Inaccessible rocky cliffs: An optimized method for plant data collection in extreme environments

Area of Science:

• Ecology
• Botany
• Environmental Science

Background:

• Traditional plant density assessments rely on complete counts.
• Inaccessible environments like rocky cliffs present significant fieldwork challenges.
• Existing data collection methods are often time-consuming and resource-intensive.

Purpose of the Study:

• To develop a method for estimating plant population sizes in difficult-to-access habitats.
• To reduce the minimum sampling effort required for ecological surveys.
• To optimize resource allocation in fieldwork without compromising accuracy.

Main Methods:

• Calculating the minimum effort for plant data collection in extreme environments.
• Identifying the theoretical distribution function that best fits species distribution data.
• Utilizing incomplete data sets for population size estimation.

Main Results:

• The proposed method significantly reduces time, material, and human resources for fieldwork.
• Accurate population size estimations are maintained despite reduced sampling effort.
• The system is effective for plant surveys in vertical and inaccessible terrains.

Conclusions:

• This approach offers a more efficient and cost-effective way to study plant populations in challenging environments.
• It enables accurate ecological assessments where traditional methods are not feasible.
• The method supports conservation efforts by making surveys of rare or endangered species in extreme habitats more attainable.