Integrative and Comparative Biology最新文献

Insects exhibit remarkable adaptability in their locomotive strategies in diverse environments, a crucial trait for foraging, survival, and predator avoidance. Microvelia americana, tiny 2-3 mm insects that adeptly walk on water surfaces, exemplify this adaptability by using the alternating tripod gait in both aquatic and terrestrial terrains. These insects commonly inhabit low-flow ponds and streams cluttered with natural debris like leaves, twigs, and duckweed. Using high-speed imaging and pose-estimation software, we analyze M. americana movement on water, sandpaper (simulating land), and varying duckweed densities (10%, 25%, and 50% coverage). Our results reveal M. americana maintain consistent joint angles and strides of their upper and hind legs across all duckweed coverages, mirroring those seen on sandpaper. Microvelia americana adjust the stride length of their middle legs based on the amount of duckweed present, decreasing with increased duckweed coverage and at 50% duckweed coverage, their middle legs' strides closely mimic their strides on sandpaper. Notably, M. americana achieve speeds up to 56 body lengths per second on the deformable surface of water, nearly double those observed on sandpaper and duckweed, which are rough, heterogeneous surfaces. This study highlights M. americana's ecological adaptability, setting the stage for advancements in amphibious robotics that emulate their unique tripod gait for navigating complex terrains.

Shark skin is composed of denticles, or complex scale-like features, which have been shown to reduce drag in turbulent and laminar flow. The denticle crown features undulating structures called riblets that interact with the turbulent boundary layer to reduce drag. Two mechanisms thought to contribute to the drag-reducing properties of riblets include the lifting of streamwise vortices and the hampering of spanwise vortex interactions to reduce crossflow, which could translate to similar flow mechanisms for denticles. Because of the varied morphologies of dermal denticles on different shark species, which also depend on body location, the impact of these denticle geometries on flow is of interest to the biology community, including related fields such as fluid mechanics and oceanography. This review highlights the past 15 years of manufacturing techniques and experimental measurements of drag over denticle-inspired surface structures, including real shark skin samples and engineered denticles and riblets. State-of-the-art additive manufacturing and other techniques are primarily limited to mm-length denticle scales, which have demonstrated drag reduction in lower flow speeds, under 1 m s-1. New manufacturing approaches can create sub-mm length denticles and nanotextured surface structures, which have achieved reported drag reductions of up to 31%. We synthesize results from the literature to illustrate the drag reduction properties of bioinspired denticles and riblets according to their geometry and flow conditions. Using these trends, we suggest design features and focus areas for future research, such as increasing studies of different denticle morphologies, hydrophobicity, antifouling properties, and acoustic noise reduction. Continued work on bioinspired denticles for drag reduction has wider implications in comparative biology and applications to design more energy-efficient, persistent vehicles for environmental monitoring.

Pursuing cutting edge questions in organismal biology in the future will require novel approaches for training the next generation of organismal biologists, including knowledge and use of systems-type modeling combined with integrative organismal biology. We link agendas recommending changes in science education and practice across three levels: Broadening the concept of organismal biology to promote modeling organisms as systems interacting with higher and lower organizational levels; enhancing undergraduate science education to improve applications of quantitative reasoning and modeling in the scientific process; and K-12 curricula based on Next Generation Science Standards emphasizing development and use of models in the context of explanatory science, solution design, and evaluating and communicating information. Out of each of these initiatives emerges an emphasis on routine use of models as tools for hypothesis testing and prediction. The question remains, however, what is the best approach for training the next generation of organismal biology students to facilitate their understanding and use of models? We address this question by proposing new ways of teaching and learning, including the development of interactive web-based modeling modules that lower barriers for scientists approaching this new way of imagining and conducting integrative organismal biology.

