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When planning abundance surveys, the impact of search intensity on the quality of the density estimates is rarely considered. We constructed a time‐budget modeling framework for abundance surveys using principles from optimal foraging theory. We link search intensity to the number of sample units surveyed, searcher detection probability, the number of detections made, and the precision of the estimated population density. This framework allowed us to determine how a searcher should behave to produce optimized density estimates. Using data collected from quadrat and removal surveys of zebra mussels (Dreissena polymorpha) in central Minnesota, we applied this framework to evaluate potential improvements. We found that by tuning searcher behavior, density estimates from removal surveys of zebra mussels could be improved by up to 60% in some cases, without changing the overall survey time. Our framework also predicts a critical population density where the best survey method switches from removal surveys at low densities to quadrat surveys at high densities, consistent with past empirical work. In addition, we provide simulation tools to apply this form of analysis to a number of other commonly used survey designs. Our results provide insights into how to improve the performance of many survey methods in high‐density environments by either tuning searcher behavior or decoupling the estimation of population density and detection probability. [ABSTRACT FROM AUTHOR]

Past research indicates that whitebark pine seeds are a critical food source for Threatened grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE). In recent decades, whitebark pine forests have declined markedly due to pine beetle infestation, invasive blister rust, and landscape-level fires. To date, no study has reliably estimated the contribution of whitebark pine seeds to the diets of grizzlies through time. We used stable isotope ratios (expressed as δ13C, δ15N, and δ34S values) measured in grizzly bear hair and their major food sources to estimate the diets of grizzlies sampled in Cooke City Basin, Montana. We found that stable isotope mixing models that included different combinations of stable isotope values for bears and their foods generated similar proportional dietary contributions. Estimates generated by our top model suggest that whitebark pine seeds (35±10%) and other plant foods (56±10%) were more important than meat (9±8%) to grizzly bears sampled in the study area. Stable isotope values measured in bear hair collected elsewhere in the GYE and North America support our conclusions about plant-based foraging. We recommend that researchers consider model selection when estimating the diets of animals using stable isotope mixing models. We also urge researchers to use the new statistical framework described here to estimate the dietary responses of grizzlies to declines in whitebark pine seeds and other important food sources through time in the GYE (e.g., cutthroat trout), as such information could be useful in predicting how the population will adapt to future environmental change.

Abundance surveys are commonly used to estimate plant or animal densities and frequently require estimating detection probabilities to account for imperfect detection. The estimation of detection probabilities requires additional measurements that take time, potentially reducing the efficiency of the survey when applied to high-density populations. We conducted quadrat, removal, and distance surveys of zebra mussels (Dreissena polymorpha) in three central Minnesota lakes and determined how much survey effort would be required to achieve a pre-specified level of precision for each abundance estimator, allowing us to directly compare survey design efficiencies across a range of conditions. We found that the required sampling effort needed to achieve our precision goal depended on both the survey design and population density. At low densities, survey designs that could cover large areas but with lower detection probabilities, such as distance surveys, were more efficient (i.e., required less sampling effort to achieve the same level of precision). However, at high densities, quadrat surveys, which tend to cover less area but with high detection rates, were more efficient. These results demonstrate that the best survey design is likely to be context-specific, requiring some prior knowledge of the underlying population density and the cost/time needed to collect additional information for estimating detection probabilities. [ABSTRACT FROM AUTHOR]

Determining the ecological mechanisms that control population abundances is an important issue for the conservation of endangered and threatened species. We examined whether a threatened bull trout (Salvelinus confluentus) population could coexist at observed levels with the ecologically similar introduced species, lake trout (Salvelinus namaycush), using a pattern-oriented analysis of population dynamics models. We used a large suite of stage- and age-structured models to examine how both competitive and predatory interactions, combined with differing life-history strategies and species vital rates, drove salmonid coexistence patterns. In our models, an ontogenetic shift in juvenile bull trout resource use was the most important factor contributing to the two species coexistence; however, this coexistence occurred with reduced abundances in bull trout that increase the chances of extirpation for the native species. Observed levels of competition were found to have stronger effects than predation on population abundances. We used a pattern-oriented modeling approach to inference; this approach assumes process models that can generate patterns similar to the observed patterns are better supported than those that cannot. This methodology may find wide use on a number of data-limited fishery management and conservation problems. La determination des mecanismes ecologiques qui controlent l'abondance des populations est un probleme important pour la conservation des especes en peril et des especes menacees. A l'aide d'une analyse basee sur les patrons des modeles de dynamique de population, nous examinons si une population menacee d'ombles a tete plate (Salvelinus confluentus) peut coexister aux densites observees en presence de l'espece introduite a ecologie semblable, le touladi (Salvelinus namaycush). Nous utilisons une importante serie de modeles structures d'apres le stade et l'age afin d'examiner comment a la fois les interactions de competition et de predation, combinees aux strategies de cycle biologique et aux taux vitaux differents des especes, expliquent les patrons de coexistence de ces salmonides. Dans nos modeles, le changement ontogenique dans l'utilisation des ressources par les jeunes ombles a tete plate est le facteur qui contribue le plus a la coexistence des deux especes; cependant, cette coexistence se fait a des abondances reduites chez l'omble a tete plate, ce qui augmente les chances d' extirpation de cette espece indigene. Les niveaux observes de competition ont des effets plus importants sur les abondances des populations que la predation. Nous utilisons une methodologie de modelisation centree sur les patrons pour etudier l' interference; cette approche presume que les modeles de processus qui peuvent produire des patrons semblables a ceux qu'on observe sont mieux appuyes que ceux qui ne le peuvent pas. Cette methodologie pourrait s'averer de grande utilite pour resoudre des problemes de gestion et de conservation dans plusieurs peches, lorsque les donnees sont limitees. [Traduit par la Redaction], Introduction Ontogenetic shifts occur in many taxa although their ecological functions are in many ways still not fully understood. In many species, size-based energy requirements necessitate that species change resource [...]

