complex interactions.
Central to this symposium is the aim to unite a diverse group of academics, practitioners, and interested stakeholders specializing or interested in landscape visualization, spatial analysis, and planning & design, all leveraging 3D spatial data. Participants can anticipate being immersed in the vast realm of 3D spatial data, including novel collection, analysis, and visualization tools and methodologies. Sessions will spotlight the integration of pioneering hardware and software for spatial data collection, analysis, and visualization, shedding light on the pragmatic applications of tools such as ArcGIS and Cesium. Discussions will discuss the intricacies of capturing localized spatial data using LiDAR, underscoring its pivotal role in ecological design. The session will also explore the visualization of spatial data, particularly in the context of altering and comprehending multifunctional landscapes, as well as the potential of new tools e.g. viewshed analysis in assessing landscapes. This symposium endeavors to nurture a comprehensive understanding of the environment through 3D geovisualization, analysis, and innovative workflows. It marks a pivotal step towards a more holistic view of multifunctional landscapes.
S-04. Phenometrics in Wild & Managed Ecosystems: Theory, Method, Application
Contact: Geoff Henebry, Professor, Michigan State University, [email protected]
Co-Organizers: Bill Hargrove, USFS, Southern Research Station
Overview:
Phenologies are key recurring subplots within the evolutionary play unfolding amidst diverse landscapes in myriad ecological theatres. Phenological data come in various forms: historical observations, curated citizen science observations, protocol-driven technical observations, and instrumental records from phenocams, audio recordings, flux towers, and constellations of spaceborne sensors. In a world recently awash in remote sensing data at various spatial, temporal, and spectral resolutions in key parts of the electromagnetic spectrum, questions abound about optimal methods for determining and using metrics to characterizing and model land surface phenologies. Moreover, there is ever a pressing need to compare species-specific ground-level observations with instrumental records that may not resolve specific organisms. In this open symposium, we will explore the cutting-edge approaches to phenometric definition, detection, and integration with ancillary data and disciplinary perspectives. We welcome contributions from students, early career scientists, and established scholars to complement our handful of invited presentations. It is sure to be an interesting and engaging symposium!
S-05. Geospatial AI and Informatics for Urban & Ecosystems Analytics
Contact: Henry Bulley, Associate Professor, BMCC, The City University of New York, [email protected]
Co-Organizers: Monika Kuffer - University of Twente (ITC), The Netherlands; Samuel Adu-Prah - Sam Houston State University, Texas, USA; Shalini Dhyani - CSIR-National Environment Engineering Research Institute, India; Ellen Banzhaf - Helmholtz Centre for Environmental Research – UFZ, Germany; Moses Azong Cho - CSIR/University of Pretoria, South Africa; WenWen Li - Arizona State University, USA; Piotr Jankowski - San Diego State University, USA; Naa Dedei Tagoe - University of Mines and Technology, Ghana
Overview:
This session aims at advancing our understanding of and improving the Synergy between GeoAI and Urban Ecosystem Analytics, to support effective decision-making for disaster risk reduction for sustainable cities. Recent advances in the availability of Big Data, including in the use of Earth Observation (EO), together with advances in Geospatial Artificial Intelligence (GeoAI) promise to rapidly transform how we assess urban resilience and ecosystem services to enhance livelihood (SGD 11) in both High Income and Low/Middle-Income Countries. Geospatial Artificial Intelligence (GeoAI) combines geospatial science and artificial intelligence techniques to derive insights from complex ‘Big’ data to extract a rich tapestry of information from data (e.g., via deep learning algorithms) and perform predictive analysis (e.g., via machine learning algorithms). This is useful in automating the process of deriving timely information from Big Data, to help make predictions that have the potential to facilitate decision-making to improve the resilience of urban areas.
