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Campylobacter and pathogenic Escherichia coliillnesses have been attributed to the consumption of fresh produce. The leafy green, kale, is increasingly consumed raw. In comparison to other leafy greens, kale has a longer shelf-life. Due to the extended shelf-life of kale, it is warranted to examine the survival of pathogenic Campylobacter jejuni and E. coli O157:H7 inoculated on the surface of kale stored in a controlled environment at 4 ± 1.4°C, and average humidity of 95 ± 1.9% over a 23-day period. At predetermined time points (days 0, 1, 2, 3, 5, 7, 9, 11, 13, 15, 17, 19, and 21), inoculated kale was destructively sampled and the surviving bacteria determined by serial dilution and plating onto Tryptic soy agar, Charcoal cefoperozone deoxycholate agar, and Eosin methylene blue for total aerobic bacteria, C. jejuni, and E. coli O157:H7, respectively. Enrichment and PCR were used for detection when pathogens were not detected using serial dilution and plating. Aerobic heterotrophic bacteria increased over the 23-day period, in contrast, significant declines in the inoculated pathogens were observed. Inoculated E. coli O157:H7 survived longer on kale (up to 19 d); in comparison, C. jejuni was undetectable by day 13 using enrichment and PCR or plating. In conclusion, C. jejuni and E. coli O157:H7 declined on fresh kale over time when held at refrigerated temperatures but were still detected during the majority of the time when the kale would likely still be considered edible by consumers.

Resource partitioning promotes coexistence among guild members, and carnivores reduce interference competition through behavioral mechanisms that promote spatio-temporal separation. We analyzed sympatric lion and spotted hyena movements and activity patterns to ascertain the mechanisms facilitating their coexistence within semi-arid and wetland ecosystems. We identified recurrent high-use (revisitation) and extended stay (duration) areas within home ranges, as well as correlated movement-derived measures of inter- and intraspecific interactions with environmental variables. Spatial overlaps among lions and hyenas expanded during the wet season, and occurred at edges of home ranges, around water-points, along pathways between patches of high-use areas. Lions shared more of their home ranges with spotted hyenas in arid ecosystems, but shared more of their ranges with conspecifics in mesic environments. Despite shared space use, we found evidence for subtle temporal differences in the nocturnal movement and activity patterns between the two predators, suggesting a fine localized-scale avoidance strategy. Revisitation frequency and duration within home ranges were influenced by interspecific interactions, after land cover categories and diel cycles. Intraspecific interactions were also important for lions and, important for hyenas were moon illumination and ungulates attracted to former anthrax carcass sites in Etosha, with distance to water in Chobe/Linyanti. Recursion and duration according to locales of competitor probabilities were similar among female lions and both sexes of hyenas, but different for male lions. Our results suggest that lions and spotted hyenas mediate the potential for interference competition through subtle differences in temporal activity, fine-scale habitat use differentiation, and localized reactive-avoidance behaviors. These findings enhance our understanding of the potential effects of interspecific interactions among large carnivore space-u

Resource partitioning promotes coexistence among guild members, and carnivores reduce interference competition through behavioral mechanisms that promote spatio-temporal separation. We analyzed sympatric lion and spotted hyena movements and activity patterns to ascertain the mechanisms facilitating their coexistence within semi-arid and wetland ecosystems. We identified recurrent high-use (revisitation) and extended stay (duration) areas within home ranges, as well as correlated movement-derived measures of inter- and intraspecific interactions with environmental variables. Spatial overlaps among lions and hyenas expanded during the wet season, and occurred at edges of home ranges, around water-points, along pathways between patches of high-use areas. Lions shared more of their home ranges with spotted hyenas in arid ecosystems, but shared more of their ranges with conspecifics in mesic environments. Despite shared space use, we found evidence for subtle temporal differences in the nocturnal movement and activity patterns between the two predators, suggesting a fine localized-scale avoidance strategy. Revisitation frequency and duration within home ranges were influenced by interspecific interactions, after land cover categories and diel cycles. Intraspecific interactions were also important for lions and, important for hyenas were moon illumination and ungulates attracted to former anthrax carcass sites in Etosha, with distance to water in Chobe/Linyanti. Recursion and duration according to locales of competitor probabilities were similar among female lions and both sexes of hyenas, but different for male lions. Our results suggest that lions and spotted hyenas mediate the potential for interference competition through subtle differences in temporal activity, fine-scale habitat use differentiation, and localized reactive-avoidance behaviors. These findings enhance our understanding of the potential effects of interspecific interactions among large carnivore space-u

Introduction: Campylobacter spp. infections are responsible for significant diarrheal disease burden across the globe, with prevalence thought to be increasing. Although wild avian species have been studied as reservoirs of Campylobacter spp., our understanding of the role of wild mammalian species in disease transmission and persistence is limited. Host factors influencing infection dynamics in wild mammals have been neglected, particularly life traits, and the role of these factors in zoonotic spillover risk is largely unknown. Methods: Here, we conducted a systematic literature review, identifying mammalian species that had been tested for Campylobacter spp. infections (molecular and culture based). We used logistic regression to evaluate the relationship between the detection of Campylobacter spp. in feces and host life traits (urban association, trophic level, and sociality). Results: Our analysis suggest that C. jejuni transmission is associated with urban living and trophic level. The probability of carriage was highest in urban-associated species (p = 0.02793) and the most informative model included trophic level. In contrast, C. coli carriage appears to be strongly influenced by sociality (p = 0.0113) with trophic level still being important. Detection of Campylobacter organisms at the genus level, however, was only associated with trophic level (p = 0.0156), highlighting the importance of this trait in exposure dynamics across host and Campylobacter pathogen systems. Discussion: While many challenges remain in the detection and characterization of Camploybacter spp., these results suggest that host life traits may have important influence on pathogen exposure and transmission dynamics, providing a useful starting point for more directed surveillance approaches.

