Project: Supporting NatureServe’s Species Habitat Modeling (SHM) Program

Contact: Anne Gage
                  Chief of Staff, Science
                  Email: Anne_Gage@natureserve.org
                  Phone: 703-908-8914              
 
About NatureServe:
For nearly 50 years, NatureServe has been the authoritative source for biodiversity data throughout the U.S. and Canada, answering fundamental questions about what exists, where it is found, and how it is doing. With an international network of over 60 natural heritage programs, NatureServe is the leading source of information on rare and endangered species and threatened ecosystems. To protect threatened biodiversity, NatureServe works with over 1,000 conservation scientists to collect, aggregate, and standardize biodiversity statistics, providing comprehensive data to the public for strategic conservation efforts.
 

  • Demonstrated expertise in producing species distribution models, ecological models, and geospatial analysis in the R statistical and programming environment.
  • Expertise in all aspects of biodiversity data science in R, including the integration, processing, analysis and visualization of large biodiversity datasets at the species and ecosystem levels.
  • Experience processing environmental predictor data from a variety of sources, including remote sensing and climate models.
  • Experience with SQL and SQLite.
  • Experience with automated reports in Rmarkdown, knitr and LateX.
  • Experience in reproducible workflows, code version control and management (Git, GitHub).
  • Ability to develop sound processes for data management and documentation.

 

 

NatureServe’s mission is to leverage the power of science, data, and technology to guide biodiversity conservation and stewardship. NatureServe is seeking a contractor for NatureServe’s Species Habitat Modeling (SHM) Program, which aims to build and maintain a library of expert-reviewed high-resolution models of the habitat and distribution of rare and endangered species in North America.  Interested parties should submit Expressions of Interest, including a resume, hourly pay rate, total number of hours, and total price, along with any questions to Anne Gage. Please also note that liability and workers compensation insurance is required.   

 

 

 

 

 

 

 

 

Purpose:

The primary focus of this engagement is to obtain technical support to NatureServe’s Species Habitat Modeling Program through model building, model revision, and/or model documentation and delivery. Support for the SHM Program will advance several funded projects with partners like the U.S. Forest Service that will inform land management decisions to maximize conservation outcomes for imperiled biodiversity.

 

Scope of Work:

Sub-tasks may include leveraging existing R workflows to:

·         Identify relevant model extent for model target

·         Process species occurrence data from across the NatureServe Network and additional biodiversity data sources (e.g., GBIF or iNaturalist)

·         Identify and process relevant high-resolution environmental predictor data

·         Identify relationships between species occurrence data and environmental variation across the model extent using machine learning algorithms (primarily RandomForest, potentially also MaxEnt and Generalised Boosted Models)

·         Evaluate and document statistical performance of models

·         Generate mapped model predictions across model extent

·         Revise model outputs based on expert reviews

·         Package and upload models for inclusion within NatureServe Explorer Pro

 

Project Timeline: November 1, 2023—September 30, 2024

 

Required Skills

 

Preferred Skills

·         Experience with ESRI products, including ArcGIS.

·         Experience with Python and ArcPy.

·         Experience with High-Performance Computing and parallel programming in R in the cloud (AWS/Azure).

·         Experience with harvesting data from the web using Application Programming Interfaces (APIs) and web scraping.

 

Deadline for Responses: October 4, 2023

This position has been filled.