�ݺ�ߣshows by User: lajensen1

�ݺ�ߣshows by User: lajensen1 / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: lajensen1 / Fri, 17 Jul 2015 04:00:56 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: lajensen1 Using STELLA to Explore Dynamic Single Species Models: The Magic of Making Humpback Whales Thrive in a Lab /lajensen1/envs545l1jensenlisa120128-50620099 d9041f50-8daa-4330-8bb1-591b4b8bddb2-150717040056-lva1-app6892
The use of formal, mathematical models allows stakeholders, decision makers and scientists to better visualize interactions and relationships within ecological systems. This study uses STELLA, a modeling tool, to simulate simple population dynamics for the humpback whale (Megaptera novaengliae) to better understand the impacts of reproductive and mortality rates as well as alternative solution algorithms used to drive the model. A wide range of population dynamics occurred as a result of varying time increments for calculating populations and use of available solution algorithms. Populations are most likely to achieve equilibrium when reproduction and mortality result in approximately the same number of individuals. ]]>
The use of formal, mathematical models allows stakeholders, decision makers and scientists to better visualize interactions and relationships within ecological systems. This study uses STELLA, a modeling tool, to simulate simple population dynamics for the humpback whale (Megaptera novaengliae) to better understand the impacts of reproductive and mortality rates as well as alternative solution algorithms used to drive the model. A wide range of population dynamics occurred as a result of varying time increments for calculating populations and use of available solution algorithms. Populations are most likely to achieve equilibrium when reproduction and mortality result in approximately the same number of individuals. ]]> Fri, 17 Jul 2015 04:00:56 GMT /lajensen1/envs545l1jensenlisa120128-50620099 lajensen1@slideshare.net(lajensen1) Using STELLA to Explore Dynamic Single Species Models: The Magic of Making Humpback Whales Thrive in a Lab lajensen1 The use of formal, mathematical models allows stakeholders, decision makers and scientists to better visualize interactions and relationships within ecological systems. This study uses STELLA, a modeling tool, to simulate simple population dynamics for the humpback whale (Megaptera novaengliae) to better understand the impacts of reproductive and mortality rates as well as alternative solution algorithms used to drive the model. A wide range of population dynamics occurred as a result of varying time increments for calculating populations and use of available solution algorithms. Populations are most likely to achieve equilibrium when reproduction and mortality result in approximately the same number of individuals. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/d9041f50-8daa-4330-8bb1-591b4b8bddb2-150717040056-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> The use of formal, mathematical models allows stakeholders, decision makers and scientists to better visualize interactions and relationships within ecological systems. This study uses STELLA, a modeling tool, to simulate simple population dynamics for the humpback whale (Megaptera novaengliae) to better understand the impacts of reproductive and mortality rates as well as alternative solution algorithms used to drive the model. A wide range of population dynamics occurred as a result of varying time increments for calculating populations and use of available solution algorithms. Populations are most likely to achieve equilibrium when reproduction and mortality result in approximately the same number of individuals.

Using STELLA to Explore Dynamic Single Species Models: The Magic of Making Humpback Whales Thrive in a Lab from Lisa Jensen

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0 Land cover supervised classification at Toro Park, California /slideshow/envs436536a9jensenlisa111116/50619162 f2801e90-3154-4590-ba1c-1c5887853d49-150717031906-lva1-app6892
Using USGS National Agriculture Imagery Program (NAIP) data, a supervised classification was performed within ERDAS Imagine to provide resource managers a better understanding of land cover at Toro Park, California.]]>
Using USGS National Agriculture Imagery Program (NAIP) data, a supervised classification was performed within ERDAS Imagine to provide resource managers a better understanding of land cover at Toro Park, California.]]> Fri, 17 Jul 2015 03:19:06 GMT /slideshow/envs436536a9jensenlisa111116/50619162 lajensen1@slideshare.net(lajensen1) Land cover supervised classification at Toro Park, California lajensen1 Using USGS National Agriculture Imagery Program (NAIP) data, a supervised classification was performed within ERDAS Imagine to provide resource managers a better understanding of land cover at Toro Park, California. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/f2801e90-3154-4590-ba1c-1c5887853d49-150717031906-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Using USGS National Agriculture Imagery Program (NAIP) data, a supervised classification was performed within ERDAS Imagine to provide resource managers a better understanding of land cover at Toro Park, California.

