Daily Activity Patterns Research Articles

Microhabitat use, daily activity pattern, and diet of Liolaemus etheridgei Laurent, 1998 (Reptilia: Liolaemidae) in the Andean Polylepis forests of Arequipa, Peru.

This study describes the microhabitat use, daily activity pattern, and diet of Liolaemus etheridgei Laurent, 1998 in the El Simbral and Tuctumpaya Polylepis forests in Arequipa, Peru. El Simbral is a fragmented forest, whereas Tuctumpaya is unfragmented. Our results reveal that L. etheridgei shows no positive selection for any of the microhabitats we identified in Polylepis forests; on the contrary, it selects negatively against Polylepis trees and nonthorny bushes. The daily activity patterns indicate a bimodal pattern with peaks at 9:00–10:59 and 13:00–13:59 h. The diet of L. etheridgei consists mainly of plant material, and the most important animal prey category is Lygaeidae: Hemiptera, which is selected for positively. In particular, microhabitat selection varied for nonthorny bushes, which were selected negatively in the Tuctumpaya population but neither positively nor negatively in the El Simbral population. According to the proportions of plant material found, the L. etheridgei from El Simbral were found to be omnivorous, whereas the Tuctumpaya population was herbivorous. However, the percentage of plant material consumed in the El Simbral population was close to the critical value for herbivory–omnivory. We conclude that the three ecological aspects of L. etheridgei studied here are virtually identical in El Simbral and Tuctumpaya; therefore, this species is not affected significantly by the current fragmentation of forest.

Patterns of Daily Physical Movement, Chronic Inflammation, and Frailty Incidence.

Low physical activity is a criterion of phenotypic frailty defined as an increased state of vulnerability to adverse health outcomes. Whether disengagement from daily all-purpose physical activity is prospectively associated with frailty and possibly modified by chronic inflammation-a pathway often underlying frailty-remains unexplored. Using the Study to Understand Fall Reduction and Vitamin D in You data from 477 robust/prefrail adults (mean age = 76 ± 5 yr; 42% women), we examined whether accelerometer patterns (activity counts per day, active minutes per day, and activity fragmentation [broken accumulation]) were associated with incident frailty using Cox proportional hazard regression. Baseline interactions between each accelerometer metric and markers of inflammation that include interleukin-6, C-reactive protein, and tumor necrosis factor-alpha receptor 1 were also examined. Over an average of 1.3 yr, 42 participants (9%) developed frailty. In Cox regression models adjusted for demographics, medical conditions, and device wear days, every 30 min·d -1 higher baseline active time, 100,000 more activity counts per day, and 1% lower activity fragmentation was associated with a 16% ( P = 0.003), 13% ( P = 0.001), and 8% ( P < 0.001) lower risk of frailty, respectively. No interactions between accelerometer metrics and baseline interleukin-6, C-reactive protein, or tumor necrosis factor-alpha receptor 1 were detected (interaction P > 0.06 for all). Among older adults who are either robust or prefrail, constricted patterns of daily physical activity (i.e., lower total activity minutes and counts, and higher activity fragmentation) were prospectively associated with higher risk of frailty but not modified by frailty-related chronic inflammation. Additional studies, particularly trials, are needed to understand if this association is causal.

Daily patterns of physical activity, sedentary behavior, and prevalent and incident depression-The Maastricht Study.

This study aims to compare the accelerometer-measured daily patterns of PA and sedentary behavior among participants with and without prevalent/incident depressive symptoms. We used data from 5582 individuals in The Maastricht Study (59.9 ± 8.6 years, 50.3% women). Daily patterns of sedentary time, light-intensity physical activity (LiPA), moderate-to-vigorous physical activity (MVPA), and sit-to-stand transitions were objectively measured at baseline with the activPAL3 activity monitor. Depressive symptoms were assessed using the 9-item Patient Health Questionnaire, both at baseline and annually (median follow-up: 5.1 years). General linear models were used to compare patterns of physical activity and sedentary behavior between those with and without prevalent/incident depressive symptoms. Participants with prevalent depressive symptoms had significantly more sedentary time (18.6min/day) and lower LiPA (26.8min/day) and MVPA (4.8min/day) than participants without depressive symptoms. Considering the daily patterns, participants with prevalent depressive symptoms had significantly more sedentary time early in the afternoon (12:00-18:00), early evening (18:00-21:00), and during the night (00:00-03:00), less time in LiPA in all periods between 09:00-21.00 and less MVPA in the morning (09:00:12:00), early afternoon (12:00-15:00), and evening (18:00-21:00), than those without. Similar differences in activity and sedentary behavior patterns between those and without incident depressive symptoms were observed albeit the differences were smaller. Overall, we did not find specific time slots particularly associated with both prevalent and incident depressive symptoms. These findings may indicate that less sedentary time and more intense PA can be important targets for the prevention of depression irrespective of the timing of the day.