Rare species are important targets for biodiversity conservation efforts because rarity often equates to small populations and increased endangerment. Rare species are prone to stochastic extinction events and may be particularly susceptible to catastrophes. Therefore, understanding how rare species respond to disturbances is critical for evaluating extinction risk and guiding conservation managers. Population viability analyses (PVAs) are essential for assessing rare species' status yet they seldom consider catastrophic events. Accordingly, we present a PVA of a rare tropical epiphyte, Lepanthes caritensis (Orchidaceae), under simulated disturbance regimes to evaluate its demographics and extinction risk. We aimed to test how demographic models incorporating catastrophes affect population viability estimates. Our goal was to better guide management of these orchids and other rare plants. Results revealed L. caritensis numbers have declined recently, but projected growth rates indicated that most subpopulations should increase in size if undisturbed. Still, projection models show that moderate catastrophes reduce growth rates, increase stochasticity in subpopulation sizes, and elevate extinction risk. Severe catastrophes had a more pronounced effect in simulations; growth rates fell below replacement level, there was greater variation in projected population sizes, and extinction risk was significantly higher. PVAs incorporating periodic catastrophes indicate that rare species may have greater extinction probabilities than standard models suggest. Thus, precautionary conservation measures should be taken in disturbance prone settings and we encourage careful monitoring after environmental catastrophes. Future rare plant PVAs should incorporate catastrophes and aim to determine if rescue and reintroduction efforts are necessary after disturbances to insure long‐term population viability. Rare species, such as Lepanthes caritensis (Orchidaceae), often have high extinction probabilities due to their small population sizes and limited ranges. Traditional demographic models may underestimate extinction risk, however, if added sources of variation in population growth, such as catastrophes, are not incorporated. Detailed new population viability assessments of L. caritensis that incorporate effects of catastrophic events demonstrate that they can significantly increase the likelihood of extinction for rare species that may otherwise exhibit stable population growth rates. [ABSTRACT FROM AUTHOR]

Past research indicates that whitebark pine seeds are a critical food source for Threatened grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE). In recent decades, whitebark pine forests have declined markedly due to pine beetle infestation, invasive blister rust, and landscape-level fires. To date, no study has reliably estimated the contribution of whitebark pine seeds to the diets of grizzlies through time. We used stable isotope ratios (expressed as δ13C, δ15N, and δ34S values) measured in grizzly bear hair and their major food sources to estimate the diets of grizzlies sampled in Cooke City Basin, Montana. We found that stable isotope mixing models that included different combinations of stable isotope values for bears and their foods generated similar proportional dietary contributions. Estimates generated by our top model suggest that whitebark pine seeds (35±10%) and other plant foods (56±10%) were more important than meat (9±8%) to grizzly bears sampled in the study area. Stable isotope values measured in bear hair collected elsewhere in the GYE and North America support our conclusions about plant-based foraging. We recommend that researchers consider model selection when estimating the diets of animals using stable isotope mixing models. We also urge researchers to use the new statistical framework described here to estimate the dietary responses of grizzlies to declines in whitebark pine seeds and other important food sources through time in the GYE (e.g., cutthroat trout), as such information could be useful in predicting how the population will adapt to future environmental change. [ABSTRACT FROM AUTHOR]

Predicting population extinction risk is a fundamental application of ecological theory to the practice of conservation biology. Here, we compared the prediction performance of a wide array of stochastic, population dynamics models against direct observations of the extinction process from an extensive experimental data set. By varying a series of biological and statistical assumptions in the proposed models, we were able to identify the assumptions that affected predictions about population extinction. We also show how certain autocorrelation structures can emerge due to interspecific interactions, and that accounting for the stochastic effect of these interactions can improve predictions of the extinction process. We conclude that it is possible to account for the stochastic effects of community interactions on extinction when using single-species time series. [ABSTRACT FROM AUTHOR]