With more than 70 percent of human populations projected to live in Urban Areas by 2050, human–environmental systems will become more dependent on ecosystems for their resilience to climate change impacts and to ensure the sustainability of cities. Using GeoAI to assess land change dynamics and the role of ecosystem services, such as green infrastructure, in improving the livelihood of urban residents also relies heavily on the availability of accurate geospatial data which often comes from disparate multisensor and multiscale Earth Observation sensors.
Landscape ecology principles such as scale and heterogeneity are vital for effective analyses and modelling of land use dynamics, and how these affect the provisioning of ecosystem services. Our proposed symposium will bring together contributions from different parts of the world that address recent developments and challenges in the integration of GeoAI and Urban Ecosystem Analytics to extract vital information from increasing amounts of Earth Observation and other Big Data repositories.
We invite contributions that address core issues on GeoAI applications (GeoAI Moonshot), Big Data `scale and landscape structure on the ecosystems services provisioning, etc. We also encourage presentations that address climate change impacts and ecosystem resilience challenges of cities in developed countries and the Global South, especially in informal settlements in developing countries. Authors would be invited to submit manuscripts of their presentations for a special issue on Geospatial AI and Informatics for Urban & Ecosystems Analytics in the journal Applied Sciences.
S-06. Advancing Inclusive Data Science in Landscape Ecology
Contact: Kusum Naithani, Associate Professor, University of Arkansas, [email protected]
Co-Organizers: Falk Huettmann, University of Alaska-Fairbanks, AK, USA
Overview:
Landscape ecology, a multidisciplinary field, plays a critical role in addressing environmental challenges. While the open data and open science movement has made significant strides, it often overlooks the rights of Indigenous Peoples. Existing open data principles like FAIR (findable, accessible, interoperable, reusable) and others prioritize data sharing but fail to consider power imbalances and historical contexts. This poses a dilemma for Indigenous Peoples and others, who seek control over data and knowledge for their well-being. The CARE Principles for Indigenous Data Governance, rooted in people and purpose, can complement FAIR principles by emphasizing the human element and purpose in data advocacy. To promote ethical, accessible, and responsible data science in landscape ecology research and education, this symposium will facilitate knowledge exchange and best practices for data sharing and reuse.
This symposium serves as a vital platform for meaningful dialogue, forging connections, and promoting inclusivity and ethics in the landscape ecology community. Together, we aim to enhance our understanding of the environment while respecting the rights and perspectives of all participating communities.
(CANCELLED) S-07. Landscape Conservation Design: Where Data Science and Conservation Practitioners Come Together
Contact: Sean Finn, Science Coordinator, U.S. Fish & Wildlife Service, [email protected]
Co-Organizers: Amy Katz, Heart of the Rockies Initiative
S-08. Landscapes of Infection: Effects of Climate and Land Cover Change on Disease Transmission
Contact: Michael Wimberly, Professor, University of Oklahoma, [email protected]
Co-Organizers: Courtney Murdock, Cornell University
Overview:
Landscape ecology explores the effects of spatial patterns on ecological processes, placing a particular emphasis on linkages across multiple spatial scales. These themes are essential for understanding the biological, environmental, and anthropogenic factors that influence the transmission of vector-borne and zoonotic diseases as well as the consequent risks of human exposure. For this reason, the concepts and methods of landscape ecology are now widely applied to study the interactions of vectors, hosts, and pathogens in heterogeneous habitat mosaics. There is increasing recognition that the transmission cycles of many pathogens are sensitive to climate change, and that these responses will be locally mediated by patterns of land use and land cover. Landscape change, including urban growth and the expansion of agriculture and human settlement into natural habitats, can also facilitate the spread of existing disease as well as the emergence of new pathogens. To address these critical and timely topics, our proposed symposium will assemble a diverse group of speakers who are conducting research on disease ecology at landscape scales. The talks will address a broad range of diseases, including vector-borne diseases transmitted by mosquitoes and ticks as well as zoonotic diseases with birds, bats, rodents, and livestock as hosts. Specific topics of interest include methods for studying the landscape ecology of infectious diseases, the sensitivity of disease transmission cycles to the spatial patterns of landscape mosaics, the relevance of landscape ecology for understanding and forecasting climate-sensitive diseases, the effects of land cover and land use change on vectors, hosts, and pathogens, and the application of research results to support disease prevention, control, and elimination efforts.