Activity patterns and reproductive behavior of the Critically Endangered Bermuda skink (Plestiodon longirostris).

The study of rare or cryptic species in zoos can provide insights into natural history and behavior that would be difficult to obtain in the field. Such information can then be used to refine population assessment protocols and conservation management. The Bermuda skink (Plestiodon longirostris) is an endemic Critically Endangered lizard. Chester Zoo's successful conservation breeding program is working to safeguard, increase and reinforce skink populations in the wild. A key aim of this program is to develop our understanding of the behavior of this species. In this study, using 24 hvideo recordings, we examined the daily activity patterns, basking behavior and food preferences of four pairs of Bermuda skinks. The skinks displayed a bimodal pattern of activity and basking, which may have evolved to avoid the strength of the midday sun in exposed habitats in Bermuda. Captive Bermuda skinks appear to prefer a fruit-based diet to orthopteran prey. We also documented their reproductive behavior and compared it against two closely related species. Although there were many similarities between the courtship and mating behaviors of the three species, there was a significantly shorter period of cloacal contact in the Bermuda skink. Oophagia was also documented for the first time in this species. This knowledge has enabled the evaluation of the current ex-situ management practices of this species, filled gaps in knowledge that would be challenging to obtain in the field, and enabled the enhancement of both animal husbandry and reproductive success for the conservation breeding program.

Daily Activity Pattern of Geladas (Theropithecus gelada, Ruppell 1835) in Kotu Forest, Northern Ethiopia.

Gelada (Theropithecus gelada) is one of the endemic primates of Ethiopia. The ecology of meta populations of geladas outside protected areas is less studied, and their population status is uncertain. As a result, we conducted a study to investigate the daily activity pattern of gelada in Kotu forest and associated grasslands in northern Ethiopia from August 2017 to February 2018 covering both wet and dry seasons. The instantaneous scan sampling method was employed to collect behavioral data. The activity pattern of three selected focal groups of geladas was studied, and predominant behavioral activities were scanned in 15 minutes intervals from dawn 7:00 h to dusk at 18:00 h. Feeding comprised 61.65% of the total scan, followed by moving 18.49%. Feeding activity was more frequent during the dry season (about 65%) than in the wet season (58.20%). On the other hand, moving activity was more frequent during the dry season (about 22%) than in the wet season (about 14%). The daily activity pattern of gelada showed a feeding peak early in the morning and in the late afternoon. The time allocated by geladas for feeding and moving in the study area is higher than other activities. Therefore, there is a need for further in-depth research on diet availability and quality to justify why geladas allocate more time for feeding and moving nexus for conservation interventions.

Assessing the impact of forest structure disturbances on the arboreal movement and energetics of orangutans—An agent-based modeling approach

