Predicting spatiotemporal patterns of road mortality for medium-large mammals

Ascensão, Fernando; Yogui, Débora Regina; Alves, Mário Henrique; Medici, Emília Patrícia; Desbiez, Arnaud Léonard Jean

doi:10.1016/j.jenvman.2019.109320

Cited by 37 publications

(27 citation statements)

References 39 publications

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“…Collectively, these results demonstrate that giant anteaters do not change their movement behaviour and space use near paved roads, nor search for safe crossing structures, which is probably the cause of the high roadkill rates (Ascensão et al 2021). This contradicts previous research suggesting that the barrier to movement and population redistribution was the most important road impact and emphasises the need to obtain sound empirical data on animal movement when planning and managing transportation networks (Ascensão et al 2019b).…”

Section: Discussioncontrasting

confidence: 69%

Roads as ecological traps for giant anteaters

Noonan

Ascensão

Yogui

et al. 2021

Preprint

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Wildlife-vehicle collisions (WVC) represent a serious source of mortality for many species, threatening local populations' persistence while also carrying a high economic and human safety cost. Animals may adapt their behaviour to road associated threats, but roadside resources can act as attractants, providing misleading signals about the quality of roadside habitats, ultimately acting as an ecological trap. Yet, the extent to which individuals modify their behaviour and space use to roads is largely unknown for most taxa. Using fine-scale movement data from 41 giant anteaters (Myrmecophaga tridactyla), tracked in the Brazilian Cerrado, we aimed to identify facets of movement behaviour that might exhibit plasticity to roads and traffic volume. Specifically, the analysis of daily and instantaneous movement speeds, home range characteristics, and crossing rates/times, allowed us to test for an effect of road proximity, traffic volume and natural linear features on movement behaviour. We found no effect of road proximity or traffic volume on space use or movement behaviour. While individuals tended to reduce their movement speed when approaching roads and crossed roads ~3 times less than would have been expected by random chance, none of the highways we monitored were impervious. The majority of tracked anteaters living near roads (<2km) crossed them, with higher crossing rates for males. Consequently, habitat near roads may function as an ecological trap where healthy individuals occupy the territories nearby or bisected by roads but eventually are road-killed given their regular crossings, leaving the territory vacant for subsequent occupation. Crucially, we found no evidence that anteaters actively searched for passage structures to cross the roads. This suggests that crossing structures alone are unlikely to mitigate WVC induced mortality. Our research reinforces the need to implement fencing, properly linked to existing passages, and minimising the amount of night-time driving to reduce the number of WVCs.

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Section: Discussioncontrasting

confidence: 69%

Roads as ecological traps for giant anteaters

Noonan

Ascensão

Yogui

et al. 2021

Preprint

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“…Therefore, their number was not enough to have a separate category and, thus, were assigned to the Others applications category. These studies are mainly related to archaeology [169]- [171], 3D printing [172], wildlife [173], [174], oil platform detection [175], and crashed airplane detection [176]. For example, 300 Landsat-8 images between 2013 and 2018 were processed in GEE to detect possible crashed airplane in the Cambodian jungle [176].…”

Section: J Othersmentioning

confidence: 99%

Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review

Amani¹,

Ghorbanian

Ahmadi

et al. 2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

597

216

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Remote Sensing (RS) systems have been collecting massive volumes of datasets for decades, managing and analyzing of which are not practical using common software packages and desktop computing resources. In this regard, Google has developed a cloud computing platform, called Google Earth Engine (GEE), to effectively address the challenges of big data analysis. In particular, this platform facilitates processing big geo data over large areas and monitoring the environment for long periods of time. Although this platform was launched in 2010 and has proved its high potential for different applications, it has not been fully investigated and utilized for RS applications until recent years. Therefore, this study aims to comprehensively explore different aspects of the GEE platform, including its datasets, functions, advantages/limitations, and various applications. For this purpose, 450 journal articles published in 150 journals between January 2010 and May 2020 were studied. It was observed that Landsat and Sentinel datasets were extensively utilized by GEE users. Moreover, supervised machine learning algorithms, such as Random Forest (RF), were more widely applied to image classification tasks. GEE has also been employed in a broad range of applications, such as Land Cover/land Use (LCLU) classification, hydrology, urban planning, natural disaster, climate analyses, and image processing. It was generally observed that the number of GEE publications has significantly increased during the past few years, and it is expected that GEE will be utilized by more users from different fields to resolve their big data processing challenges.

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“…Between February 2017 and February 2020, a periodic road monitoring was carried out to identify the number of armadillos killed by MVC in two states of Brazil, Mato Grosso do Sul (MS) and Sao Paulo (SP) (See 25 for details) 25 . Epidemiological and biological data [species, age class, sex, season (rainy or dry) and coordinates] were recorded from all carcasses.…”

Section: Methodsmentioning

confidence: 99%

“…Since there are reports of PA in Brazil, and the etiologic agent has already been reported in armadillos (preliminarily by molecular technique) 23 , we hypothesized a possible role of armadillos in the epidemiology of PA. Considering that the number of wild animals killed by MVC in Brazil is remarkable 25 , and the potential role of armadillos in the epidemiology of adiaspiromycosis, in this study, we sought to investigate the occurrence and pathological features of adiaspiromycosis in roadkilled armadillos. Here we report 12 cases of PA in two species of wild armadillos of Brazil: the six-banded armadillo ( Euphractus sexcinctus ) and the southern naked-tailed armadillo ( Cabassous unicinctus ).…”

Section: Introductionmentioning

confidence: 99%

Pulmonary adiaspiromycosis in armadillos killed by motor vehicle collisions in Brazil

Navas‐Suárez

Sacristán

Díaz‐Delgado

et al. 2021

Sci Rep

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Knowledge of infectious diseases in wildlife provides important information for preventing potential outbreaks of zoonotic diseases. Adiaspiromycosis is a neglected human disease caused by dimorphic Onygenales fungi. The disease is produced by the inflammatory response against growing adiaspores, leading to granulomatous pneumonia. In humans, adiaspiromycosis is relevant in immunosuppressed patients. In animals, it is associated with pneumonia in fossorial species. Given the potential role of armadillos in the epidemiology of adiaspiromycosis, in this study, we sought to investigate the occurrence and pathological features of adiaspiromycosis in roadkilled armadillos. In total, 54 armadillo carcasses were suitable for postmortem pathologic examinations between February 2017 and 2020. Adiaspores, associated with granulomatous lesions, were observed in ten six-banded (Euphractus sexcinctus) and two southern naked-tailed armadillos (Cabassous unicinctus). A previously uncharacterized Onygenales species was molecularly identified in two E. sexcinctus. In summary, herein we report 12 cases of pulmonary adiaspiromycosis (PA) in two species of free-living armadillos in Brazil. Both, the morphology of the fungus, as well as the histopathological findings (granulomatous inflammatory response to adiaspores) are consistent with PA; however, as the molecular identification differs from the reported species, the potential impact of this fungus for human PA is unknown, and we cannot rule out its impact on public health.

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Predicting spatiotemporal patterns of road mortality for medium-large mammals

Cited by 37 publications

References 39 publications

Roads as ecological traps for giant anteaters

Roads as ecological traps for giant anteaters

Google Earth Engine Cloud Computing Platform for Remote Sensing Big Data Applications: A Comprehensive Review

Pulmonary adiaspiromycosis in armadillos killed by motor vehicle collisions in Brazil

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