S-09. Model Interactions Between Green Initiatives, People, and the Environment Using a Data Science Approach
Contact: Li An, Solon & Martha Dixon Endowed Professor, Auburn University, [email protected]
Co-Organizers: Conghe Song, professor, Department of Geography, University of North Carolina Chapel Hill, [email protected]; Qi Zhang, Research Assistant Professor, Department of Geography, University of North Carolina Chapel Hill, [email protected]; Rong Zhang, Research Scientist, College of Forestry, Wildlife, and Environment, Auburn University, [email protected]
Overview:
Humanity stands in an unprecedented era of climate change, environmental degradation, and rapid biodiversity loss. These interconnected crises threaten the very survival of humanity. Therefore, green initiatives—defined to be conservation programs, funds, payments, policies, or any endeavors—have been launched worldwide to restore, sustain, or improve nature’s capacity to benefit human beings. Despite reported successes in restoring and preserving the Nature—including ecosystems and their corresponding services such as clean air and water, food, and soil fertility—green initiatives are subject to many challenges, such as lack of sustainability over time, unclear mechanisms, and negative externalities in escalated consequences in the corresponding human-environment systems.
This symposium convenes a diverse group of researchers to delve into these challenges in complex human-environment systems using a data science approach. Employing data from three key sites in Nepal (i.e., Salyan, Pyuthan, and Chitwan), we address theoretical, methodological, and empirical issues related to green initiatives as follow:
1.Ecological effects of green initiatives;
2.Socioeconomic, demographic, and political consequences of green initiatives;
3.Potential mechanisms for success/failure observed in green initiatives;
4.Interactions between green initiatives that are implemented in the same area or contacted to same recipients;
5.Complexities in complex human-environment systems arising from green initiatives (e.g., feedback, nonlinearity, time lags).
6.Data science issues: data collection, analysis, and modeling, integration of multidisciplinary and multi-scale data, validation and appraisal, etc.
This symposium will substantially improve our understanding of multiple green initiatives in terms of driving force, social impacts, and ecological consequences, contributing to the effectiveness and sustainability of many green initiatives worldwide. On a methodological standpoint, this symposium will compare and evaluate the pros and cons of several traditional and non-traditional data science methods. Furthermore, we will consider a proposal for editing a book on the same topic and welcome potential collaborators.
S-10. Leveraging AI Advances in Landscape Ecology
Contact: Nathan Fox, Postdoctoral Fellow, University of Michigan, [email protected]
Co-Organizers: Prof. Derek Van Berkel, University of Michigan
Overview:
In the rapidly evolving world of technology, Artificial Intelligence (AI) emerges as a groundbreaking tool with the potential to revolutionize the realm of landscape ecology. This confluence of technology and nature promises not only enhanced analytical capabilities but also the unveiling of patterns and insights previously hidden in vast and complex ecological datasets.
Landscape ecology, inherently multidisciplinary, delves into the spatial patterns of landscapes and the processes that produce them. With the integration of AI, we can now automate the analysis of large-scale satellite imagery to monitor deforestation, predict the spread of invasive species, or even model the impacts of climate change on habitat fragmentation. Furthermore, AI paves the way for harnessing big data from novel sources, especially in the rapidly growing realm of online citizen science, where enthusiasts and professionals alike contribute to a collective pool of ecological information.
The symposium aims to serve as a nexus for innovators, researchers, and practitioners. We endeavor to showcase cutting-edge AI applications in landscape ecology, offering attendees a comprehensive view of current advancements. More importantly, this gathering seeks to foster an environment of collaboration, sparking new ideas and forging interdisciplinary partnerships. By bridging the gap between AI specialists and landscape ecologists, we hope to catalyze a wave of innovation, driving both fields into uncharted territories and achieving unprecedented breakthroughs.