Campylobacter and pathogenic Escherichia coliillnesses have been attributed to the consumption of fresh produce. The leafy green, kale, is increasingly consumed raw. In comparison to other leafy greens, kale has a longer shelf-life. Due to the extended shelf-life of kale, it is warranted to examine the survival of pathogenic Campylobacter jejuni and E. coli O157:H7 inoculated on the surface of kale stored in a controlled environment at 4 ± 1.4°C, and average humidity of 95 ± 1.9% over a 23-day period. At predetermined time points (days 0, 1, 2, 3, 5, 7, 9, 11, 13, 15, 17, 19, and 21), inoculated kale was destructively sampled and the surviving bacteria determined by serial dilution and plating onto Tryptic soy agar, Charcoal cefoperozone deoxycholate agar, and Eosin methylene blue for total aerobic bacteria, C. jejuni, and E. coli O157:H7, respectively. Enrichment and PCR were used for detection when pathogens were not detected using serial dilution and plating. Aerobic heterotrophic bacteria increased over the 23-day period, in contrast, significant declines in the inoculated pathogens were observed. Inoculated E. coli O157:H7 survived longer on kale (up to 19 d); in comparison, C. jejuni was undetectable by day 13 using enrichment and PCR or plating. In conclusion, C. jejuni and E. coli O157:H7 declined on fresh kale over time when held at refrigerated temperatures but were still detected during the majority of the time when the kale would likely still be considered edible by consumers.

Hydrological modeling of large river basins and flood plains continues to be challenged by the low availability and quality of observed data for modeling input and model calibration. Global datasets are often used to bridge this gap, but are often difficult and time consuming to acquire, particularly in low resource regions of the world. Numerous calls have been made to standardize and share data to increase local basin modeling capacities and reduce redundancy in efforts, but barriers still exist. We discuss the challenges of hydrological modeling in data-scarce regions and describe a freely available online tool site developed to enable users to extract input data for any basin of any size. The site will allow users to visualize, map, interpolate, and reformat the data as needed for the intended application. We used our hydrological model of the Upper Zambezi basin and the Chobe-Zambezi floodplains to illustrate the use of this online toolset. Increasing access and dissemination of hydrological modeling data is a critical need, particularly among users where data requirements and access continue to impede locally driven management of hydrological systems.

Hydrological modeling of large river basins and flood plains continues to be challenged by the low availability and quality of observed data for modeling input and model calibration. Global datasets are often used to bridge this gap, but are often difficult and time consuming to acquire, particularly in low resource regions of the world. Numerous calls have been made to standardize and share data to increase local basin modeling capacities and reduce redundancy in efforts, but barriers still exist. We discuss the challenges of hydrological modeling in data-scarce regions and describe a freely available online tool site developed to enable users to extract input data for any basin of any size. The site will allow users to visualize, map, interpolate, and reformat the data as needed for the intended application. We used our hydrological model of the Upper Zambezi basin and the Chobe-Zambezi floodplains to illustrate the use of this online toolset. Increasing access and dissemination of hydrological modeling data is a critical need, particularly among users where data requirements and access continue to impede locally driven management of hydrological systems.

Campylobacter and pathogenic Escherichia coli illnesses are attributed to consumption of fresh produce. From 2018-2021 there were eleven multistate outbreaks investigated by the US Centers for Disease Control and Prevention that were linked to leafy greens. The leafy green, kale, is increasingly consumed raw. Without cooking, there is no heat kill step to remove harmful pathogens from raw kale. There are several places along the supply chain that leafy greens, such as kale, can become contaminated with E. coli and Campylobacter. Contamination can occur at the farm during growth, during harvest, and after harvest. In comparison to other leafy greens kale has a longer shelf life often exceeding 15 days under proper storage conditions

Antimicrobial resistance is a disseminated global health challenge because many of the genes that cause resistance can transfer horizontally between bacteria. Despite the central role of extrachromosomal DNA elements called plasmids in driving the spread of resistance, the detection and surveillance of plasmids remains a significant barrier in molecular epidemiology. We assessed two DNA sequencing platforms alone and in combination for laboratory diagnostics in Botswana by annotating antibiotic resistance genes and plasmids in extensively drug resistant bacteria from diarrhea in Botswana. Long-read Nanopore DNA sequencing and high accuracy basecalling effectively estimated the architecture and gene content of three plasmids in Escherichia coli HUM3355 and two plasmids in Klebsiella pneumoniae HUM7199. Polishing the assemblies with Illumina reads increased base calling precision with small improvements to gene prediction. All five plasmids encoded one or more antibiotic resistance genes, usually within gene islands containing multiple antibiotic and metal resistance genes, and four plasmids encoded genes associated with conjugative transfer. Two plasmids were almost identical to antibiotic resistance plasmids sequenced in Europe and North America from human infection and a pig farm. These One Health connections demonstrate how low-, middle-, and high-income countries collectively benefit from increased whole genome sequencing capacity for surveillance and tracking of infectious diseases and antibiotic resistance genes that can transfer between animal hosts and move across continents.

Campylobacter and pathogenic Escherichia coli illnesses are attributed to consumption of fresh produce. From 2018-2021 there were eleven multistate outbreaks investigated by the US Centers for Disease Control and Prevention that were linked to leafy greens. The leafy green, kale, is increasingly consumed raw. Without cooking, there is no heat kill step to remove harmful pathogens from raw kale. There are several places along the supply chain that leafy greens, such as kale, can become contaminated with E. coli and Campylobacter. Contamination can occur at the farm during growth, during harvest, and after harvest. In comparison to other leafy greens kale has a longer shelf life often exceeding 15 days under proper storage conditions

Antimicrobial resistance is a disseminated global health challenge because many of the genes that cause resistance can transfer horizontally between bacteria. Despite the central role of extrachromosomal DNA elements called plasmids in driving the spread of resistance, the detection and surveillance of plasmids remains a significant barrier in molecular epidemiology. We assessed two DNA sequencing platforms alone and in combination for laboratory diagnostics in Botswana by annotating antibiotic resistance genes and plasmids in extensively drug resistant bacteria from diarrhea in Botswana. Long-read Nanopore DNA sequencing and high accuracy basecalling effectively estimated the architecture and gene content of three plasmids in Escherichia coli HUM3355 and two plasmids in Klebsiella pneumoniae HUM7199. Polishing the assemblies with Illumina reads increased base calling precision with small improvements to gene prediction. All five plasmids encoded one or more antibiotic resistance genes, usually within gene islands containing multiple antibiotic and metal resistance genes, and four plasmids encoded genes associated with conjugative transfer. Two plasmids were almost identical to antibiotic resistance plasmids sequenced in Europe and North America from human infection and a pig farm. These One Health connections demonstrate how low-, middle-, and high-income countries collectively benefit from increased whole genome sequencing capacity for surveillance and tracking of infectious diseases and antibiotic resistance genes that can transfer between animal hosts and move across continents.