Agent-based models have been developed and widely employed to assess the impact of disturbances or conservation management on animal habitat use, population development, and viability. However, the direct impacts of canopy disturbance on the arboreal movement of individual primates have been less studied. Such impacts could shed light on the cascading effects of disturbances on animal health and fitness. Orangutans are an arboreal primate that commonly encounters habitat quality deterioration due to land-use changes and related disturbances such as forest fires. Forest disturbance may, therefore, create a complex stress scenario threatening orangutan populations. Due to forest disturbances, orangutans may adapt to employ more terrestrial, as opposed to arboreal, movements potentially prolonging the search for fruiting and nesting trees. In turn, this may lead to changes in daily activity patterns (i.e., time spent traveling, feeding, and resting) and available energy budget, potentially decreasing the orangutan's fitness. We developed the agent-based simulation model BORNEO (arBOReal aNimal movEment mOdel), which explicitly describes both orangutans' arboreal and terrestrial movement in a forest habitat, depending on distances between trees and canopy structures. Orangutans in the model perform activities with a motivation to balance energy intake and expenditure through locomotion. We tested the model using forest inventory data obtained in Sebangau National Park, Central Kalimantan, Indonesia. This allowed us to construct virtual forests with real characteristics including tree connectivity, thus creating the potential to expand the environmental settings for simulation experiments. In order to parameterize the energy related processes of the orangutans described in the model, we applied a computationally intensive evolutionary algorithm and evaluated the simulation results against observed behavioral patterns of orangutans. Both the simulated variability and proportion of activity budgets including feeding, resting, and traveling time for female and male orangutans confirmed the suitability of the model for its purpose. We used the calibrated model to compare the activity patterns and energy budgets of orangutans in both natural and disturbed forests . The results confirm field observations that orangutans in the disturbed forest are more likely to experience deficit energy balance due to traveling to the detriment of feeding time. Such imbalance is more pronounced in males than in females. The finding of a threshold of forest disturbances that affects a significant change in activity and energy budgets suggests potential threats to the orangutan population. Our study introduces the first agent-based model describing the arboreal movement of primates that can serve as a tool to investigate the direct impact of forest changes and disturbances on the behavior of species such as orangutans. Moreover, it demonstrates the suitability of high-performance computing to optimize the calibration of complex agent-based models describing animal behavior at a fine spatio-temporal scale (1-m and 1-s granularity).

A before−after assessment of the response of mammals to tourism in a Brazilian national park

AbstractWorldwide, nature-based tourism is becoming more popular and important economically. However, there is still debate regarding its impact on wildlife in protected areas. We conducted a quasi-experimental study to investigate the effects of tourism on the mammal community of Cavernas do Peruaçu National Park, a priority area for conservation in Brazil. We used camera traps to survey tourist and non-tourist trails during 2011–2017, encompassing periods before and after tourism started in the Park. We used four metrics for assessment: species richness, probability of using trails, activity levels and daily activity patterns. After tourism began in the Park there was no significant change in species richness and the probability of using tourist trails either increased or remained stable for five of the six species assessed. The rock cavyKerodon rupestriswas the only species to be displaced from tourist areas and to show reduced overall activity on tourist trails after tourism began. The ocelotLeopardus pardalisshowed reduced diurnal activity on tourist trails, an indication of temporal adjustment. Overall, our results show that the initial years of visitation at the Park had limited negative impacts on the target mammal species, supporting the possibility of accommodating tourism activity and effective conservation of wildlife in the region. However, it is essential to continue monitoring in the Park because of the expected growth in tourism and potential time lags in responses of species.

Bison and elk spatiotemporal interactions in Elk Island National Park

Elk Island National Park (EINP) is a fenced park in the Beaver Hills UNESCO Biosphere Reserve of central Alberta where aspen parkland is being conserved. This area maintains high densities of native ungulates including elk (Cervus elaphus), bison (Bison bison bison, B. bison athabascae), moose (Alces alces), white-tailed deer (Odocoileus virginianus), and mule deer (O. hemionus). Our objective was to evaluate spatiotemporal overlap and interspecific interactions between bison and elk in EINP using camera traps. Bison and elk have overlapping habitat use and diet and are the primary focus of ungulate management in EINP. We examined distributions of both species in relation to season, landscape characteristics, anthropogenic features, and heterospecifics using generalized linear models (GLMs). We then examined seasonal daily activity patterns of bison and elk and calculated the degree of overlap. The spatial analysis revealed that bison counts were positively associated with higher proportions of open habitats across seasons and in areas farther from water in summer and fall but had no associations with distance to water during winter. Bison removal year (years during which bison removals were conducted by Parks Canada) was a significant predictor variable for bison counts in winter when the bison roundup takes place. Elk avoided areas with high linear feature density across seasons. During fall and winter, we observed higher elk counts associated with bison presence. Temporal activity patterns revealed that elk were crepuscular in all three seasons, but bison activity patterns varied with diurnal activity being more common in the summer, crepuscular activity in winter, and intermediate activity patterns during fall. Coefficients of overlap between elk and bison were high in all three seasons with the greatest difference in daily activity patterns in summer and the highest overlap in winter when both species showed strong crepuscular activity. Despite the fenced perimeter in EINP resulting in high ungulate densities, limited dispersal, and low predation, our data show patterns of habitat use and interactions between bison and elk that were similar to those in other systems. Spatiotemporal partitioning does not appear necessary for coexistence of bison and elk in the aspen parkland.