Land cover supervised classification at Toro Park, California from Lisa Jensen

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0 Habitat models: Predicting Sebastes presence in the Del Monte Shalebeds /slideshow/jensenreport051712/50619051 13110807-cb18-4e06-968f-5ce045fab69b-150717031312-lva1-app6892
The structure and composition of habitat play key roles in determining the spatial patterns of biota within marine landscapes. Understanding species habitat associations provides the information necessary to predict the diversity and abundance of species thus enabling greater control over species management and sustainability. Landscape ecology is commonly used in the terrestrial environment to understand the relationship between spatial patterns and ecological processes. While some landscape ecology metrics lend themselves to marine spatial studies more recent studies offer new ways of understanding the spatial relationships between species and the marine environment utilizing remote sensing and marine focused spatial pattern measures. Advances in remote sensing and spatial pattern recognition make it possible to assess habitat value within rocky reefs and create predictive models of fish association. Understanding habitat associations and having the ability to predict fish aggregations is a valuable tool for resource managers and marine spatial planning during development or redesign of marine protected areas. The oceans around the world are suffering a variety of abuses which may be lending to the decline in abundance of many economically valuable fish species. Improved resource management is necessary to ensure sustainability of the world’s fisheries. Multiple predictors are often used in development of predictive models for groundfish including complexity (VRM), relative topographic position (TPI), depth, distance to maximum VRM, and slope. Habitat complexity offers shelter from predation, a place for larval settlement, and is believed to be a predictor of species diversity. This study investigated use of habitat characteristics as predictors of species presence or absence at rocky reefs off the coast of Monterey, California over the Del Monte Shalebeds. Using bathymetric and fish aggregation data collected by the Seafloor Mapping Lab (SFML) at California State University, Monterey Bay (CSUMB) a probability model for groundfish aggregations in the shalebeds.]]>
The structure and composition of habitat play key roles in determining the spatial patterns of biota within marine landscapes. Understanding species habitat associations provides the information necessary to predict the diversity and abundance of species thus enabling greater control over species management and sustainability. Landscape ecology is commonly used in the terrestrial environment to understand the relationship between spatial patterns and ecological processes. While some landscape ecology metrics lend themselves to marine spatial studies more recent studies offer new ways of understanding the spatial relationships between species and the marine environment utilizing remote sensing and marine focused spatial pattern measures. Advances in remote sensing and spatial pattern recognition make it possible to assess habitat value within rocky reefs and create predictive models of fish association. Understanding habitat associations and having the ability to predict fish aggregations is a valuable tool for resource managers and marine spatial planning during development or redesign of marine protected areas. The oceans around the world are suffering a variety of abuses which may be lending to the decline in abundance of many economically valuable fish species. Improved resource management is necessary to ensure sustainability of the world’s fisheries. Multiple predictors are often used in development of predictive models for groundfish including complexity (VRM), relative topographic position (TPI), depth, distance to maximum VRM, and slope. Habitat complexity offers shelter from predation, a place for larval settlement, and is believed to be a predictor of species diversity. This study investigated use of habitat characteristics as predictors of species presence or absence at rocky reefs off the coast of Monterey, California over the Del Monte Shalebeds. Using bathymetric and fish aggregation data collected by the Seafloor Mapping Lab (SFML) at California State University, Monterey Bay (CSUMB) a probability model for groundfish aggregations in the shalebeds.]]