Campylobacter and pathogenic Escherichia coli illnesses are attributed to consumption of fresh produce. From 2018-2021 there were eleven multistate outbreaks investigated by the US Centers for Disease Control and Prevention that were linked to leafy greens. The leafy green, kale, is increasingly consumed raw. Without cooking, there is no heat kill step to remove harmful pathogens from raw kale. There are several places along the supply chain that leafy greens, such as kale, can become contaminated with E. coli and Campylobacter. Contamination can occur at the farm during growth, during harvest, and after harvest. In comparison to other leafy greens kale has a longer shelf life often exceeding 15 days under proper storage conditions

Disease transmission can be strongly influenced by the manner in which conspecifics are connected across a landscape and the effects of land use upon these dynamics. In northern Botswana, the territorial and group-living banded mongoose (Mungos mungo) lives across urban and natural landscapes and is infected with a novel Mycobacterium tuberculosis complex pathogen, M. mungi. Using microsatellite markers amplified from DNA derived from banded mongoose fecal and tissue samples (n = 168), we evaluated population genetic structure, individual dispersal, and gene flow for 12 troops. Genetic structure was detectable and moderately strong across groups (FST = 0.086), with K = 7 being the best-supported number of genetic clusters. Indications of admixture in certain troops suggest formation of new groups through recent fusion events. Differentiation was higher for troops inhabiting natural areas (FST = 0.102) than for troops in urban landscapes (FST = 0.081). While this suggests increased levels of gene flow between urban-dwelling troops, the inclusion of a smaller number of study troops from natural land types may have influenced these findings. Of those individuals confirmed infected with M. mungi, the majority (73%, n = 11) were assigned to their natal group which is consistent with previous observations linking lower levels of dispersal with infection. Twenty-one probable dispersing individuals were identified, with all suspected migrants originating from troops within the urban landscape. Findings suggest that urbanized landscapes may increase gene flow and dispersal behavior with a concomitant increase in the risk of pathogen spread. As urban landscapes expand, there is an increasing need to understand how land use and pathogen infection may change wildlife behavior and disease transmission potential.

We evaluated the prevalence of Rift Valley fever virus IgG and IgM in human serum samples (n = 1,276) collected in 2013–2014 in northern Botswana. Our findings provide evidence of active circulation of this virus in humans in the absence of clinical disease in this region.

We evaluated the prevalence of Rift Valley fever virus IgG and IgM in human serum samples (n = 1,276) collected in 2013-2014 in northern Botswana. Our findings provide evidence of active circulation of this virus in humans in the absence of clinical disease in this region.

Background: Campylobacter is a common, but neglected foodborne-zoonotic pathogen, identified as a growing cause of foodborne disease worldwide. Wildlife and domestic animals are considered important reservoirs, but little is known about pathogen infection dynamics in free-ranging mammalian wildlife particularly in sub-Saharan Africa. In countries like Botswana, there is significant overlap between humans and wildlife, with the human population having one of the highest HIV infection rates in the world, increasing vulnerability to infection. Methodology/Principal findings: We investigated Campylobacter occurrence in archived human fecal samples (children and adults, n = 122, 2011), feces from free-ranging banded mongooses (Mungos mungo, n = 201), surface water (n = 70), and river sediment samples (n = 81) collected in 2017 from the Chobe District, northern Botswana. Campylobacter spp. was widespread in humans (23.0%, 95% CI 13.9–35.4%), with infections dominantly associated with C. jejuni (82.1%, n = 28, 95% CI 55.1–94.5%). A small number of patients presented with asymptomatic infections (n = 6). While Campylobacter spp. was rare or absent in environmental samples, over half of sampled mongooses tested positive (56%, 95% CI 45.6–65.4%). Across the urbanwilderness continuum, we found significant differences in Campylobacter spp. detection associated with the type of den used by study mongooses. Mongooses utilizing man-made structures as den sites had significantly higher levels of C. jejuni infection (p = 0.019) than mongooses using natural dens. Conversely, mongooses using natural dens had overall higher levels of detection of Campylobacter at the genus level (p = 0.001). Conclusions: These results suggest that landscape features may have important influences on Campylobacter species exposure and transmission dynamics in wildlife. In particular, data suggest that human-modified landscapes may increase C. jejuni infection, a primarily human pathogen, in banded mongoo

A complex suite of drivers can influence infectious disease transmission with behavior and landscape spatial dynamics contributing importantly to epidemic patterns across host–pathogen-environmental systems. However, our understanding of the interaction between landscape and host behavior and its influence on spatial variability in pathogen transmission is limited. In the banded mongoose (Mungos mungo), a novel tuberculosis pathogen, Mycobacterium mungi, has emerged in Northern Botswana, which is transmitted through olfactory communication behaviors. We evaluated how associations between landscape type and mongoose behaviors affect the frequency of olfactory communication behaviors and pathogen transmission potential. We used remote sensing camera traps at den sites to eliminate observer influence across human-modified and natural landscapes (n = 18 troops, 18,229 detections of banded mongooses from 7,497 photographs). Using generalized linear mixed models, we identified a significant effect of vigilance and the interactions between vigilance and landscape, and vigilance and troop count on the frequency of olfactory behaviors. Troop count-vigilance interactions had a negative influence on olfactory communication. Vigilance, however, appeared to have a bidirectional association with olfactory communication depending on land type. In lodge areas, vigilance was associated with increased olfactory behaviors, but in landscapes with expected increases in predation risk (i.e., national park and urban land-use areas), vigilance had a negative association with olfactory behaviors. The interaction between behavior and landscape type may have the potential to create “super-spreading” environments, or transmission hotspots, where behavior-landscape interactions increase pathogen shedding and transmission potential.

Diarrheal disease is the second largest cause of mortality in children younger than 5, yet our ability to anticipate and prepare for outbreaks remains limited. Here, we develop and test an epidemiological forecast model for childhood diarrheal disease in Chobe District, Botswana. Our prediction system uses a compartmental susceptible-infected-recovered-susceptible (SIRS) model coupled with Bayesian data assimilation to infer relevant epidemiological parameter values and generate retrospective forecasts. Our model inferred two system parameters and accurately simulated weekly observed diarrhea cases from 2007-2017. Accurate retrospective forecasts for diarrhea outbreaks were generated up to six weeks before the predicted peak of the outbreak, and accuracy increased over the progression of the outbreak. Many forecasts generated by our model system were more accurate than predictions made using only historical data trends. Accurate real-time forecasts have the potential to increase local preparedness for coming outbreaks through improved resource allocation and healthcare worker distribution.