Temporal overlap of human and apex predator activity on wildlife trails and forest roads

The daily activity patterns of animals are modulated by external factors such as habitat selection, temporal niche selection, prey availability and predation risk. Furthermore, different species show a variety of responses to human disturbance; therefore, to understand the effects of human activities on wildlife, it is crucial to consider the disturbance characteristics (e.g. type, frequency, timing and location of human activity). Our objective was to evaluate whether vehicles on forest roads altered the daily temporal activity patterns of three apex predators; Eurasian lynx (Lynx lynx), the grey wolf (Canis lupus) and brown bear (Ursus arctos), using an extensive camera trap data set collected across a gradient of forest roads and wildlife trails in the Croatian part of the Dinaric mountains. We expected a low temporal overlap between humans and apex predators but predicted this even lower at sites where vehicles are present. Consistent with our expectations, the general overlap in temporal activity of all three apex predators and humans was low, the former being primarily active at night/dawn/dusk hours and the latter during daylight hours. In contrast, our results showed similarity in the temporal activity of all three predators on wildlife trails and forest roads where human activity was more frequent and diverse.

Reef effect of offshore structures on the occurrence and foraging activity of harbour porpoises

With increasing numbers of offshore structures being installed and decommissioned, a better understanding of their effect on marine predators is timely. There is some evidence that oil and gas platforms may attract marine mammals, acting as artificial reefs. However, it is unclear whether different man-made structure designs have similar effects or whether artificial structures modify the diel patterns of occurrence and foraging of marine mammals. Here, we used passive acoustics to investigate the occurrence and foraging activity of harbour porpoises (Phocoena phocoena) around four artificial structures of different age and complexity. We deployed an array of echolocation click detectors (CPODs) in 2021, along a gradient of distances to these structures and assessed the extent to which porpoises were attracted to them and their effect on porpoises’ diel patterns of occurrence and foraging activity. The probability of porpoise occurrence and foraging activity decreased with distance from offshore structures. A significant increase in porpoise occurrence and foraging was detected during night-time compared to daytime around all four offshore structures (&amp;lt; 200 m). Comparing pre- and post-installation porpoise detections, the daily patterns of occurrence and foraging activity shifted from a weak diel pattern before the structure was installed, to a strong nocturnal pattern when the structure was present. These findings provide evidence that marine mammals are attracted to man-made structures and that porpoises modify their diel patterns of occurrence and foraging activity around them. This research suggests that offshore structures play an important role as foraging areas for some marine mammals and provides key information for decommissioning considerations and the planning of decommissioning activities.

Phenological research based on natural history collections: Practical guidelines and a lepidopteran case study

Abstract Natural history collections (NHCs) have been indispensable to understanding longer‐term trends of the timing of seasonal events. Massive‐scale digitization of specimens promises to further enable phenological research, especially the ability to move towards a deeper understanding of drivers of change and how trait–environment interactions shape phenological sensitivity. Despite the promise of NHCs to answer fundamental phenology questions, the use of these data resources presents unique and often overlooked challenges requiring specialized workflow steps, such as assembling multisource data, accounting for date imprecision and making decisions about trade‐offs between data density and spatial resolution. We provide a set of key best practice recommendations and showcase these via a case study that utilizes NHC data to test hypotheses about spatiotemporal trends in adult Lepidoptera (i.e. butterflies and moths) flight timing across North America. Our case study is a worked example of these best practices, helping practitioners recognize and overcome potential pitfalls at each step, from data acquisition and cleaning, to delineating spatial units and proper estimation of phenological metrics and associated uncertainty, to building appropriate models. We confirm and extend the critical importance of voltinism and diapause strategy, but less‐so daily activity patterns, for predicting Lepidoptera phenology spatiotemporal trends. Our case study also showcases the unique power of NHC data to test existing hypotheses and generate new insights about temporal phenological trends. Specifically, migratory species and species that enter diapause as adults are advancing the start of flight periods in more recent years, even after accounting for climate context. These results highlight the physiological and adaptive differences between species with different overwintering strategies. We close by noting the value of partnerships between data scientists, museum experts and ecological modellers to fully harness the power of digital data resources to address pressing global change challenges. These partnerships can extend approaches for integrating multiple data types to fully unlock our understanding of the tempo, mode, drivers and outcomes of phenological changes at greater spatial, temporal and taxonomic scales. Read the free Plain Language Summary for this article on the Journal blog.