Contact: Xin Wang, PhD student, Arizona State University, [email protected]
Co-Organizers: Josh Gilman, School of Life Sciences, Arizona State University; Chenwei Shang, School of Ecology and the Environment, Inner Mongolia University, China; Jianguo (Jingle) Wu, School of Life Sciences and School of Sustainability, Arizona State University
Overview:
Sustainability has become an increasingly compelling topic in the Anthropocene. Landscape, as a basic spatial unit of human-nature interactions, is considered as the most pivotal scale domain to address sustainability problems. The science of landscape sustainability – the capacity of a landscape to consistently provide long-term, landscape-specific ecosystem services essential for maintaining and improving human wellbeing – has emerged and been developing rapidly. Aiming to understand the relationships between landscape pattern, ecosystem services and human wellbeing, landscape sustainability science borrows the knowledge and approaches from, and provides the ultimate goal for, landscape ecology. However, the topic of sustainability has not received sufficient attention at the recent meetings of IALE-NA. In the 2023 Annual Meeting, for example, only 2 oral presentations and 1 poster presentation mentioned sustainability or sustainable development in their titles. The goal of this symposium is to promote the theoretical development and practical applications of landscape sustainability science, with a focus on the pattern-service-wellbeing relationship nexus. We will invite scientists to present their insights on landscape sustainability science from theoretical work or empirical case studies of various landscapes around the world.
S-02. Remote Sensing of Landscape Change and Disturbance
Contact: Jitendra Kumar, R&D Staff, Oak Ridge National Laboratory, [email protected]
Co-Organizers: Jitendra Kumar, Oak Ridge National Laboratory; Steven P. Norman, USDA Forest Service Southern Research Station; William W. Hargrove, USDA Forest Service Southern Research Station; Forrest M. Hoffman, Oak Ridge National Laboratory; Shashank Konduri, National Ecological Observation Network; Alyson East, ORISE Fellow, USDA Forest Service Southern Research Station
Overview:
Remote sensing has been a foundational tool for landscape ecology for decades, and it has been critical for tracking disturbance and change over time. From providing national products and datasets, to monitoring landscape dynamics in near-real-time, to the integration with other datasets, remote sensing has carved out a pivotal role. Development of new platforms and sensors having increasing spatial, temporal and spectral resolution and new sensor modalities offers unprecedented opportunities to better understand the locations, severity and rates of disturbance and change that are increasingly reshaping landscapes in both predictable and novel ways. Emerging machine learning and big data analytics algorithms, computational methods and improved access to high performance and cloud computing resources have enabled novel use and application of voluminous remote sensing datasets. Technical and methodological advances have led to a substantial increase in data availability, to the extent that the sheer abundance of data products can create a challenge. While routine adoption of tools, approaches and technologies continues to lag cutting edge research, this application divide itself presents opportunities for further research and collaboration. This open IALE-NA symposium invites all practitioners to share their approaches and experiences using remote sensing methods to understand, detect, describe and monitor landscape change and disturbances through time.
S-03. 3D Spatial Data Science for Landscape Ecology
Contact: Mark Lindquist, Associate Professor, University of Michigan, [email protected]
Co-Organizers: Dr. Ramiro Serrano Vergel, University of Michigan
Overview:
This symposium extends the overarching theme of the conference ""Data Science in Landscape Ecology,"" to explore the transformative potential of leveraging 3D spatial data across all scales of inquiry. With the rapid advancements in 3D data collection technology at ever finer scales the increasing influx of 3D data is reshaping opportunities for landscape ecology. In addition, 3D spatial data and data collection tools are becoming increasingly accessible and democratized leading to a new paradigm emerging. This paradigm can empower numerous stakeholders by providing access to, analysis, and visualization of 3D spatial data at an unimaginable speed and scale until now. This advancement provides new opportunities to understand the ecological and sociocultural functions of landscapes, as well as their complex interactions.
