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"Marking"
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Using heterogeneous camera-trapping sites to obtain the first density estimates for the transboundary Eurasian lynx (Lynx lynx) population in the Dinaric Mountains
Estimating abundance of wild animal populations is crucial for their management and conservation. While spatial capture-recapture models are becoming increasingly common to assess the densities of elusive species, recent studies have indicated potential bias that can be introduced by unaccounted spatial variation of detectability. We used camera-trapping data collected in collaboration with local hunters from a transnational population survey of the Eurasian lynx (Lynx lynx) in Slovenia and Croatia, to provide the first density estimate for the threatened Eurasian lynx population in the Northern Dinaric Mountains. Population density was 0.83 (95% CI: 0.60–1.16) lynx/100 km2, which is comparable to other reintroduced Eurasian lynx populations in Europe. Furthermore, we showed that baseline detection rate was influenced by the type of site used, as well as by sex of the individual and local behavioural response. Scent-marking sites had on average a 1.6- and 2.5-times higher baseline detection rate compared to roads and other locations, respectively. Scent-marking behaviour is common for several mammals, and selecting sites that attracts the targeted species is used to increase detection rates, especially for rare and cryptic species. But we show that the use of different location types for camera trapping can bias density estimates if not homogenously distributed across the surveyed area. This highlights the importance of incorporating not only individual characteristics (e.g., sex), but also information on the type of site used in camera trapping surveys into estimates of population densities.
Journal Article
The flunking of Joshua T. Bates
Driving home from the beach on Labor Day, Joshua receives some shocking news from his mother: he must repeat third grade.
Book
Signal detection theory applied to giant pandas: Do pandas go out of their way to make sure their scent marks are found?
Inter‐animal communication allows signals released by an animal to be perceived by others. Scent‐marking is the primary mode of such communication in giant pandas (Ailuropoda melanoleuca). Signal detection theory propounds that animals choose the substrate and location of their scent marks so that the signals released are transmitted more widely and last longer. We believe that pandas trade‐off scent‐marking because they are an energetically marginal species and it is costly to generate and mark chemical signals. Existing studies only indicate where pandas mark more frequently, but their selection preferences remain unknown. This study investigates whether the marking behavior of pandas is consistent with signal detection theory. Feces count, reflecting habitat use intensity, was combined with mark count to determine the selection preference for marking. The results showed that pandas preferred to mark ridges with animal trails and that most marked tree species were locally dominant. In addition, marked plots and species were selected for lower energy consumption and a higher chance of being detected. Over 90% of the marks used were the longest‐surviving anogenital gland secretion marks, and over 80% of the marks were oriented toward animal trails. Our research demonstrates that pandas go out of their way to make sure their marks are found. This study not only sheds light on the mechanisms of scent‐marking by pandas but also guides us toward more precise conservation of the panda habitat.
This study provides a more rigorous approach to the study of scent marking in giant pandas and concludes that it is indeed consistent with signal detection theory.
Journal Article
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary
The Synthetic Minority Oversampling Technique (SMOTE) preprocessing algorithm is considered \"de facto\" standard in the framework of learning from imbalanced data. This is due to its simplicity in the design of the procedure, as well as its robustness when applied to different type of problems. Since its publication in 2002, SMOTE has proven successful in a variety of applications from several different domains. SMOTE has also inspired several approaches to counter the issue of class imbalance, and has also significantly contributed to new supervised learning paradigms, including multilabel classification, incremental learning, semi-supervised learning, multi-instance learning, among others. It is standard benchmark for learning from imbalanced data. It is also featured in a number of different software packages - from open source to commercial. In this paper, marking the fifteen year anniversary of SMOTE, we reflect on the SMOTE journey, discuss the current state of affairs with SMOTE, its applications, and also identify the next set of challenges to extend SMOTE for Big Data problems.
Journal Article
The internet of animals : discovering the collective intelligence of life on Earth
\"All we need to do is give animals a voice and our perception of the world could change forever. That's what author Martin Wikelski and his team of scientists believe, and this book shares their story for the first time. As they tag animals around the world with minuscule tracking devices, they link their movements to The International Space Station, which taps into the 'internet of animals': an astonishing network of information made up of thousands of animals communicating with each other and their environments. Called the International Cooperation for Animal Research Using Space, or ICARUS, this phenomenal project is poised to change our world. Down on the ground, Wikelski describes animals' sixth sense first-hand. Farm animals become restless when earthquakes are imminent. Animals on the African plains sense when poachers are on the move. Frigatebirds in South America depart before hurricanes arrive.\"-- Provided by publisher.
Book
To Hunt or Patrol? Social Composition and Location Mediate Scent Marking Decisions of a Large Carnivore
ABSTRACT
While sociality is known to mediate territorial processes, it is less clear how sociality interacts with environmental features and neighbors' location to influence habitat selection and behavior. Scent marking, a fundamental behavior in maintaining territories, can be utilized by receiving conspecifics to evaluate both encounter risk and competitive ability of the depositing individual or group. African wild dog packs were followed in the field across 2010–2021, where researchers recorded individual behaviors and pack composition, including scent marking behaviors. We combined this historical and unique behavioral dataset with co‐occurring GPS collar data to make inferences on territorial behaviors, sociality, and habitat selection across spatial scales. We performed three analyses to determine (1) the relative probability of scent mark placement, (2) the probability of scent marking, and (3) the trade‐off strategy between scent marking and hunting, as predicted by habitat, neighbors' territories, and pack social composition. Specifically, we used resource selection function frameworks to determine how and whether conspecifics influenced habitat selection and behavior at multiple orders of selection. We found that conspecifics were influential across all three analyses, and mediated the impact of habitat on scent mark placement and probability. Scent mark placement and probability were both influenced by the social composition of packs, specifically pup presence, pack size, and number of overlapping neighbors, while pack size and pack experience influenced territorial maintenance strategy. Our findings demonstrate the importance of social structure across scales of territorial processes, from larger scale habitat selection to the probability of a behavior. We demonstrate how key behavioral theories underpinning territoriality function at the scale of habitat selection and behavioral decision‐making in a free‐ranging, large carnivore. Future research should continue to incorporate sociality in understanding the habitat selection of animals.
Using a unique set of near‐continuous behavioral observations of free‐ranging wild dog packs, we combine field data with GPS locations to make inferences on how sociality mediates territorial strategies in a large carnivore. By investigating habitat selection across territorial behaviors, we make multi‐scale inferences on how inter‐ and intra‐pack structures mediate territorial maintenance.
Journal Article