DOI: 10.5061/dryad.hmgqnk9z4
title: Data and code from: Integrating multiple-covariate distance sampling and habitat modeling to inform conservation of the Asian houbara in central Iran

description: Reliable estimates of abundance and habitat associations are critical for
 conserving low-density species such as the Asian houbara (Chlamydotis
 macqueenii). Despite its vulnerable global status, robust estimates of
 houbara population size and habitat requirements remain scarce across much
 of its range. We combined multiple-covariate distance sampling (MCDS) with
 habitat modeling (Random Forest, GAMs, and GLMs) to estimate density and
 identify habitat relationships of houbaras in central Iran. In spring
 2022, 223 line-transect surveys (1,449 km) covering a 10,000 km2 area
 yielded 205 individuals across 67 detections. The best-supported MCDS
 model included fine gravel cover (positive) and vegetation height
 (negative) as detectability covariates, though their effects were weak.
 This model estimated a density of 0.53 individuals/km2 (95 % CI:
 0.37–0.75), corresponding to ~5,293 individuals (95 % CI: 3,778–7,473).
 Estimates were nearly identical to those from the best conventional
 distance sampling (CDS) model, indicating that detectability covariates
 did not materially improve model accuracy. However, habitat models
 consistently identified fine gravel cover and vegetation height as the
 most influential predictors, underscoring their ecological relevance for
 habitat use. Results indicate an ongoing population decline relative to
 previous regional estimates, highlighting the need for continued
 monitoring. Integrating population estimation with habitat modeling
 provides a practical framework for improving conservation assessments of
 the Asian houbara and other ground-dwelling birds in open habitats.
 Conservation actions should prioritize the protection and management of
 suitable habitats, supported by standardized survey protocols that improve
 population assessments and inform management decisions.
description: # Data and code from: Integrating multiple-covariate distance sampling and
 habitat modeling to inform conservation of the Asian houbara in central
 Iran Dataset DOI:
 [10.5061/dryad.hmgqnk9z4](https://doi.org/10.5061/dryad.hmgqnk9z4) ##
 Description of the data and file structure This supplementary dataset,
 integral to the associated research article, contains all data necessary
 for understanding and reproducing the analyses conducted in this study on
 the distribution, density, and habitat associations of the Asian houbara.
 The dataset includes transect‐based survey records, detection and
 distance‐sampling data, environmental and microhabitat measurements, and
 derived variables used in population estimation and predictive modeling.
 These data support analyses of density estimation and evaluation of
 environmental drivers using multiple statistical and machine‐learning
 approaches. The Excel files provided in this repository contain both raw
 and processed datasets required for interpretation, replication, and
 further comparative analyses, thereby promoting transparency,
 reproducibility, and reuse in ecological and conservation research.
 Additionally, an R script included in the repository contains all
 necessary code to reproduce the analyses presented in the study. ### Files
 and variables #### File: Asian_houbaras_data_-Distance_Sampling.csv
 **Description:**  ##### Variables * Region.Label:Province: Isfahan
 Province, Iran * Area:Study area size: 10000 km^2^ * Sample.Label:
 Transect Name * Effort: Sampling effort * distance: Perpendicular distance
 * size: Size of each cluster * BSH: bush cover percentage * SHB: shrub
 cover percentage * CR : coarse gravel percentage * FN: fine gravel
 percentage * MM : medium gravel percentage * SD: sand cover * HT: average
 vegetation height #### File: Asian_houbaras_data-_Habitat_Use.csv
 **Description:**  ##### Variables * Bush: bush cover percentage * Shrub:
 shrub cover percentage * Coarse : coarse gravel percentage * Fine: fine
 gravel percentage * Medium: medium gravel percentage * Sand: sand cover *
 Height: average vegetation height * Observation: number of Houbara in
 cluster #### File: Asian_houbaras_data-Distance_Sampling(High-Low).csv
 **Description:**  ##### Variables * Region.Label: Isfahan Province, Iran *
 Area: 10000 km² * Sample.Label: Transect Name * Effort: Sampling effort *
 distance: Perpendicular distance * size: size of each cluster * BSH: bush
 cover percentage * SHB: shrub cover percentage * CR : coarse gravel
 percentage * FN: fine gravel percentage * MM : medium gravel percentage *
 SD: sand cover * HT: average vegetation height ## Code/software Use the
 included file analysis.R. Analyses done in R.