Central to this symposium is the aim to unite a diverse group of academics, practitioners, and interested stakeholders specializing or interested in landscape visualization, spatial analysis, and planning & design, all leveraging 3D spatial data. Participants can anticipate being immersed in the vast realm of 3D spatial data, including novel collection, analysis, and visualization tools and methodologies. Sessions will spotlight the integration of pioneering hardware and software for spatial data collection, analysis, and visualization, shedding light on the pragmatic applications of tools such as ArcGIS and Cesium. Discussions will discuss the intricacies of capturing localized spatial data using LiDAR, underscoring its pivotal role in ecological design. The session will also explore the visualization of spatial data, particularly in the context of altering and comprehending multifunctional landscapes, as well as the potential of new tools e.g. viewshed analysis in assessing landscapes. This symposium endeavors to nurture a comprehensive understanding of the environment through 3D geovisualization, analysis, and innovative workflows. It marks a pivotal step towards a more holistic view of multifunctional landscapes.
S-04. Phenometrics in Wild & Managed Ecosystems: Theory, Method, Application
Contact: Geoff Henebry, Professor, Michigan State University, [email protected]
Co-Organizers: Bill Hargrove, USFS, Southern Research Station
Overview:
Phenologies are key recurring subplots within the evolutionary play unfolding amidst diverse landscapes in myriad ecological theatres. Phenological data come in various forms: historical observations, curated citizen science observations, protocol-driven technical observations, and instrumental records from phenocams, audio recordings, flux towers, and constellations of spaceborne sensors. In a world recently awash in remote sensing data at various spatial, temporal, and spectral resolutions in key parts of the electromagnetic spectrum, questions abound about optimal methods for determining and using metrics to characterizing and model land surface phenologies. Moreover, there is ever a pressing need to compare species-specific ground-level observations with instrumental records that may not resolve specific organisms. In this open symposium, we will explore the cutting-edge approaches to phenometric definition, detection, and integration with ancillary data and disciplinary perspectives. We welcome contributions from students, early career scientists, and established scholars to complement our handful of invited presentations. It is sure to be an interesting and engaging symposium!
S-05. Geospatial AI and Informatics for Urban & Ecosystems Analytics
Contact: Henry Bulley, Associate Professor, BMCC, The City University of New York, [email protected]
Co-Organizers: Monika Kuffer - University of Twente (ITC), The Netherlands; Samuel Adu-Prah - Sam Houston State University, Texas, USA; Shalini Dhyani - CSIR-National Environment Engineering Research Institute, India; Ellen Banzhaf - Helmholtz Centre for Environmental Research – UFZ, Germany; Moses Azong Cho - CSIR/University of Pretoria, South Africa; WenWen Li - Arizona State University, USA; Piotr Jankowski - San Diego State University, USA; Naa Dedei Tagoe - University of Mines and Technology, Ghana
Overview:
This session aims at advancing our understanding of and improving the Synergy between GeoAI and Urban Ecosystem Analytics, to support effective decision-making for disaster risk reduction for sustainable cities. Recent advances in the availability of Big Data, including in the use of Earth Observation (EO), together with advances in Geospatial Artificial Intelligence (GeoAI) promise to rapidly transform how we assess urban resilience and ecosystem services to enhance livelihood (SGD 11) in both High Income and Low/Middle-Income Countries. Geospatial Artificial Intelligence (GeoAI) combines geospatial science and artificial intelligence techniques to derive insights from complex ‘Big’ data to extract a rich tapestry of information from data (e.g., via deep learning algorithms) and perform predictive analysis (e.g., via machine learning algorithms). This is useful in automating the process of deriving timely information from Big Data, to help make predictions that have the potential to facilitate decision-making to improve the resilience of urban areas.
With more than 70 percent of human populations projected to live in Urban Areas by 2050, human–environmental systems will become more dependent on ecosystems for their resilience to climate change impacts and to ensure the sustainability of cities. Using GeoAI to assess land change dynamics and the role of ecosystem services, such as green infrastructure, in improving the livelihood of urban residents also relies heavily on the availability of accurate geospatial data which often comes from disparate multisensor and multiscale Earth Observation sensors.
