Effects of sun angle, lunar illumination, and diurnal temperature on temporal movement rates of sympatric ocelots and bobcats in South Texas

Ocelots in the moonlight: Influence of lunar phase on habitat selection and movement of two sympatric felids

Various landscape and environmental factors influence animal movement and habitat selection. Lunar illumination affects nocturnal visual perception of many species and, consequently, may influence animal activity and habitat selection. However, the effects of varying moon stage may differ across taxa. Prey species often reduce activity during highly visible periods of night while predators may increase activity or alter their habitat use. Ocelots (Leopardus pardalis) and bobcats (Lynx rufus), two nocturnal predatory felids that coexist in southern Texas, may also alter their behavior in response to the phase of the moon. To evaluate the effects of lunar phase on habitat selection of ocelots and bobcats, we executed a step selection analysis using high-frequency GPS-telemetry data collected on each species (ocelot, N = 8; bobcat, N = 13) in southern Texas during 2017-2021 and compared step length during new versus full moons. We predicted that ocelots would increase use of dense thornshrub to reduce their visibility during a full moon. However, as bobcats are habitat generalists and are more active during crepuscular periods, we predicted less influence of moon phase on activity. Ocelots did not alter habitat selection in response to lunar phase but moved shorter distances during full moon phases. Conversely, bobcats selected for greater vegetation cover during full moons, possibly to facilitate hunting during brighter periods, but exhibited no difference in movement across lunar phase. We provide, to our knowledge, the first example of habitat selection by predators in relation to lunar phase and show differences across new versus full moons by ocelots and bobcats such that ocelots alter step length but not habitat selection while bobcats altered habitat selection but not step length in response to shifting lunar phase. Further, we suggest the high potential for ocelot-vehicle collisions on darker nights due to increased movement by ocelots and poor visibility for drivers.

Temporal activity patterns of North China leopards and their prey in response to moonlight and habitat factors

The nocturnal activities of predators and prey are influenced by several factors, including physiological adaptations, habitat quality and, we suspect, corresponds to changes in brightness of moonlight according to moon phase. In this study, we used a dataset from 102 camera traps to explore which factors are related to the activity pattern of North China leopards (Panthera pardus japonensis) in Shanxi Tieqiaoshan Provincial Nature Reserve (TPNR), China. We found that nocturnal activities of leopards were irregular during four different lunar phases, and while not strictly lunar philic or lunar phobic, their temporal activity was highest during the brighter moon phases (especially the last quarter) and lower during the new moon phase. On the contrary, roe deer (Capreolus pygargus) exhibited lunar philic activity, while wild boar (Sus scrofa) and tolai hare (Lepus tolai) were evidently lunar phobic, with high and low temporal activity during the full moon, respectively. In terms of temporal overlap, there was positive overlap between leopards and their prey species, including roe deer and tolai hare, while leopard activity did not dip to the same low level of wild boar during the full moon phase. Human activities also more influenced the temporal activity of leopards and wild boar than other species investigated. Generally, our results suggested that besides moonlight risk index (MRI), cloud cover and season have diverse effects on leopard and prey nocturnal activity. Finally, distinct daytime and nighttime habitats were identified, with leopards, wild boar, and tolai hare all using lower elevations at night and higher elevations during the day, while leopards and roe deer were closer to secondary roads during the day than at night.

Analysis of how the spatial and temporal patterns of fire and their bioclimatic and anthropogenic drivers vary across the Amazon rainforest in El Niño and non-El Niño years

In the past two decades, Amazon rainforest countries (Brazil, Bolivia, Colombia, Ecuador, Guyana, Peru and Venezuela) have experienced a substantial increase in fire frequency due to the changes in the patterns of different anthropogenic and climatic drivers. This study examines how both fire dynamics and bioclimatic factors varied based on the season (wet season and dry season) El Niño years across the different countries and ecosystems within the Amazon rainforest. Data from publicly available databases on forest fires (Global Fire Atlas) and bioclimatic, topographic and anthropogenic variables were employed in the analysis. Linear mixed-effect models discovered that year type (El Niño vs. non-El Niño), seasonality (dry vs. wet), land cover and forest strata (in terms of canopy cover and intactness) and their interactions varied across the Amazonian countries (and the different ecosystems) under consideration. A machine learning model, Multivariate Adaptive Regression Spline (MARS), was utilized to determine the relative importance of climatic, topographic, forest structure and human modification variables on fire dynamics across wet and dry seasons, both in El Niño and non-El Niño years. The findings of this study make clear that declining precipitation and increased temperatures have strong impact on fire dynamics (size, duration, expansion and speed) for El Niño years. El Niño years also saw greater fire sizes and speeds as compared to non-El Niño years. Dense and relatively undisturbed forests were found to have the lowest fire activity and increased human impact on a landscape was associated with exacerbated fire dynamics, especially in the El Niño years. Additionally, the presence of grass-dominated ecosystems such as grasslands also acted as a driver of fire in both El Niño and non-El Niño years. Hence, from a conservation perspective, increased interventions during the El Niño periods should be considered.

Landscape Structure of Woody Cover Patches for Endangered Ocelots in Southern Texas

Few ecological studies have explored landscape suitability using the gradient concept of landscape structure for wildlife species. Identification of conditions influencing the landscape ecology of endangered species allows for development of more robust recovery strategies. Our objectives were to (i) identify the range of landscape metrics (i.e., mean patch area; patch and edge densities; percent land cover; shape, aggregation, and largest patch indices) associated with woody vegetation used by ocelots (Leopardus pardalis), and (ii) quantify the potential distribution of suitable woody cover for ocelots across southern Texas. We used the gradient concept of landscape structure and the theory of slack combined with GPS telemetry data from 10 ocelots. Spatial distribution of high suitable woody cover is comprised of large patches, with low shape-index values (1.07–2.25), patch (27.21–72.50 patches/100 ha), and edge (0–191.50 m/ha) densities. High suitability landscape structure for ocelots occurs in 45.27% of woody cover in southern Texas. Our study demonstrates a new approach for measuring landscape suitability for ocelots in southern Texas. The range of landscape values identified that there are more large woody patches containing the spatial structure used by ocelots than previously suspected, which will aid in evaluating recovery and road planning efforts.

