DOI: 10.5061/dryad.qbzkh18k6
title: Predicting daily activity time through ecological niche modeling and microclimatic data

description: 1. Climate temporality is a phenomenon that affects species' activity
 and distribution patterns across spatial and temporal scales. Despite the
 global availability of microclimatic data, their use to predict activity
 patterns and distributions remains scarce, particularly at fine temporal
 scales (e.g., &lt; month). Predicting activity patterns based on
 climatic data may allow us to foresee some of the consequences of climate
 change, particularly for ectothermic vertebrates. 2. The Gila monster
 exhibits marked daily and seasonal activity patterns linked to physiology
 and reproduction. Here we evaluate if ecological niche models fitted using
 microclimate data can predict temporal activity patterns using the Gila
 monster (Heloderma suspectum) as a study system. Further, we identified if
 the activity patterns are related to physiological constraints. 3. We used
 dated occurrences from museum specimens and human observations to generate
 and test ecological niche models using minimum-volume ellipsoids. We
 generated hourly microclimatic data for each occurrence site for ten years
 using the NicheMapR package. For ecological niche modeling, we compared
 the traditional seasonal approach versus a daily activity pattern strategy
 for model construction. We tested both using the omission rate of
 independent observations (citizen science data). Finally, we tested if
 unimodal and bimodal activity patterns for each season could be recreated
 through ecological niche modeling and if these patterns followed known
 physiological constraints. 4. The unimodal and bimodal activity patterns
 previously reported directly from tracking individuals across the year
 were recovered by using niche modeling and microclimate across the
 species' geographical range. We found that upper thermal tolerances
 can explain the daily activity patterns of this species. 5. We conclude
 that ecological niche models trained with microclimatic data can be used
 to predict activity patterns at fine temporal scales, particularly on
 ectotherm species of arid zones coping with rapid climate modifications.
 Further, the use of fine temporal scale variables can lead to a better
 niche delimitation, enhancing the results of any research objective that
 uses correlative models.
description: We generated an ecological
 niche model using georeferenced specimen records (see Occurrence data) and
 microclimatic data at an hourly resolution (see Environmental data). Since
 the specimen records did not include the exact hour of collection, we made
 use of an available dataset of daily activity patterns for every season
 throughout the year based on individual observations and radio-tracked
 individuals of <em>Heloderma suspectum</em> (see daily
 activity pattern section below, Beck 2005). We associated the
 microclimatic data that corresponded to the time of activity sensu Beck
 (2005) according to the specific season for each record. We used the
 prediction of the ecological niche model for occurrence sites
 (suitability) to recover the daily activity patterns per season (see Daily
 activity patterns and microclimate variation). Finally, we validated the
 model's predictions regarding suitability per hour for each season
 concerning Beck's activity data and to iNaturalist records that had
 the time of sighting (see Ecological niche
 modeling). 
description: R software