Landscape ecology principles such as scale and heterogeneity are vital for effective analyses and modelling of land use dynamics, and how these affect the provisioning of ecosystem services. Our proposed symposium will bring together contributions from different parts of the world that address recent developments and challenges in the integration of GeoAI and Urban Ecosystem Analytics to extract vital information from increasing amounts of Earth Observation and other Big Data repositories.
We invite contributions that address core issues on GeoAI applications (GeoAI Moonshot), Big Data `scale and landscape structure on the ecosystems services provisioning, etc. We also encourage presentations that address climate change impacts and ecosystem resilience challenges of cities in developed countries and the Global South, especially in informal settlements in developing countries. Authors would be invited to submit manuscripts of their presentations for a special issue on Geospatial AI and Informatics for Urban & Ecosystems Analytics in the journal Applied Sciences.
S-06. Advancing Inclusive Data Science in Landscape Ecology
Contact: Kusum Naithani, Associate Professor, University of Arkansas, [email protected]
Co-Organizers: Falk Huettmann, University of Alaska-Fairbanks, AK, USA
Overview:
Landscape ecology, a multidisciplinary field, plays a critical role in addressing environmental challenges. While the open data and open science movement has made significant strides, it often overlooks the rights of Indigenous Peoples. Existing open data principles like FAIR (findable, accessible, interoperable, reusable) and others prioritize data sharing but fail to consider power imbalances and historical contexts. This poses a dilemma for Indigenous Peoples and others, who seek control over data and knowledge for their well-being. The CARE Principles for Indigenous Data Governance, rooted in people and purpose, can complement FAIR principles by emphasizing the human element and purpose in data advocacy. To promote ethical, accessible, and responsible data science in landscape ecology research and education, this symposium will facilitate knowledge exchange and best practices for data sharing and reuse.
This symposium serves as a vital platform for meaningful dialogue, forging connections, and promoting inclusivity and ethics in the landscape ecology community. Together, we aim to enhance our understanding of the environment while respecting the rights and perspectives of all participating communities.
(CANCELLED) S-07. Landscape Conservation Design: Where Data Science and Conservation Practitioners Come Together
Contact: Sean Finn, Science Coordinator, U.S. Fish & Wildlife Service, [email protected]
Co-Organizers: Amy Katz, Heart of the Rockies Initiative
S-08. Landscapes of Infection: Effects of Climate and Land Cover Change on Disease Transmission
Contact: Michael Wimberly, Professor, University of Oklahoma, [email protected]
Co-Organizers: Courtney Murdock, Cornell University
Overview:
Landscape ecology explores the effects of spatial patterns on ecological processes, placing a particular emphasis on linkages across multiple spatial scales. These themes are essential for understanding the biological, environmental, and anthropogenic factors that influence the transmission of vector-borne and zoonotic diseases as well as the consequent risks of human exposure. For this reason, the concepts and methods of landscape ecology are now widely applied to study the interactions of vectors, hosts, and pathogens in heterogeneous habitat mosaics. There is increasing recognition that the transmission cycles of many pathogens are sensitive to climate change, and that these responses will be locally mediated by patterns of land use and land cover. Landscape change, including urban growth and the expansion of agriculture and human settlement into natural habitats, can also facilitate the spread of existing disease as well as the emergence of new pathogens. To address these critical and timely topics, our proposed symposium will assemble a diverse group of speakers who are conducting research on disease ecology at landscape scales. The talks will address a broad range of diseases, including vector-borne diseases transmitted by mosquitoes and ticks as well as zoonotic diseases with birds, bats, rodents, and livestock as hosts. Specific topics of interest include methods for studying the landscape ecology of infectious diseases, the sensitivity of disease transmission cycles to the spatial patterns of landscape mosaics, the relevance of landscape ecology for understanding and forecasting climate-sensitive diseases, the effects of land cover and land use change on vectors, hosts, and pathogens, and the application of research results to support disease prevention, control, and elimination efforts.