Background Glucocorticoids mediate responses to perceived stressors, thereby restoring homeostasis. However, prolonged glucocorticoid elevation may cause homeostatic overload. Using extensive field investigations of banded mongoose (Mungos mungo) groups in northern Botswana, we assessed the influence of reproduction, predation risk, and food limitation on apparent homeostatic overload (n=13 groups, 1542 samples from 268 animals). We experimentally manipulated reproduction and regulated food supply in captive mongooses, and compared their glucocorticoid responses to those obtained from free-living groups. Results At the population level, variation in glucocorticoid levels in free-living mongooses was explained by food limitation: fecal organic matter, recent rainfall, and access to concentrated anthropogenic food resources. Soil macrofauna density and reproductive events explained less and predation risk very little variation in glucocorticoid levels. Reproduction and its associated challenges alone (under regulated feeding conditions) increased glucocorticoid levels 19-fold in a captive group. Among free-living groups, glucocorticoid elevation was seasonal (occurring in late dry season or early wet season when natural food resources were less available), but the timing of peak glucocorticoid production was moderated by access to anthropogenic resources (groups with fewer anthropogenic food sources had peaks earlier in dry seasons). Peak months represented 12- and 16-fold increases in glucocorticoids relative to nadir months with some animals exhibiting 100-fold increases. Relative to the captive group nadir, some free-living groups exhibited 60-fold increases in peak glucocorticoid levels with some animals exhibiting up to 800-fold increases. Most of these animals exhibited 1- to 10-fold increases relative to the captive animal peak. Conclusions Banded mongooses exhibit seasonal chronic glucocorticoid elevation, associated primarily with food limitation and secondar

Diarrheal disease is the second largest cause of mortality in children younger than 5, yet our ability to anticipate and prepare for outbreaks remains limited. Here, we develop and test an epidemiological forecast model for childhood diarrheal disease in Chobe District, Botswana. Our prediction system uses a compartmental susceptible-infected-recovered-susceptible (SIRS) model coupled with Bayesian data assimilation to infer relevant epidemiological parameter values and generate retrospective forecasts. Our model inferred two system parameters and accurately simulated weekly observed diarrhea cases from 2007-2017. Accurate retrospective forecasts for diarrhea outbreaks were generated up to six weeks before the predicted peak of the outbreak, and accuracy increased over the progression of the outbreak. Many forecasts generated by our model system were more accurate than predictions made using only historical data trends. Accurate real-time forecasts have the potential to increase local preparedness for coming outbreaks through improved resource allocation and healthcare worker distribution.

Background: Campylobacter is a common, but neglected foodborne-zoonotic pathogen, identified as a growing cause of foodborne disease worldwide. Wildlife and domestic animals are considered important reservoirs, but little is known about pathogen infection dynamics in free-ranging mammalian wildlife particularly in sub-Saharan Africa. In countries like Botswana, there is significant overlap between humans and wildlife, with the human population having one of the highest HIV infection rates in the world, increasing vulnerability to infection. Methodology/Principal findings: We investigated Campylobacter occurrence in archived human fecal samples (children and adults, n = 122, 2011), feces from free-ranging banded mongooses (Mungos mungo, n = 201), surface water (n = 70), and river sediment samples (n = 81) collected in 2017 from the Chobe District, northern Botswana. Campylobacter spp. was widespread in humans (23.0%, 95% CI 13.9–35.4%), with infections dominantly associated with C. jejuni (82.1%, n = 28, 95% CI 55.1–94.5%). A small number of patients presented with asymptomatic infections (n = 6). While Campylobacter spp. was rare or absent in environmental samples, over half of sampled mongooses tested positive (56%, 95% CI 45.6–65.4%). Across the urbanwilderness continuum, we found significant differences in Campylobacter spp. detection associated with the type of den used by study mongooses. Mongooses utilizing man-made structures as den sites had significantly higher levels of C. jejuni infection (p = 0.019) than mongooses using natural dens. Conversely, mongooses using natural dens had overall higher levels of detection of Campylobacter at the genus level (p = 0.001). Conclusions: These results suggest that landscape features may have important influences on Campylobacter species exposure and transmission dynamics in wildlife. In particular, data suggest that human-modified landscapes may increase C. jejuni infection, a primarily human pathogen, in banded mongoo

Disease transmission can be strongly influenced by the manner in which conspecifics are connected across a landscape and the effects of land use upon these dynamics. In northern Botswana, the territorial and group-living banded mongoose (Mungos mungo) lives across urban and natural landscapes and is infected with a novel Mycobacterium tuberculosis complex pathogen, M. mungi. Using microsatellite markers amplified from DNA derived from banded mongoose fecal and tissue samples (n = 168), we evaluated population genetic structure, individual dispersal, and gene flow for 12 troops. Genetic structure was detectable and moderately strong across groups (FST = 0.086), with K = 7 being the best-supported number of genetic clusters. Indications of admixture in certain troops suggest formation of new groups through recent fusion events. Differentiation was higher for troops inhabiting natural areas (FST = 0.102) than for troops in urban landscapes (FST = 0.081). While this suggests increased levels of gene flow between urban-dwelling troops, the inclusion of a smaller number of study troops from natural land types may have influenced these findings. Of those individuals confirmed infected with M. mungi, the majority (73%, n = 11) were assigned to their natal group which is consistent with previous observations linking lower levels of dispersal with infection. Twenty-one probable dispersing individuals were identified, with all suspected migrants originating from troops within the urban landscape. Findings suggest that urbanized landscapes may increase gene flow and dispersal behavior with a concomitant increase in the risk of pathogen spread. As urban landscapes expand, there is an increasing need to understand how land use and pathogen infection may change wildlife behavior and disease transmission potential.

