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A Precise and Autonomous System for the Detection of Insect Emergence Patterns

A Precise and Autonomous System for the Detection of Insect Emergence Patterns

Published on: January 9, 2019

Estimating thresholds in occupancy when species detection is imperfect.

Jay E Jones¹, Andrew J Kroll, Jack Giovanini

¹Weyerhaeuser Company, WTC 1B20, P.O. Box 9777, Federal Way, Washington 98063-9777, USA. jay.jones@weyerhaeuser.com

|February 23, 2012

Summary

Accurate ecological threshold estimation requires accounting for imperfect species detection. New models improve occupancy threshold analysis, revealing that many apparent thresholds disappear when detection probability is considered.

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A Method for Quantifying Foliage-Dwelling Arthropods

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Published on: October 20, 2019

Area of Science:

Ecology
Conservation Biology
Statistical Modeling

Background:

Ecological thresholds are crucial for understanding state changes and informing conservation.
Existing occupancy models often overlook imperfect species detection, potentially leading to inaccurate ecological conclusions.

Purpose of the Study:

To develop and validate a novel statistical model for estimating occupancy thresholds while accounting for imperfect species detection.
To assess the impact of imperfect detection on the inference of ecological relationships and conservation targets.

Main Methods:

A joint model was developed to simultaneously estimate species occurrence and detection probabilities.
The model was evaluated using simulation studies and applied to avian occurrence data with replicate surveys.
Results were compared against a standard segmented logistic regression model (frequentist and Bayesian).

Main Results:

Simulation results demonstrated the model's accuracy and precision, with improved estimates at larger sample sizes.
In empirical data, apparent threshold relationships for some species were not supported when imperfect detection was incorporated.
Accounting for nondetection generally resulted in wider confidence intervals for threshold effects.

Conclusions:

The proposed model provides a more robust method for threshold detection in ecological studies by addressing imperfect detection.
Failure to account for imperfect detection can lead to false positives in threshold identification, impacting conservation strategies.
The model framework is adaptable for investigating abundance thresholds and complex hierarchical ecological systems.