A note on investigating co-occurrence patterns and dynamics for many species, with imperfect detection and a log-linear modeling parameterization

Patterns in, and the underlying dynamics of, species co-occurrence is of interest in many ecological applications. Unaccounted for, imperfect detection of the species can lead to misleading inferences about the nature and magnitude of any interaction. A range of different parameterizations have been published that could be used with the same fundamental modeling framework that accounts for imperfect detection, although each parameterization has different advantages and disadvantages.We propose a parameterization based on log-linear modeling that does not require a species hierarchy to be defined (in terms of dominance) and enables a numerically robust approach for estimating covariate effects.Conceptually, the parameterization is equivalent to using the presence of species in the current, or a previous, time period as predictor variables for the current occurrence of other species. This leads to natural, "symmetric," interpretations of parameter estimates.The parameterization can be applied to many species, in either a maximum likelihood or Bayesian estimation framework. We illustrate the method using camera-trapping data collected on three mesocarnivore species in South Texas.

Small cats in big trouble? Diet, activity, and habitat use of jungle cats and leopard cats in threatened dry deciduous forests, Cambodia

Dry deciduous dipterocarp forests (DDF) cover about 15%-20% of Southeast Asia and are the most threatened forest type in the region. The jungle cat (Felis chaus) is a DDF specialist that occurs only in small isolated populations in Southeast Asia. Despite being one of the rarest felids in the region, almost nothing is known about its ecology. We investigated the ecology of jungle cats and their resource partitioning with the more common leopard cats (Prionailurus bengalensis) in a DDF-dominated landscape in Srepok Wildlife Sanctuary, Cambodia. We used camera-trap data collected from 2009 to 2019 and DNA-confirmed scats to determine the temporal, dietary and spatial overlap between jungle cats and leopard cats. The diet of jungle cats was relatively diverse and consisted of murids (56% biomass consumed), sciurids (15%), hares (Lepus peguensis; 12%), birds (8%), and reptiles (8%), whereas leopard cats had a narrower niche breadth and a diet dominated by smaller prey, primarily murids (73%). Nonetheless, dietary overlap was high because both felid species consumed predominantly small rodents. Both species were primarily nocturnal and had high temporal overlap. Two-species occupancy modelling suggested jungle cats were restricted to DDF and had low occupancy, whereas leopard cats had higher occupancy and were habitat generalists. Our study confirmed that jungle cats are DDF specialists that likely persist in low numbers due to the harsh conditions of the dry season in this habitat, including annual fires and substantial decreases in small vertebrate prey. The lower occupancy and more diverse diet of jungle cats, together with the broader habitat use of leopard cats, likely facilitated the coexistence of these species. The low occupancy of jungle cats in DDF suggests that protection of large areas of DDF will be required for the long-term conservation of this rare felid in Southeast Asia.

Polyrhythmic foraging and competitive coexistence

The current ecological understanding still does not fully explain how biodiversity is maintained. One strategy to address this issue is to contrast theoretical prediction with real competitive communities where diverse species share limited resources. I present, in this study, a new competitive coexistence theory-diversity of biological rhythms. I show that diversity in activity cycles plays a key role in coexistence of competing species, using a two predator-one prey system with diel, monthly, and annual cycles for predator foraging. Competitive exclusion always occurs without activity cycles. Activity cycles do, however, allow for coexistence. Furthermore, each activity cycle plays a different role in coexistence, and coupling of activity cycles can synergistically broaden the coexistence region. Thus, with all activity cycles, the coexistence region is maximal. The present results suggest that polyrhythmic changes in biological activity in response to the earth's rotation and revolution are key to competitive coexistence. Also, temporal niche shifts caused by environmental changes can easily eliminate competitive coexistence.

Spatial structure of woody cover affects habitat use patterns of ocelots in Texas

About 80% of the known breeding population of ocelots (Leopardus pardalis) in the USA occurs exclusively on private ranches in northern Willacy and Kenedy counties in South Texas. These private ranches support several large contiguous undisturbed patches of thornscrub, which is preferred by ocelots. Past studies have indicated ocelots in South Texas select for woody patches that contain extremely dense thornscrub (i.e., 95% canopy cover and 85% vertical cover) and require large patches of woody cover to survive. Landscape metrics have been used to explain ocelot habitat use in fragmented areas, but their application in less-fragmented rangelands is lacking. From 2011 to 2018, we used camera traps on the East Foundation’s El Sauz Ranch to assess seasonal habitat use of ocelots relative to landscape structure, configuration, and complexity and other site-level factors in South Texas. Seasonal habitat use and detection were positively influenced by larger mean patch area and lower landscape shape index values. We also observed ocelots were less likely to be detected during periods of drought and exhibited a seasonal trend in detection. Ocelots used woody patches that were larger and more regularly shaped, indicating a preference for areas with a lower degree of fragmentation across the study area. As patches become larger, they will coalesce over time and form larger woody aggregates, which will promote ocelot habitat use. Brush management needs to be strategic as patch area and shape index are a limiting factor to promote ocelot habitat use on working rangelands in South Texas. These results demonstrate the ability to use landscape metrics to discern the effects of spatial structure of vegetation communities relative to ocelot occupancy parameters.