A complex suite of drivers can influence infectious disease transmission with behavior and landscape spatial dynamics contributing importantly to epidemic patterns across host–pathogen-environmental systems. However, our understanding of the interaction between landscape and host behavior and its influence on spatial variability in pathogen transmission is limited. In the banded mongoose (Mungos mungo), a novel tuberculosis pathogen, Mycobacterium mungi, has emerged in Northern Botswana, which is transmitted through olfactory communication behaviors. We evaluated how associations between landscape type and mongoose behaviors affect the frequency of olfactory communication behaviors and pathogen transmission potential. We used remote sensing camera traps at den sites to eliminate observer influence across human-modified and natural landscapes (n = 18 troops, 18,229 detections of banded mongooses from 7,497 photographs). Using generalized linear mixed models, we identified a significant effect of vigilance and the interactions between vigilance and landscape, and vigilance and troop count on the frequency of olfactory behaviors. Troop count-vigilance interactions had a negative influence on olfactory communication. Vigilance, however, appeared to have a bidirectional association with olfactory communication depending on land type. In lodge areas, vigilance was associated with increased olfactory behaviors, but in landscapes with expected increases in predation risk (i.e., national park and urban land-use areas), vigilance had a negative association with olfactory behaviors. The interaction between behavior and landscape type may have the potential to create “super-spreading” environments, or transmission hotspots, where behavior-landscape interactions increase pathogen shedding and transmission potential.

Diarrheal disease is the second largest cause of mortality in children younger than 5, yet our ability to anticipate and prepare for outbreaks remains limited. Here, we develop and test an epidemiological forecast model for childhood diarrheal disease in Chobe District, Botswana. Our prediction system uses a compartmental susceptible-infected-recovered-susceptible (SIRS) model coupled with Bayesian data assimilation to infer relevant epidemiological parameter values and generate retrospective forecasts. Our model inferred two system parameters and accurately simulated weekly observed diarrhea cases from 2007-2017. Accurate retrospective forecasts for diarrhea outbreaks were generated up to six weeks before the predicted peak of the outbreak, and accuracy increased over the progression of the outbreak. Many forecasts generated by our model system were more accurate than predictions made using only historical data trends. Accurate real-time forecasts have the potential to increase local preparedness for coming outbreaks through improved resource allocation and healthcare worker distribution.

Background: Campylobacter is a common, but neglected foodborne-zoonotic pathogen, identified as a growing cause of foodborne disease worldwide. Wildlife and domestic animals are considered important reservoirs, but little is known about pathogen infection dynamics in free-ranging mammalian wildlife particularly in sub-Saharan Africa. In countries like Botswana, there is significant overlap between humans and wildlife, with the human population having one of the highest HIV infection rates in the world, increasing vulnerability to infection. Methodology/Principal findings: We investigated Campylobacter occurrence in archived human fecal samples (children and adults, n = 122, 2011), feces from free-ranging banded mongooses (Mungos mungo, n = 201), surface water (n = 70), and river sediment samples (n = 81) collected in 2017 from the Chobe District, northern Botswana. Campylobacter spp. was widespread in humans (23.0%, 95% CI 13.9–35.4%), with infections dominantly associated with C. jejuni (82.1%, n = 28, 95% CI 55.1–94.5%). A small number of patients presented with asymptomatic infections (n = 6). While Campylobacter spp. was rare or absent in environmental samples, over half of sampled mongooses tested positive (56%, 95% CI 45.6–65.4%). Across the urbanwilderness continuum, we found significant differences in Campylobacter spp. detection associated with the type of den used by study mongooses. Mongooses utilizing man-made structures as den sites had significantly higher levels of C. jejuni infection (p = 0.019) than mongooses using natural dens. Conversely, mongooses using natural dens had overall higher levels of detection of Campylobacter at the genus level (p = 0.001). Conclusions: These results suggest that landscape features may have important influences on Campylobacter species exposure and transmission dynamics in wildlife. In particular, data suggest that human-modified landscapes may increase C. jejuni infection, a primarily human pathogen, in banded mongoo

Background Glucocorticoids mediate responses to perceived stressors, thereby restoring homeostasis. However, prolonged glucocorticoid elevation may cause homeostatic overload. Using extensive field investigations of banded mongoose (Mungos mungo) groups in northern Botswana, we assessed the influence of reproduction, predation risk, and food limitation on apparent homeostatic overload (n=13 groups, 1542 samples from 268 animals). We experimentally manipulated reproduction and regulated food supply in captive mongooses, and compared their glucocorticoid responses to those obtained from free-living groups. Results At the population level, variation in glucocorticoid levels in free-living mongooses was explained by food limitation: fecal organic matter, recent rainfall, and access to concentrated anthropogenic food resources. Soil macrofauna density and reproductive events explained less and predation risk very little variation in glucocorticoid levels. Reproduction and its associated challenges alone (under regulated feeding conditions) increased glucocorticoid levels 19-fold in a captive group. Among free-living groups, glucocorticoid elevation was seasonal (occurring in late dry season or early wet season when natural food resources were less available), but the timing of peak glucocorticoid production was moderated by access to anthropogenic resources (groups with fewer anthropogenic food sources had peaks earlier in dry seasons). Peak months represented 12- and 16-fold increases in glucocorticoids relative to nadir months with some animals exhibiting 100-fold increases. Relative to the captive group nadir, some free-living groups exhibited 60-fold increases in peak glucocorticoid levels with some animals exhibiting up to 800-fold increases. Most of these animals exhibited 1- to 10-fold increases relative to the captive animal peak. Conclusions Banded mongooses exhibit seasonal chronic glucocorticoid elevation, associated primarily with food limitation and secondar

We evaluated the prevalence of Rift Valley fever virus IgG and IgM in human serum samples (n = 1,276) collected in 2013-2014 in northern Botswana. Our findings provide evidence of active circulation of this virus in humans in the absence of clinical disease in this region.

We evaluated the prevalence of Rift Valley fever virus IgG and IgM in human serum samples (n = 1,276) collected in 2013–2014 in northern Botswana. Our findings provide evidence of active circulation of this virus in humans in the absence of clinical disease in this region.