S-09. Model Interactions Between Green Initiatives, People, and the Environment Using a Data Science Approach
Contact: Li An, Solon & Martha Dixon Endowed Professor, Auburn University, [email protected]
Co-Organizers: Conghe Song, professor, Department of Geography, University of North Carolina Chapel Hill, [email protected]; Qi Zhang, Research Assistant Professor, Department of Geography, University of North Carolina Chapel Hill, [email protected]; Rong Zhang, Research Scientist, College of Forestry, Wildlife, and Environment, Auburn University, [email protected]
Overview:
Humanity stands in an unprecedented era of climate change, environmental degradation, and rapid biodiversity loss. These interconnected crises threaten the very survival of humanity. Therefore, green initiatives—defined to be conservation programs, funds, payments, policies, or any endeavors—have been launched worldwide to restore, sustain, or improve nature’s capacity to benefit human beings. Despite reported successes in restoring and preserving the Nature—including ecosystems and their corresponding services such as clean air and water, food, and soil fertility—green initiatives are subject to many challenges, such as lack of sustainability over time, unclear mechanisms, and negative externalities in escalated consequences in the corresponding human-environment systems.
This symposium convenes a diverse group of researchers to delve into these challenges in complex human-environment systems using a data science approach. Employing data from three key sites in Nepal (i.e., Salyan, Pyuthan, and Chitwan), we address theoretical, methodological, and empirical issues related to green initiatives as follow:
1.Ecological effects of green initiatives;
2.Socioeconomic, demographic, and political consequences of green initiatives;
3.Potential mechanisms for success/failure observed in green initiatives;
4.Interactions between green initiatives that are implemented in the same area or contacted to same recipients;
5.Complexities in complex human-environment systems arising from green initiatives (e.g., feedback, nonlinearity, time lags).
6.Data science issues: data collection, analysis, and modeling, integration of multidisciplinary and multi-scale data, validation and appraisal, etc.
This symposium will substantially improve our understanding of multiple green initiatives in terms of driving force, social impacts, and ecological consequences, contributing to the effectiveness and sustainability of many green initiatives worldwide. On a methodological standpoint, this symposium will compare and evaluate the pros and cons of several traditional and non-traditional data science methods. Furthermore, we will consider a proposal for editing a book on the same topic and welcome potential collaborators.
S-10. Leveraging AI Advances in Landscape Ecology
Contact: Nathan Fox, Postdoctoral Fellow, University of Michigan, [email protected]
Co-Organizers: Prof. Derek Van Berkel, University of Michigan
Overview:
In the rapidly evolving world of technology, Artificial Intelligence (AI) emerges as a groundbreaking tool with the potential to revolutionize the realm of landscape ecology. This confluence of technology and nature promises not only enhanced analytical capabilities but also the unveiling of patterns and insights previously hidden in vast and complex ecological datasets.
Landscape ecology, inherently multidisciplinary, delves into the spatial patterns of landscapes and the processes that produce them. With the integration of AI, we can now automate the analysis of large-scale satellite imagery to monitor deforestation, predict the spread of invasive species, or even model the impacts of climate change on habitat fragmentation. Furthermore, AI paves the way for harnessing big data from novel sources, especially in the rapidly growing realm of online citizen science, where enthusiasts and professionals alike contribute to a collective pool of ecological information.
The symposium aims to serve as a nexus for innovators, researchers, and practitioners. We endeavor to showcase cutting-edge AI applications in landscape ecology, offering attendees a comprehensive view of current advancements. More importantly, this gathering seeks to foster an environment of collaboration, sparking new ideas and forging interdisciplinary partnerships. By bridging the gap between AI specialists and landscape ecologists, we hope to catalyze a wave of innovation, driving both fields into uncharted territories and achieving unprecedented breakthroughs.