No relationship between chronotype and timing of breeding when variation in daily activity patterns across the breeding season is taken into account.

There is increasing evidence that individuals are consistent in the timing of their daily activities, and that individual variation in temporal behavior is related to the timing of reproduction. However, it remains unclear whether observed patterns relate to the timing of the onset of activity or whether an early onset of activity extends the time that is available for foraging. This may then again facilitate reproduction. Furthermore, the timing of activity onset and offset may vary across the breeding season, which may complicate studying the above‐mentioned relationships. Here, we examined in a wild population of great tits (Parus major) whether an early clutch initiation date may be related to an early onset of activity and/or to longer active daylengths. We also investigated how these parameters are affected by the date of measurement. To test these hypotheses, we measured emergence and entry time from/into the nest box as proxies for activity onset and offset in females during the egg laying phase. We then determined active daylength. Both emergence time and active daylength were related to clutch initiation date. However, a more detailed analysis showed that the timing of activities with respect to sunrise and sunset varied throughout the breeding season both within and among individuals. The observed positive relationships are hence potentially statistical artifacts. After methodologically correcting for this date effect, by using data from the pre‐egg laying phase, where all individuals were measured on the same days, neither of the relationships remained significant. Taking methodological pitfalls and temporal variation into account may hence be crucial for understanding the significance of chronotypes.

Activity patterns of Asiatic black bear (Ursus thibetanus) in the moist temperate forests of Machiara National Park, Azad Jammu and Kashmir, Pakistan.

The Asiatic black bear (Ursus thibetanus) is an environmental indicator species whose activity patterns may be highly impacted by habitat changes. We monitored the monthly and daily activity patterns of black bears in the moist temperate forests of Machiara National Park. We used infrared camera traps and local ecological knowledge for data collection from April 2019 to April 2021. Camera traps recorded 109 [inside forest = 107, outside forest (near crop fields and human settlements) = 2] independent registrations (IR) in 5541 (692.63 ± 36.72, mean ± SD) camera days. We found (i) spring and autumn to be the lowest activity seasons for black bears inside the forest. (ii) The highest activity was recorded in summer, with a peak in August followed closely by July. (iii) The activity level sharply declined after August and halted from December to March, indicative of the bears' hibernation period. Local knowledge revealed that (i) bears remained active from May to November and hibernated the rest of the period. (ii) Bear activity was at its peak inside the forest in summer and outside the forest in autumn when bears sought to raid the widely cultivated maize crop (Zea mays) planted along forest edges. This increased activity outside of the forest is likely driven by decreased food availability inside the forest area and maize crop being a preferred anthropogenic food type for bears. Based on the daily activity pattern, bears exhibited cathemeral behavior (i.e., active throughout the day) with maximum overlap between camera trap and local ecological knowledge data. Human activity may be impacting the daily activity patterns of bears via disturbance and interference. The data collected in this study can help mitigate conflicts between humans and black bears and consequently assist in future conservation of black bears in the area.

Truck industry classification from anonymous mobile sensor data using machine learning