Background: Campylobacter is a common, but neglected foodborne-zoonotic pathogen, identified as a growing cause of foodborne disease worldwide. Wildlife and domestic animals are considered important reservoirs, but little is known about pathogen infection dynamics in free-ranging mammalian wildlife particularly in sub-Saharan Africa. In countries like Botswana, there is significant overlap between humans and wildlife, with the human population having one of the highest HIV infection rates in the world, increasing vulnerability to infection. Methodology/Principal findings: We investigated Campylobacter occurrence in archived human fecal samples (children and adults, n = 122, 2011), feces from free-ranging banded mongooses (Mungos mungo, n = 201), surface water (n = 70), and river sediment samples (n = 81) collected in 2017 from the Chobe District, northern Botswana. Campylobacter spp. was widespread in humans (23.0%, 95% CI 13.9–35.4%), with infections dominantly associated with C. jejuni (82.1%, n = 28, 95% CI 55.1–94.5%). A small number of patients presented with asymptomatic infections (n = 6). While Campylobacter spp. was rare or absent in environmental samples, over half of sampled mongooses tested positive (56%, 95% CI 45.6–65.4%). Across the urbanwilderness continuum, we found significant differences in Campylobacter spp. detection associated with the type of den used by study mongooses. Mongooses utilizing man-made structures as den sites had significantly higher levels of C. jejuni infection (p = 0.019) than mongooses using natural dens. Conversely, mongooses using natural dens had overall higher levels of detection of Campylobacter at the genus level (p = 0.001). Conclusions: These results suggest that landscape features may have important influences on Campylobacter species exposure and transmission dynamics in wildlife. In particular, data suggest that human-modified landscapes may increase C. jejuni infection, a primarily human pathogen, in banded mongoo

Diarrheal disease is the second largest cause of mortality in children younger than 5, yet our ability to anticipate and prepare for outbreaks remains limited. Here, we develop and test an epidemiological forecast model for childhood diarrheal disease in Chobe District, Botswana. Our prediction system uses a compartmental susceptible-infected-recovered-susceptible (SIRS) model coupled with Bayesian data assimilation to infer relevant epidemiological parameter values and generate retrospective forecasts. Our model inferred two system parameters and accurately simulated weekly observed diarrhea cases from 2007-2017. Accurate retrospective forecasts for diarrhea outbreaks were generated up to six weeks before the predicted peak of the outbreak, and accuracy increased over the progression of the outbreak. Many forecasts generated by our model system were more accurate than predictions made using only historical data trends. Accurate real-time forecasts have the potential to increase local preparedness for coming outbreaks through improved resource allocation and healthcare worker distribution.

Disease transmission can be strongly influenced by the manner in which conspecifics are connected across a landscape and the effects of land use upon these dynamics. In northern Botswana, the territorial and group-living banded mongoose (Mungos mungo) lives across urban and natural landscapes and is infected with a novel Mycobacterium tuberculosis complex pathogen, M. mungi. Using microsatellite markers amplified from DNA derived from banded mongoose fecal and tissue samples (n = 168), we evaluated population genetic structure, individual dispersal, and gene flow for 12 troops. Genetic structure was detectable and moderately strong across groups (FST = 0.086), with K = 7 being the best-supported number of genetic clusters. Indications of admixture in certain troops suggest formation of new groups through recent fusion events. Differentiation was higher for troops inhabiting natural areas (FST = 0.102) than for troops in urban landscapes (FST = 0.081). While this suggests increased levels of gene flow between urban-dwelling troops, the inclusion of a smaller number of study troops from natural land types may have influenced these findings. Of those individuals confirmed infected with M. mungi, the majority (73%, n = 11) were assigned to their natal group which is consistent with previous observations linking lower levels of dispersal with infection. Twenty-one probable dispersing individuals were identified, with all suspected migrants originating from troops within the urban landscape. Findings suggest that urbanized landscapes may increase gene flow and dispersal behavior with a concomitant increase in the risk of pathogen spread. As urban landscapes expand, there is an increasing need to understand how land use and pathogen infection may change wildlife behavior and disease transmission potential.

Background Glucocorticoids mediate responses to perceived stressors, thereby restoring homeostasis. However, prolonged glucocorticoid elevation may cause homeostatic overload. Using extensive field investigations of banded mongoose (Mungos mungo) groups in northern Botswana, we assessed the influence of reproduction, predation risk, and food limitation on apparent homeostatic overload (n=13 groups, 1542 samples from 268 animals). We experimentally manipulated reproduction and regulated food supply in captive mongooses, and compared their glucocorticoid responses to those obtained from free-living groups. Results At the population level, variation in glucocorticoid levels in free-living mongooses was explained by food limitation: fecal organic matter, recent rainfall, and access to concentrated anthropogenic food resources. Soil macrofauna density and reproductive events explained less and predation risk very little variation in glucocorticoid levels. Reproduction and its associated challenges alone (under regulated feeding conditions) increased glucocorticoid levels 19-fold in a captive group. Among free-living groups, glucocorticoid elevation was seasonal (occurring in late dry season or early wet season when natural food resources were less available), but the timing of peak glucocorticoid production was moderated by access to anthropogenic resources (groups with fewer anthropogenic food sources had peaks earlier in dry seasons). Peak months represented 12- and 16-fold increases in glucocorticoids relative to nadir months with some animals exhibiting 100-fold increases. Relative to the captive group nadir, some free-living groups exhibited 60-fold increases in peak glucocorticoid levels with some animals exhibiting up to 800-fold increases. Most of these animals exhibited 1- to 10-fold increases relative to the captive animal peak. Conclusions Banded mongooses exhibit seasonal chronic glucocorticoid elevation, associated primarily with food limitation and secondar

Background: Campylobacter is a common, but neglected foodborne-zoonotic pathogen, identified as a growing cause of foodborne disease worldwide. Wildlife and domestic animals are considered important reservoirs, but little is known about pathogen infection dynamics in free-ranging mammalian wildlife particularly in sub-Saharan Africa. In countries like Botswana, there is significant overlap between humans and wildlife, with the human population having one of the highest HIV infection rates in the world, increasing vulnerability to infection. Methodology/Principal findings: We investigated Campylobacter occurrence in archived human fecal samples (children and adults, n = 122, 2011), feces from free-ranging banded mongooses (Mungos mungo, n = 201), surface water (n = 70), and river sediment samples (n = 81) collected in 2017 from the Chobe District, northern Botswana. Campylobacter spp. was widespread in humans (23.0%, 95% CI 13.9–35.4%), with infections dominantly associated with C. jejuni (82.1%, n = 28, 95% CI 55.1–94.5%). A small number of patients presented with asymptomatic infections (n = 6). While Campylobacter spp. was rare or absent in environmental samples, over half of sampled mongooses tested positive (56%, 95% CI 45.6–65.4%). Across the urbanwilderness continuum, we found significant differences in Campylobacter spp. detection associated with the type of den used by study mongooses. Mongooses utilizing man-made structures as den sites had significantly higher levels of C. jejuni infection (p = 0.019) than mongooses using natural dens. Conversely, mongooses using natural dens had overall higher levels of detection of Campylobacter at the genus level (p = 0.001). Conclusions: These results suggest that landscape features may have important influences on Campylobacter species exposure and transmission dynamics in wildlife. In particular, data suggest that human-modified landscapes may increase C. jejuni infection, a primarily human pathogen, in banded mongoo

