Estimating environmental suitability
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Help
Clear All

Query Builder

Query box

Help
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Estimating environmental suitability

Filetype[PDF-1.28 MB]


Details Related Documents You May Also Like

Details:

  • Journal Title:
    Ecosphere
  • Personal Author:
  • NOAA Program & Office:
    NOS (National Ocean Service)
  • Description:
    Methods for modeling species’ distributions in nature are typically evaluated empirically with respect to data from observations of species occurrence and, occasionally, absence at surveyed locations. Such models are relatively “theory‐free.” In contrast, theories for explaining species’ distributions draw on concepts like fitness , niche , and environmental suitability . This paper proposes that environmental suitability be defined as the conditional probability of occurrence of a species given the state of the environment at a location. Any quantity that is proportional to this probability is a measure of relative suitability and the support of this probability is the niche. This formulation suggests new methods for presence‐background modeling of species distributions that unify statistical methodology with the conceptual framework of niche theory. One method, the plug‐and‐play approach, is introduced for the first time. Variations on the plug‐and‐play approach were studied with respect to their numerical performance on 106 species from an exhaustively sampled presence–absence survey of vegetation in the Canton of Vaud, Switzerland. Additionally, we looked at the robustness of these methods to the presence of irrelevant information and sample size. Although irrelevant variables eroded the predictive performance of all methods, these methods were found to be both numerically and statistically robust.
  • Keywords:
  • Source:
    Ecosphere 9(9): e02373
  • DOI:
  • Document Type:
    Journal Article
  • Funding:
    Grant no. NA10NOS4780218
  • Rights Information:
    CC BY
  • Compliance:
    Submitted
  • Main Document Checksum:
  • Download URL:
  • File Type:

Supporting Files

  • No Additional Files

More +

Related Documents

You May Also Like

Checkout today's featured content at repository.library.noaa.gov

Version 3.26