Large-bodied, top- and apex predators (e.g., crocodilians, sharks, wolves, killer whales) can exert strong top-down effects within ecological communities through their interactions with prey. Due to inherent difficulties while studying the behavior of these often dangerous predatory species, relatively little is known regarding their feeding behaviors and activity patterns, information that is essential to understanding their role in regulating food web dynamics and ecological processes. Here we use animal-borne imaging systems (Crittercam) to study the foraging behavior and activity patterns of a cryptic, large-bodied predator, the American alligator (Alligator mississippiensis) in two estuaries of coastal Florida, USA. Using retrieved video data we examine the variation in foraging behaviors and activity patterns due to abiotic factors. We found the frequency of prey-attacks (mean = 0.49 prey attacks/hour) as well as the probability of prey-capture success (mean = 0.52 per attack) were significantly affected by time of day. Alligators attempted to capture prey most frequently during the night. Probability of prey-capture success per attack was highest during morning hours and sequentially lower during day, night, and sunset, respectively. Position in the water column also significantly affected prey-capture success, as individuals’ experienced two-fold greater success when attacking prey while submerged. These estimates are the first for wild adult American alligators and one of the few examples for any crocodilian species worldwide. More broadly, these results reveal that our understandings of crocodilian foraging behaviors are biased due to previous studies containing limited observations of cryptic and nocturnal foraging interactions. Our results can be used to inform greater understanding regarding the top-down effects of American alligators in estuarine food webs. Additionally, our results highlight the importance and power of using animal-borne imaging when studying the behavior of elusive large-bodied, apex predators, as it provides critical insights into their trophic and behavioral interactions. [ABSTRACT FROM AUTHOR]

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Large-bodied, top- and apex predators (e.g., crocodilians, sharks, wolves, killer whales) can exert strong top-down effects within ecological communities through their interactions with prey. Due to inherent difficulties while studying the behavior of these often dangerous predatory species, relatively little is known regarding their feeding behaviors and activity patterns, information that is essential to understanding their role in regulating food web dynamics and ecological processes. Here we use animal-borne imaging systems (Crittercam) to study the foraging behavior and activity patterns of a cryptic, large-bodied predator, the American alligator (Alligator mississippiensis) in two estuaries of coastal Florida, USA. Using retrieved video data we examine the variation in foraging behaviors and activity patterns due to abiotic factors. We found the frequency of prey-attacks (mean = 0.49 prey attacks/hour) as well as the probability of prey-capture success (mean = 0.52 per attack) were significantly affected by time of day. Alligators attempted to capture prey most frequently during the night. Probability of prey-capture success per attack was highest during morning hours and sequentially lower during day, night, and sunset, respectively. Position in the water column also significantly affected prey-capture success, as individuals’ experienced two-fold greater success when attacking prey while submerged. These estimates are the first for wild adult American alligators and one of the few examples for any crocodilian species worldwide. More broadly, these results reveal that our understandings of crocodilian foraging behaviors are biased due to previous studies containing limited observations of cryptic and nocturnal foraging interactions. Our results can be used to inform greater understanding regarding the top-down effects of American alligators in estuarine food webs. Additionally, our results highlight the importance and power of using animal-borne imaging when studying the behavior of elusive large-bodied, apex predators, as it provides critical insights into their trophic and behavioral interactions. [ABSTRACT FROM AUTHOR]

Understanding how populations respond to increasingly variable conditions is a major objective for natural resource managers forecasting extinction risk. The lesson from current modelling is clear: increasing environmental variability increases population abundance variability. We show that this paradigm fails to describe a broad class of empirically observed dynamics, namely endogenously driven population cycles. In contrast to the dominant paradigm, these populations can exhibit reduced long-run population variance under increasing environmental variability. We provide evidence for a mechanistic explanation of this phenomenon that relies on how stochasticity interacts with long transient dynamics present in the deterministic cycling model. This interaction stands in contrast to the often assumed additivity of stochastic and deterministic drivers of population fluctuations. We show evidence for the phenomenon in two cyclical populations: flour beetles and Canadian lynx. We quantify the impact of the phenomenon with new theory that partitions the effects of nonlinear dynamics and stochastic variation on dynamical systems. In both empirical examples, the partitioning shows that the interaction between deterministic and stochastic dynamics reduces the variance in population size. Our results highlight that previous predictions about extinction under environmental variability may prove inadequate to understand the effects of climate change in some populations., Competing Interests: The authors declare no competing interests related to this work., (© 2024 The Author(s).)

Objective: The article proposes a set of metrics for evaluation of patient performance in physical therapy exercises., Methods: Taxonomy is employed that classifies the metrics into quantitative and qualitative categories, based on the level of abstraction of the captured motion sequences. Further, the quantitative metrics are classified into model-less and model-based metrics, in reference to whether the evaluation employs the raw measurements of patient performed motions, or whether the evaluation is based on a mathematical model of the motions. The reviewed metrics include root-mean square distance, Kullback Leibler divergence, log-likelihood, heuristic consistency, Fugl-Meyer Assessment, and similar., Results: The metrics are evaluated for a set of five human motions captured with a Kinect sensor., Conclusion: The metrics can potentially be integrated into a system that employs machine learning for modelling and assessment of the consistency of patient performance in home-based therapy setting. Automated performance evaluation can overcome the inherent subjectivity in human performed therapy assessment, and it can increase the adherence to prescribed therapy plans, and reduce healthcare costs.