> Fri, 17 Jul 2015 03:13:12 GMT /slideshow/jensenreport051712/50619051 lajensen1@slideshare.net(lajensen1) Habitat models: Predicting Sebastes presence in the Del Monte Shalebeds lajensen1 The structure and composition of habitat play key roles in determining the spatial patterns of biota within marine landscapes. Understanding species habitat associations provides the information necessary to predict the diversity and abundance of species thus enabling greater control over species management and sustainability. Landscape ecology is commonly used in the terrestrial environment to understand the relationship between spatial patterns and ecological processes. While some landscape ecology metrics lend themselves to marine spatial studies more recent studies offer new ways of understanding the spatial relationships between species and the marine environment utilizing remote sensing and marine focused spatial pattern measures. Advances in remote sensing and spatial pattern recognition make it possible to assess habitat value within rocky reefs and create predictive models of fish association. Understanding habitat associations and having the ability to predict fish aggregations is a valuable tool for resource managers and marine spatial planning during development or redesign of marine protected areas. The oceans around the world are suffering a variety of abuses which may be lending to the decline in abundance of many economically valuable fish species. Improved resource management is necessary to ensure sustainability of the world’s fisheries. Multiple predictors are often used in development of predictive models for groundfish including complexity (VRM), relative topographic position (TPI), depth, distance to maximum VRM, and slope. Habitat complexity offers shelter from predation, a place for larval settlement, and is believed to be a predictor of species diversity. This study investigated use of habitat characteristics as predictors of species presence or absence at rocky reefs off the coast of Monterey, California over the Del Monte Shalebeds. Using bathymetric and fish aggregation data collected by the Seafloor Mapping Lab (SFML) at California State University, Monterey Bay (CSUMB) a probability model for groundfish aggregations in the shalebeds. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/13110807-cb18-4e06-968f-5ce045fab69b-150717031312-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> The structure and composition of habitat play key roles in determining the spatial patterns of biota within marine landscapes. Understanding species habitat associations provides the information necessary to predict the diversity and abundance of species thus enabling greater control over species management and sustainability. Landscape ecology is commonly used in the terrestrial environment to understand the relationship between spatial patterns and ecological processes. While some landscape ecology metrics lend themselves to marine spatial studies more recent studies offer new ways of understanding the spatial relationships between species and the marine environment utilizing remote sensing and marine focused spatial pattern measures. Advances in remote sensing and spatial pattern recognition make it possible to assess habitat value within rocky reefs and create predictive models of fish association. Understanding habitat associations and having the ability to predict fish aggregations is a valuable tool for resource managers and marine spatial planning during development or redesign of marine protected areas. The oceans around the world are suffering a variety of abuses which may be lending to the decline in abundance of many economically valuable fish species. Improved resource management is necessary to ensure sustainability of the world’s fisheries. Multiple predictors are often used in development of predictive models for groundfish including complexity (VRM), relative topographic position (TPI), depth, distance to maximum VRM, and slope. Habitat complexity offers shelter from predation, a place for larval settlement, and is believed to be a predictor of species diversity. This study investigated use of habitat characteristics as predictors of species presence or absence at rocky reefs off the coast of Monterey, California over the Del Monte Shalebeds. Using bathymetric and fish aggregation data collected by the Seafloor Mapping Lab (SFML) at California State University, Monterey Bay (CSUMB) a probability model for groundfish aggregations in the shalebeds.