Bacillus anthracis is a spore-forming, Gram-positive bacterium responsible for anthrax, an acute infection that most significantly affects grazing livestock and wild ungulates, but also poses a threat to human health. The geographic extent of B. anthracis is poorly understood, despite multi-decade research on anthrax epizootic and epidemic dynamics; many countries have limited or inadequate surveillance systems, even within known endemic regions. Here, we compile a global occurrence dataset of human, livestock and wildlife anthrax outbreaks. With these records, we use boosted regression trees to produce a map of the global distribution of B. anthracis as a proxy for anthrax risk. We estimate that 1.83 billion people (95% credible interval (CI): 0.59-4.16 billion) live within regions of anthrax risk, but most of that population faces little occupational exposure. More informatively, a global total of 63.8 million poor livestock keepers (95% CI: 17.5-168.6 million) and 1.1 billion livestock (95% CI: 0.4-2.3 billion) live within vulnerable regions. Human and livestock vulnerability are both concentrated in rural rainfed systems throughout arid and temperate land across Eurasia, Africa and North America. We conclude by mapping where anthrax risk could disrupt sensitive conservation efforts for wild ungulates that coincide with anthrax-prone landscapes.

Epidemiological contact network models have emerged as an important tool in understanding and predicting spread of infectious disease, due to their capacity to engage individual heterogeneity that may underlie essential dynamics of a particular host-pathogen system. Just as fundamental are the changes that real-world contact networks undergo over time, both independently of and in response to pathogen spreading. These dynamics play a central role in determining whether a disease will die out or become epidemic within a population, known as the epidemic threshold. In this paper, we provide an overview of methods to predict the epidemic threshold for temporal contact network models, and discuss areas that remain unexplored.

Childhood diarrheal disease causes significant morbidity and mortality in low and middle income countries, yet our ability to accurately predict diarrhea incidence remains limited. El Niño-Southern Oscillation (ENSO) has been shown to affect diarrhea dynamics in South America and Asia. However, understanding of its effects in sub-Saharan Africa, where the burden of under-5 diarrhea is high, remains inadequate. Here we investigate the connections between ENSO, local environmental conditions, and childhood diarrheal disease in Chobe District, Botswana. Our results demonstrate that La Niña conditions are associated with cooler temperatures, increased rainfall, and higher flooding in the Chobe region during the rainy season. In turn, La Niña conditions lagged 0–5 months are associated with higher than average incidence of under-5 diarrhea in the early rainy season. These findings demonstrate the potential use of ENSO as a long-lead prediction tool for childhood diarrhea in southern Africa.

Epidemiological contact network models have emerged as an important tool in understanding and predicting spread of infectious disease, due to their capacity to engage individual heterogeneity that may underlie essential dynamics of a particular host-pathogen system. Just as fundamental are the changes that real-world contact networks undergo over time, both independently of and in response to pathogen spreading. These dynamics play a central role in determining whether a disease will die out or become epidemic within a population, known as the epidemic threshold. In this paper, we provide an overview of methods to predict the epidemic threshold for temporal contact network models, and discuss areas that remain unexplored.

Bacillus anthracis is a spore-forming, Gram-positive bacterium responsible for anthrax, an acute infection that most significantly affects grazing livestock and wild ungulates, but also poses a threat to human health. The geographic extent of B. anthracis is poorly understood, despite multi-decade research on anthrax epizootic and epidemic dynamics; many countries have limited or inadequate surveillance systems, even within known endemic regions. Here, we compile a global occurrence dataset of human, livestock and wildlife anthrax outbreaks. With these records, we use boosted regression trees to produce a map of the global distribution of B. anthracis as a proxy for anthrax risk. We estimate that 1.83 billion people (95% credible interval (CI): 0.59-4.16 billion) live within regions of anthrax risk, but most of that population faces little occupational exposure. More informatively, a global total of 63.8 million poor livestock keepers (95% CI: 17.5-168.6 million) and 1.1 billion livestock (95% CI: 0.4-2.3 billion) live within vulnerable regions. Human and livestock vulnerability are both concentrated in rural rainfed systems throughout arid and temperate land across Eurasia, Africa and North America. We conclude by mapping where anthrax risk could disrupt sensitive conservation efforts for wild ungulates that coincide with anthrax-prone landscapes.

Epidemiological contact network models have emerged as an important tool in understanding and predicting spread of infectious disease, due to their capacity to engage individual heterogeneity that may underlie essential dynamics of a particular host-pathogen system. Just as fundamental are the changes that real-world contact networks undergo over time, both independently of and in response to pathogen spreading. These dynamics play a central role in determining whether a disease will die out or become epidemic within a population, known as the epidemic threshold. In this paper, we provide an overview of methods to predict the epidemic threshold for temporal contact network models, and discuss areas that remain unexplored.

Epidemiological contact network models have emerged as an important tool in understanding and predicting spread of infectious disease, due to their capacity to engage individual heterogeneity that may underlie essential dynamics of a particular host-pathogen system. Just as fundamental are the changes that real-world contact networks undergo over time, both independently of and in response to pathogen spreading. These dynamics play a central role in determining whether a disease will die out or become epidemic within a population, known as the epidemic threshold. In this paper, we provide an overview of methods to predict the epidemic threshold for temporal contact network models, and discuss areas that remain unexplored.

Epidemiological contact network models have emerged as an important tool in understanding and predicting spread of infectious disease, due to their capacity to engage individual heterogeneity that may underlie essential dynamics of a particular host-pathogen system. Just as fundamental are the changes that real-world contact networks undergo over time, both independently of and in response to pathogen spreading. These dynamics play a central role in determining whether a disease will die out or become epidemic within a population, known as the epidemic threshold. In this paper, we provide an overview of methods to predict the epidemic threshold for temporal contact network models, and discuss areas that remain unexplored.

Childhood diarrheal disease causes significant morbidity and mortality in low and middle income countries, yet our ability to accurately predict diarrhea incidence remains limited. El Niño-Southern Oscillation (ENSO) has been shown to affect diarrhea dynamics in South America and Asia. However, understanding of its effects in sub-Saharan Africa, where the burden of under-5 diarrhea is high, remains inadequate. Here we investigate the connections between ENSO, local environmental conditions, and childhood diarrheal disease in Chobe District, Botswana. Our results demonstrate that La Niña conditions are associated with cooler temperatures, increased rainfall, and higher flooding in the Chobe region during the rainy season. In turn, La Niña conditions lagged 0–5 months are associated with higher than average incidence of under-5 diarrhea in the early rainy season. These findings demonstrate the potential use of ENSO as a long-lead prediction tool for childhood diarrhea in southern Africa.