Freight demand forecasting models used by federal, state, and local transportation agencies to predict future freight flows are often based on economic forecasts of industry growth and/or commodity production/consumption rates which are then used to estimate expected freight movement, e.g., truck volumes. Unfortunately, there is a lack of data connecting industry served and commodity carried to freight movements which limits the accuracy and usability of such models. While the private sector collects robust data on freight movements including commodity carried, when shared with the public sector, this data is anonymized to protect privacy. Thus, there is a critical need to re-identify industry served and commodity carried from anonymous freight movement data in ways that maintain privacy standards. To address this research gap, we developed a classification model using data mining and machine learning methods to predict industry served by a truck from daily activity patterns of trip and stop sequences extracted from truck Global Positioning System (GPS) data. A Weighted Random Forest (WRF) supervised machine learning model is used to predict five industry groups: farm products, mining materials, chemicals, manufactured goods, and miscellaneous mixed goods. The WRF model achieves 88% prediction accuracy and explicitly accounts for class imbalance. The model does not reveal fleet, driver, company, etc. and thus, we are able to provide necessary insight into the relationship between truck movement and economic (industry) forecasts without violating data privacy standards. Ultimately, our model allows large streams of truck movement data to be leveraged for freight travel demand forecasting.

Temporal and spatial segregation among mammal predators and their prey

Time and space are niche dimensions that allow a local coexistence of predators and their prey. Daily activity patterns are a crucial component of mammalian ecology and behavior, being temporal avoidance often the most important mechanism of coexistence among species. Animal’s daily activity patterns (temporal specialization) can be classified in diurnal, nocturnal, crepuscular or cathemeral. Temporal overlap alone does not define the vulnerability of the prey or the preference of the predator, since there must also be spatial segregation, which can alleviate possible hostile interactions among the animals. In this study, we test if there are any significant differences among the daily activity patterns of predators and prey. We used the camera-trapping data to test if the predator’s species have less occurrence than expected by chance on the trails. The study area is the Parque Nacional da Serra dos Órgãos (PARNASO). C-score is used to determine the spatial segregation and the exact test to determine the temporal segregation between predators and prey. Our results suggest spatial segregation among predators and prey in PARNASO. Also, the exact test showed that predators have cathemeral activity while prey are mainly nocturnal, as expected, probably to avoid predators. Despite its importance, the theory of how predation affects species differences and diversity is much less developed than the competition theory, which shows that more studies like this one need to be done

Colony specificity and starvation-driven changes in activity patterns of the red ant Myrmica rubra.

Although the activity levels of insect societies are assumed to contribute to their ergonomic efficiency, most studies of the temporal organization of ant colony activity have focused on only a few species. Little is known about the variation in activity patterns across colonies and species, and in different environmental contexts. In this study, the activity patterns of colonies of the red ant Myrmica rubra were characterized over 15 consecutive days. The main goals were to evaluate the colony specificity of the activity patterns and the impact of food deprivation on these patterns. We found that the average activity level varied across colonies and remained consistent over 1 week, providing evidence that the activity level is a colony-specific life trait. Furthermore, all colonies applied an energy-saving strategy, decreasing their average levels of activity inside the nest, when starved. Starvation induced no consistent change in the activity level outside of the nest. An analysis of activity time series revealed activity bursts, with nestmates being active (or inactive) together, the amplitudes of which reflected the ants' degree of synchronization. Food deprivation increased the amplitude and number of these activity bursts. Finally, wavelet analyses of daily activity patterns revealed no evidence of any periodicity of activity bouts occurring inside or outside of the nest. This study showed that M. rubra ant colonies are characterized by specific activity levels that decrease in response to starvation with the adoption of an energy-saving strategy. In addition, our results help to understand the functional value associated with synchronized and/or periodic fluctuation in activity, which has been debated for years.

Changes in roe deer (Capreolus capreolus) daily activity patterns in Warsaw during the COVID-19 pandemic

The COVID-19 pandemic, which modified levels of visitor attendance to urban forests and green spaces, provided a unique opportunity to measure the effects of human presence on wild animals and their activity. The aim of our study was to describe how the daily activity pattern of roe deer (i.e. proportion of day- and night-time observations) changed in response to visitor frequency in urban forests of Warsaw in four periods of 2020 (the year the COVID-19 pandemic was announced) compared to the same periods in 2019 (control year). In total, 662 observations of roe deer were recorded by camera traps in both years. The frequency of roe deer observations in urban forests of Warsaw in day- and night-time did not differ between March 2019 and 2020 (period before lockdown, no changes in the number of visitors). Next, between 1 and 20 April 2020 (national lockdown; urban forests were closed for public) the activity of roe deer increased during the day-time. Between 21 April and 30 June in both 2019 and 2020 the frequency of roe deer observations in day and night-time did not differ (green areas were reopened, remote learning). Finally, in July–August 2020 (summer holidays, tourist traffic in forests elevated all day round) the activity of roe deer visibly increased during the night-time. Our research shows how their activity rapidly shifted toward day-time when forests were closed for visitors, and toward night-time when the number of visitors was higher in urban forests after the lockdown. To summarize, roe deer in urban forests showed high ecological plasticity to human presence and rapidly adjusted to changes in the number of visitors in urban forest during the COVID-19 pandemic.

