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A website with links to the Landscape Conservation Cooperative (LCC) Integrated Data Management Network (IDMN) final report as well as individual LCC websites. The IDMN worked with over 20 organizations over two years to bring coherence to the LCC information management landscape. Specifically, the IDMN Network tried to address ways LCC partners implemented the basic building blocks of data management. Issues addressed included building and sharing science products with partners, securely storing those data for the long term, and evaluating ways to get those outputs to cooperators and eventually the public. Over the course of the IDMN project, the scope was expanded to address ways to track projects that produced...
This work provides a flexible and scalable framework to assess the impacts of climate change on streamflow and stream temperature within the North Atlantic Landscape Conservation Cooperative (NALCC) region. This is accomplished through use of lumped parameter, physically-based, conceptual hydrologic and stream temperature models formulated in a hierarchical Bayesian framework. This allows for model predictions of streamflow and temperature at ungaged locations and a formal accounting of model estimate uncertainty at each location, something not previously achieved in these models. These environmental models will also link seamlessly with the land use and fish models. The final products of this project will provide:...
This R code (Nest_Cards_QC.R) is used to process the raw legacy nest card data (1985 - 2019) and produce the quality controlled legacy nest card data for analysis and sharing. This code does not quality control the double searched plots (R2 plots in 1995-99), which is done in the file ‘PrepData.R’. Basic operations include transforming missing value to a common code, transforming other variable to match the data dictionary for nest cards, and resolving non-unique observer initials. The code requires the raw data (“1985-2019_Nest Cards_10-24-19_cleaned.xlsx”) and the table of observer names (“Observer Names_1985-2019_10-24-19.xlsx”). The code writes the QC nest card file “Nest_Cards_1985_2019_QC.csv”. Mostly obseration...
Categories: Data,
Software;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
The Desert Landscape Conservation Cooperative Land Cover Map shows land cover at a regional scale (1:2,500,000). The files provided are graphic design files that can be used to plot a publication-quality, poster-size map.Scale: 1:2,500,000 Map poster dimensions: 34 x 44 inches Data sources:Land cover from North American Environmental Atlas by the Commission for Environmental Cooperation, 2010. Physiographic regions from Natural Earth 1:10 million scale Physical Labels (3.0.0) derived from Patterson’s Physical Map of the World, 2008. Hydrography, populated places, and political boundaries from National Atlas of the United States, 2004. File descriptions: DLCC_LandCover.ai is an Adobe Illustrator file. DLCC_LandCover.pdf...
Categories: Data;
Types: ArcGIS REST Map Service,
ArcGIS Service Definition,
Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: Academics & scientific researchers,
Conservation NGOs,
DATA ANALYSIS AND VISUALIZATION,
Data,
Data.gov Desert Landscape Conservation Cooperative,
The Gulf Coast Prairie Landscape Conservation Cooperative needed seamless landcover data for the south-central United States. This information is essential for developing computer modeling tools related to the conservation of many terrestrial species and determining the quality of vegetation to assess current and desired conditions.
Categories: Data,
Project;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: 2012,
Conservation NGOs,
DATA ANALYSIS AND VISUALIZATION,
DATA ANALYSIS AND VISUALIZATION,
Data Acquisition and Development,
DLCC’s Vegetation Map Pilot is a project envisioned initially as a supervised classification of two or three small areas of the DLCC. DLCC technical stakeholders advised changing from a supervised classification to an object oriented classification (OOC) method.This report presents the findings, feasibility, and lessons-learned during the exploration and object oriented classification process and results of the two sites on the United States-Mexico border, this is needed information before considering a full-scale, Vegetation Mapping Project, to include bigger areas or the totality of the Desert LCC region.
Categories: Data;
Tags: Academics & scientific researchers,
Aquascalientes,
Aquascalientes,
Arizona,
Arizona,
Desert Landscape Conservation Cooperative Boundary delineates the spatial extent of the DLCC. The vector boundary is available as both a shapefile and KML file. This is a derivative product of the LCCs shapefile produced by the U.S. Fish and Wildlife Service, accessed from http:/http://www.fws.gov/GIS/data/national/ in 2014.To access the KML file, click on the ScienceBase URL and then select Open in Google Earth (KML). To access the shapefile (FWS_LCC_DLCC.shp), click on FWS_LCC_DLCC.zip linked from this product profile.
The Desert Landscape Conservation Cooperative (LCC) is a partnership formed and directed by resource management entities as well as interested public and private entities in the Mojave, Sonoran, and Chihuahuan Desert and montane sky island regions of the southwestern United States and northern Mexico. Desert LCC science depends on access to transboundary base datasets. Given the importance of vegetation such as grasslands and riparian vegetation in conservation science, a bi-national, landscape-scale vegetation data layer with classes relevant to Desert LCC research is crucial. One objective of this project is to investigate appropriate methodologies and landscape scales to create a Desert LCC binational land cover...