Little is known about the role of surface water in the propagation of antibiotic resistance (AR), or the relationship between AR and water quality declines. While healthcare and agricultural sectors are considered the main contributors to AR dissemination, few studies have been conducted in their absence. Using linear models and Bayesian kriging, we evaluate AR among Escherichia coli water isolates collected bimonthly from the Chobe River in Northern Botswana (n = 1997, n = 414 water samples; July 2011–May 2012) in relation to water quality dynamics (E. coli, fecal coliform, and total suspended solids), land use, season, and AR in wildlife and humans within this system. No commercial agricultural or large medical facilities exist within this region. Here, we identify widespread AR in surface water, with land use and season significant predicators of AR levels. Mean AR was significantly higher in the wet season than the dry season (p = 0.003), and highest in the urban landscape (2.15, SD = 0.098) than the protected landscape (1.39, SD = 0.051). In-water E. coli concentrations were significantly positively associated with mean AR in the wet season (p < 0.001) but not in the dry season (p = 0.110), with TSS negatively associated with mean AR across seasons (p = 0.016 and p = 0.029), identifying temporal and spatial relationships between water quality variables and AR. Importantly, when human, water, and wildlife isolates were examined, similar AR profiles were identified (p < 0.001). Our results suggest that direct human inputs are sufficient for extensive dispersal of AR into the environment, with landscape features, season, and water quality variables influencing AR dynamics. Focused and expensive efforts to minimize pollution from agricultural sources, while important, may only provide incremental benefits to the management of AR across complex landscapes. Controlling direct human AR inputs into the environment remains a critical and pressing challenge.

Background Variation in animal space use reflects fitness trade-offs associated with ecological constraints. Associated theories such as the metabolic theory of ecology and the resource dispersion hypothesis generate predictions about what drives variation in animal space use. But, metabolic theory is usually tested in macro-ecological studies and is seldom invoked explicitly in within-species studies. Full evaluation of the resource dispersion hypothesis requires testing in more species. Neither have been evaluated in the context of anthropogenic landscape change. Methods In this study, we used data for banded mongooses (Mungos mungo) in northeastern Botswana, along a gradient of association with humans, to test for effects of space use drivers predicted by these theories. We used Bayesian parameter estimation and inference from linear models to test for seasonal differences in space use metrics and to model seasonal effects of space use drivers. Results Results suggest that space use is strongly associated with variation in the level of overlap that mongoose groups have with humans. Seasonality influences this association, reversing seasonal space use predictions historically-accepted by ecologists. We found support for predictions of the metabolic theory when moderated by seasonality, by association with humans and by their interaction. Space use of mongooses living in association with humans was more concentrated in the dry season than the wet season, when historically-accepted ecological theory predicted more dispersed space use. Resource richness factors such as building density were associated with space use only during the dry season. We found negligible support for predictions of the resource dispersion hypothesis in general or for metabolic theory where seasonality and association with humans were not included. For mongooses living in association with humans, space use was not associated with patch dispersion or group size over both seasons. Conclusions In

Little is known about the role of surface water in the propagation of antibiotic resistance (AR), or the relationship between AR and water quality declines. While healthcare and agricultural sectors are considered the main contributors to AR dissemination, few studies have been conducted in their absence. Using linear models and Bayesian kriging, we evaluate AR among Escherichia coli water isolates collected bimonthly from the Chobe River in Northern Botswana (n = 1997, n = 414 water samples; July 2011–May 2012) in relation to water quality dynamics (E. coli, fecal coliform, and total suspended solids), land use, season, and AR in wildlife and humans within this system. No commercial agricultural or large medical facilities exist within this region. Here, we identify widespread AR in surface water, with land use and season significant predicators of AR levels. Mean AR was significantly higher in the wet season than the dry season (p = 0.003), and highest in the urban landscape (2.15, SD = 0.098) than the protected landscape (1.39, SD = 0.051). In-water E. coli concentrations were significantly positively associated with mean AR in the wet season (p < 0.001) but not in the dry season (p = 0.110), with TSS negatively associated with mean AR across seasons (p = 0.016 and p = 0.029), identifying temporal and spatial relationships between water quality variables and AR. Importantly, when human, water, and wildlife isolates were examined, similar AR profiles were identified (p < 0.001). Our results suggest that direct human inputs are sufficient for extensive dispersal of AR into the environment, with landscape features, season, and water quality variables influencing AR dynamics. Focused and expensive efforts to minimize pollution from agricultural sources, while important, may only provide incremental benefits to the management of AR across complex landscapes. Controlling direct human AR inputs into the environment remains a critical and pressing challenge.

Wildlife activity patterns tend to be defined by terms such as diurnal and nocturnal that might not fully depict the complexity of a species' life history strategy and behavior in a given system. These activity pattern categories often influence the methodological approaches employed, including the temporal period of study (daylight or nighttime). We evaluated banded mongoose (Mungos mungo) behavior in Northern Botswana through the use of remote sensing cameras at active den sites in order to characterize early morning behavior for this diurnal species. Our approach, however, provided the facility to capture unexpected nocturnal activity in a species that had otherwise only been studied during daylight hours. Camera traps were deployed for 215 trap days (24 hour data capture period) at den sites, capturing 5,472 photos over all events. Nocturnal activity was identified in 3% of trap days at study den sites with both vigilant and non-vigilant nocturnal behaviors identified. While vigilant behaviors involved troop fleeing responses, observations of non-vigilant behaviors suggest nonresident mongoose may investigate den sites of other troops during nocturnal time periods. There was no association between the occurrence of nocturnal activity and lunar phase (Fisher's exact test, n = 215, p = 0.638) and thus, increased moonlight was not identified as a factor influencing nocturnal behavior. The drivers and fitness consequences of these nocturnal activities remain uncertain and present intriguing areas for future research. Our findings highlight the need for ecological studies to more explicitly address and evaluate the potential for temporal variability in activity periods. Modifying our approach and embracing variation in wildlife activity patterns might provide new insights into the interaction between ecological phenomenon and species biology that spans the diurnal-nocturnal spectrum.