Electronic recording of lifetime locomotory activity patterns of adult medflies.

Age-specific and diurnal patterns of locomotory activity, can be considered as biomarkers of aging in model organisms and vary across the lifetime of individuals. Τhe Mediterranean fruit fly (medfly), Ceratitis capitata, is a commonly used model-species in studies regarding demography and aging. In the present study, we introduce a modification of the automated locomotory activity electronic device LAM25system (Locomotory Activity Monitor)-Trikinetics, commonly used in short time studies, to record the daily locomotory activity patterns of adult medflies throughout the life. Additionally, fecundity rates and survival of adult medflies were recorded. Male and female medflies were kept in the system tubes and had access to an agar-based gel diet, which provided water and nutrients. The locomotory activity was recorded at every minute by three monitors in the electronic device. The locomotory activity of females was higher than that of males across the different ages. For both sexes locomotory rates were high during the first 20 days of the adult life and decreased in older ages. The activity of males was high in the morning and late afternoon hours, while that of females was constantly high throughout the photophase. Negligible locomotory activity was recorded for both sexes during the nighttime. Males outlived females. Fecundity of females was higher in younger ages. Our results support the adoption of LAM25system in studies addressing aging of insects using medfly as a model organism.

Comparative analysis of temperature preference behavior and effects of temperature on daily behavior in 11 Drosophila species

Temperature is one of the most critical environmental factors that influence various biological processes. Species distributed in different temperature regions are considered to have different optimal temperatures for daily life activities. However, how organisms have acquired various features to cope with particular temperature environments remains to be elucidated. In this study, we have systematically analyzed the temperature preference behavior and effects of temperatures on daily locomotor activity and sleep using 11 Drosophila species. We also investigated the function of antennae in the temperature preference behavior of these species. We found that, (1) an optimal temperature for daily locomotor activity and sleep of each species approximately matches with temperatures it frequently encounters in its habitat, (2) effects of temperature on locomotor activity and sleep are diverse among species, but each species maintains its daily activity and sleep pattern even at different temperatures, and (3) each species has a unique temperature preference behavior, and the contribution of antennae to this behavior is diverse among species. These results suggest that Drosophila species inhabiting different climatic environments have acquired species-specific temperature response systems according to their life strategies. This study provides fundamental information for understanding the mechanisms underlying their temperature adaptation and lifestyle diversification.

SNAPSHOT USA 2020: A second coordinated national camera trap survey of the United States during the COVID-19 pandemic.

Managing wildlife populations in the face of global change requires regular data on the abundance and distribution of wild animals, but acquiring these over appropriate spatial scales in a sustainable way has proven challenging. Here we present the data from Snapshot USA 2020, a second annual national mammal survey of the USA. This project involved 152 scientists setting camera traps in a standardized protocol at 1485 locations across 103 arrays in 43 states for a total of 52,710 trap‐nights of survey effort. Most (58) of these arrays were also sampled during the same months (September and October) in 2019, providing a direct comparison of animal populations in 2 years that includes data from both during and before the COVID‐19 pandemic. All data were managed by the eMammal system, with all species identifications checked by at least two reviewers. In total, we recorded 117,415 detections of 78 species of wild mammals, 9236 detections of at least 43 species of birds, 15,851 detections of six domestic animals and 23,825 detections of humans or their vehicles. Spatial differences across arrays explained more variation in the relative abundance than temporal variation across years for all 38 species modeled, although there are examples of significant site‐level differences among years for many species. Temporal results show how species allocate their time and can be used to study species interactions, including between humans and wildlife. These data provide a snapshot of the mammal community of the USA for 2020 and will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, and the impacts of species interactions on daily activity patterns. There are no copyright restrictions, and please cite this paper when using these data, or a subset of these data, for publication.