Categories: Data;
Tags: Academics & scientific researchers,
Aquascalientes,
Arizona,
Baja California,
California,
The Missouri Resource Assessment Partnership (MoRAP) of the University of Missouri, in conjunction with the Oklahoma Biological Survey of the University of Oklahoma, produced a vegetation and landcover GIS data layer for the eastern portions of Oklahoma. This effort was accomplished with direction and funding from the Oklahoma Department of Wildlife Conservation and state and federal partners (particularly the Gulf Coast Prairie and Great Plains Landscape Conservation Cooperatives of the U. S. Fish and Wildlife Service). The legend for the layer is based on NatureServe’s Ecological System Classification, with finer thematic units derived from land cover and abiotic modifiers of the System unit. Data for development...
Successful conservation strategies in the face of climate change will require careful consideration of how changing climate will affect wildlife and habitats. Development of innovative, data driven, accessible tools will assist in understanding and planning for those effects. This document serves the final report for U.S. Fish and Wildlife Service (USFWS) project # F11AC00028 that provides tools that enhance the U.S. Fish and Wildlife Service’s (and others) climate change toolbox. This project was funded to (1) develop climate envelope models and associated prediction maps for 26 federally threatened and endangered terrestrial (T&E) vertebrate species occurring in peninsular Florida; (2) provide a technical guidebook...
These data accompany task 4 as described in the final report, “Comparability of landscape connectivity products for large-scale landscape planning.”
This guidebook is intended to provide a practical overview of climate envelope modeling for conservation professionals and natural resource managers. The material is intended for people with little background or experience in climate envelope modeling who want to better understand and interpret models developed by others and the results generated by such models, or want to do some modeling themselves. This is not an exhaustive review of climate envelope modeling, but rather a brief introduction to some key concepts in the discipline. Here we treat selected topics from a practical perspective, using minimal jargon to explain and illustrate some of the many issues that one has to be aware of when using climate envelope...
abstract
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: EARTH SCIENCE > ATMOSPHERE,
EARTH SCIENCE > CLIMATE INDICATORS,
EARTH SCIENCE > HUMAN DIMENSIONS,
EARTH SCIENCE SERVICES,
map,
abstract
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: EARTH SCIENCE > ATMOSPHERE,
EARTH SCIENCE > CLIMATE INDICATORS,
EARTH SCIENCE > HUMAN DIMENSIONS,
EARTH SCIENCE SERVICES,
map,
abstract
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: EARTH SCIENCE > ATMOSPHERE,
EARTH SCIENCE > CLIMATE INDICATORS,
EARTH SCIENCE > HUMAN DIMENSIONS,
EARTH SCIENCE SERVICES,
map,
abstract
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: EARTH SCIENCE > ATMOSPHERE,
EARTH SCIENCE > CLIMATE INDICATORS,
EARTH SCIENCE > HUMAN DIMENSIONS,
EARTH SCIENCE SERVICES,
map,
abstract
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: EARTH SCIENCE > ATMOSPHERE,
EARTH SCIENCE > CLIMATE INDICATORS,
EARTH SCIENCE > HUMAN DIMENSIONS,
EARTH SCIENCE SERVICES,
map,
R code that takes in the nest capture history data (chdata.csv), reformats it for model fitting in Program Mark via the R package RMark. A series of models of increasing complexity are fit and compared using AIC. Output is written to text files for each model but is generally not used or saved. Code can be run to generate model results and R workspaces/ object to inspect parameter estimates. The primary purpose of this code is to explore model structures for predicting detection and as an attempt to reproduce historically used parameter estimates in past nest plot reports (e.g., Fischer et al. 2017 and earlier). Results from ‘Model 7’ are most similar to detection estimates used in the past.
Categories: Data,
Software;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
ANIMALS/VERTEBRATES,
BIOLOGICAL CLASSIFICATION,
BIOLOGICAL CLASSIFICATION,
This R code (YKDsalinity_QC.R) is used to process the raw legacy salinity data for fixed and random plots (2006 - 2019) and produce the quality controlled legacy salinity data for analysis and sharing (YKDsalinity_QC.csv). Basic operations include transforming missing value to a common code, transforming other variables to match the data dictionary, and cleaning spatial location issues. Of special note is that this QC process discover significant error in location data due to a variety of reasons so the random plot centers are added to the data table and should be used for analysis. The code requires the raw data (“Official_YKD.SALINITY.DATA.MASTER.2020.csv”), a definition of the nest plot study area (“NestPlotStudyAreaBoundary.geojson”),...
Categories: Data,
Software;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: BIOSPHERE,
BIOSPHERE,
BIOSPHERE,
DATA INTEROPERABILITY,
DATA INTEROPERABILITY,
abstract
Categories: Data;
Types: Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service;
Tags: EARTH SCIENCE > ATMOSPHERE,
EARTH SCIENCE > CLIMATE INDICATORS,
EARTH SCIENCE > HUMAN DIMENSIONS,
EARTH SCIENCE SERVICES,
map,
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