Habitat models: Predicting Sebastes presence in the Del Monte Shalebeds from Lisa Jensen

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0 Habitat suitability models: Predicting Sebastes presence at the Del Monte Shalebeds /slideshow/envs532posterjensen/50618741 3bcc2d49-fb40-486b-8cd9-0ba5ba71df3a-150717025552-lva1-app6892
Habitat structure plays a key role in determining spatial patterns of marine biota. Understanding species habitat associations offers resource managers better control over species management and sustainability. Terrestrial landscape ecology metrics used to analyze the spatial relationships for habitat associations can often be adapted to marine habitat association and compliment marine specific metrics. Rockfish are an economically important species for California fisheries, some of these species have been overexploited and are at risk of localized extinction. This research will aid in identification of spatial patterns important to rockfish. The Del Monte Shalebeds are located approximately 1 kilometer offshore of Cannery Row in Monterey, CA. The shalebeds and associated granitic outcrops are home to different species of rockfish including Sebastes pinninger which is listed under the Endangered Species Act as a threatened species. The area for this study is approximately 11 km2 and includes 4.4 km2 of hard substrate with high relief granitic outcrop and low relief shalebeds. Past research indicates there may be different degrees of site fidelity depending on topographic relief with rockfish exhibiting a lower degree of site fidelity over low relief substrate. ]]>
Habitat structure plays a key role in determining spatial patterns of marine biota. Understanding species habitat associations offers resource managers better control over species management and sustainability. Terrestrial landscape ecology metrics used to analyze the spatial relationships for habitat associations can often be adapted to marine habitat association and compliment marine specific metrics. Rockfish are an economically important species for California fisheries, some of these species have been overexploited and are at risk of localized extinction. This research will aid in identification of spatial patterns important to rockfish. The Del Monte Shalebeds are located approximately 1 kilometer offshore of Cannery Row in Monterey, CA. The shalebeds and associated granitic outcrops are home to different species of rockfish including Sebastes pinninger which is listed under the Endangered Species Act as a threatened species. The area for this study is approximately 11 km2 and includes 4.4 km2 of hard substrate with high relief granitic outcrop and low relief shalebeds. Past research indicates there may be different degrees of site fidelity depending on topographic relief with rockfish exhibiting a lower degree of site fidelity over low relief substrate. ]]> Fri, 17 Jul 2015 02:55:52 GMT /slideshow/envs532posterjensen/50618741 lajensen1@slideshare.net(lajensen1) Habitat suitability models: Predicting Sebastes presence at the Del Monte Shalebeds lajensen1 Habitat structure plays a key role in determining spatial patterns of marine biota. Understanding species habitat associations offers resource managers better control over species management and sustainability. Terrestrial landscape ecology metrics used to analyze the spatial relationships for habitat associations can often be adapted to marine habitat association and compliment marine specific metrics. Rockfish are an economically important species for California fisheries, some of these species have been overexploited and are at risk of localized extinction. This research will aid in identification of spatial patterns important to rockfish. The Del Monte Shalebeds are located approximately 1 kilometer offshore of Cannery Row in Monterey, CA. The shalebeds and associated granitic outcrops are home to different species of rockfish including Sebastes pinninger which is listed under the Endangered Species Act as a threatened species. The area for this study is approximately 11 km2 and includes 4.4 km2 of hard substrate with high relief granitic outcrop and low relief shalebeds. Past research indicates there may be different degrees of site fidelity depending on topographic relief with rockfish exhibiting a lower degree of site fidelity over low relief substrate. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/3bcc2d49-fb40-486b-8cd9-0ba5ba71df3a-150717025552-lva1-app6892-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Habitat structure plays a key role in determining spatial patterns of marine biota. Understanding species habitat associations offers resource managers better control over species management and sustainability. Terrestrial landscape ecology metrics used to analyze the spatial relationships for habitat associations can often be adapted to marine habitat association and compliment marine specific metrics. Rockfish are an economically important species for California fisheries, some of these species have been overexploited and are at risk of localized extinction. This research will aid in identification of spatial patterns important to rockfish. The Del Monte Shalebeds are located approximately 1 kilometer offshore of Cannery Row in Monterey, CA. The shalebeds and associated granitic outcrops are home to different species of rockfish including Sebastes pinninger which is listed under the Endangered Species Act as a threatened species. The area for this study is approximately 11 km2 and includes 4.4 km2 of hard substrate with high relief granitic outcrop and low relief shalebeds. Past research indicates there may be different degrees of site fidelity depending on topographic relief with rockfish exhibiting a lower degree of site fidelity over low relief substrate.

Habitat suitability models: Predicting Sebastes presence at the Del Monte Shalebeds from Lisa Jensen

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0 https://cdn.slidesharecdn.com/profile-photo-lajensen1-48x48.jpg?cb=1566403248 Environmental Scientist with diversified experience including ecology and natural resource management, remote sensing, geographic information systems (GIS), and federal and state environmental regulations (Clean Water Act, CEQA, NEPA, California Ocean Plan, and Endangered Species Act). Specific skills include environmental analysis & planning, analysis and compliance with local, state and federal regulations, program & project management, spatial analytics, marine science, policy and technology, and climate change. Specialties include, Analysis, Database Design & Implementation, Data Quality Analysis & Validation, Predictive Analytics, and Statistical Modeling. seafloor.csumb.edu/csmp/csmp.html https://cdn.slidesharecdn.com/ss_thumbnails/d9041f50-8daa-4330-8bb1-591b4b8bddb2-150717040056-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds lajensen1/envs545l1jensenlisa120128-50620099 Using STELLA to Explor... https://cdn.slidesharecdn.com/ss_thumbnails/f2801e90-3154-4590-ba1c-1c5887853d49-150717031906-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/envs436536a9jensenlisa111116/50619162 Land cover supervised ... https://cdn.slidesharecdn.com/ss_thumbnails/13110807-cb18-4e06-968f-5ce045fab69b-150717031312-lva1-app6892-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/jensenreport051712/50619051 Habitat models: Predic...