In the era of big data, ecological research is experiencing a transformative shift, yet big-data advancements in thermal ecology and the study of animal responses to climate conditions remain limited. This review discusses how big data analytics and artificial intelligence (AI) can significantly enhance our understanding of microclimates and animal behaviors under changing climatic conditions. We explore AI's potential to refine microclimate models and analyze data from advanced sensors and camera technologies, which capture detailed, high-resolution information. This integration can allow researchers to dissect complex ecological and physiological processes with unprecedented precision. We describe how AI can enhance microclimate modeling through improved bias correction and downscaling techniques, providing more accurate estimates of the conditions that animals face under various climate scenarios. Additionally, we explore AI's capabilities in tracking animal responses to these conditions, particularly through innovative classification models that utilize sensors such as accelerometers and acoustic loggers. For example, the widespread usage of camera traps can benefit from AI-driven image classification models to accurately identify thermoregulatory responses, such as shade usage and panting. AI is therefore instrumental in monitoring how animals interact with their environments, offering vital insights into their adaptive behaviors. Finally, we discuss how these advanced data-driven approaches can inform and enhance conservation strategies. In particular, detailed mapping of microhabitats essential for species survival under adverse conditions can guide the design of climate-resilient conservation and restoration programs that prioritize habitat features crucial for biodiversity resilience. In conclusion, the convergence of AI, big data, and ecological science heralds a new era of precision conservation, essential for addressing the global environmental challenges of the 21st century.

Predicting performance responses of insects to climate change is crucial for biodiversity conservation and pest management. While most projections on insects' performance under climate change have used macro-scale weather station data, few incorporated the microclimates within vegetation that insects inhabit and their feeding behaviors (e.g., leaf-nesting: building leaf nests or feeding inside). Here, taking advantage of relatively homogenous vegetation structures in agricultural fields, we built microclimate models to examine fine-scale air temperatures within two important crop systems (maize and rice) and compared microclimate air temperatures to temperatures from weather stations. We deployed physical models of caterpillars and quantified effects of leaf-nesting behavior on operative temperatures of two Lepidoptera pests: Ostrinia furnacalis (Pyralidae) and Cnaphalocrocis medinalis (Crambidae). We built temperature-growth rate curves and predicted the growth rate of caterpillars with and without leaf-nesting behavior based on downscaled microclimate changes under different climate change scenarios. We identified widespread differences between microclimates in our crop systems and air temperatures reported by local weather stations. Leaf-nesting individuals in general had much lower body temperatures compared to non-leaf-nesting individuals. When considering microclimates, we predicted leaf-nesting individuals grow slower compared to non-leaf-nesting individuals with rising temperature. Our findings highlight the importance of considering microclimate and habitat-modifying behavior in predicting performance responses to climate change. Understanding the thermal biology of pests and other insects would allow us to make more accurate projections on crop yields and biodiversity responses to environmental changes.

Many animals migrate across regions of their geographic range as part of extended events, with groups of individuals proceeding through areas of travel on several successive days. Early migrating individuals may have an advantage over late migrating individuals by gaining early access to the resources at the eventual destination. For situations where early access to resources would provide an advantage, specific sets of locomotor traits might be found among individuals that are earlier migrators. We tested for associations between migration timing and traits related to escape responses, climbing, and morphology in the amphidromous Hawaiian stream goby, 'o'opu nōpili (Sicyopterus stimpsoni). In this species, juvenile fish migrate in pulses over several days immediately following flash floods. We collected daily measurements of escape responses and waterfall climbing from juvenile fish arriving at streams from the ocean. We found that escape performance showed mainly stochastic variation across migrating individuals tested on successive days. In contrast, some metrics of climbing performance decrease over successive pulses during a migration event. We also found more variation in body shape among fish from early pulses during migration events compared to later in pulses. These results could have implications for guiding conservation efforts, identifying critical time windows for protection as periods with the greatest likelihood of successful migrants.

A central question in ecology is to what extent do trophic interactions govern the structure and function of communities? This question is becoming more pressing as trophic interactions shift with rapid climate change. Sea urchins and abalone are key invertebrates in the habitats where they reside. Sea urchins are critical members of exemplar trophic cascades in kelp forests due to their impact on kelp establishment and maintenance; yet their populations are controlled by predators, such as sea otters and sunflower sea stars. Abalone compete with urchins for macroalgal food resources and therefore can help regulate urchin populations in kelp forests. Given that both urchin tests and abalone shells used for predator defense are comprised of calcium carbonate, much research has been conducted on the impacts of ocean acidification (OA) on these calcified structures. A growing body of literature has shown that urchin tests are less calcified and break with less force under OA conditions. Less is known about abalone, but their shells also appear to respond negatively to OA. Using kelp forest communities as exemplar ecosystems, we discuss the morphological, biomechanical, and physiological responses to OA in urchins and abalone and consider how these individual level responses scale to trophic interactions and ultimately whole ecosystem processes. Although the impacts of OA on the calcified structures used for defense have been well studied, calcified mechanisms for food consumption, such as the Aristotle's lantern of urchins, are much less understood. Thus, examining both the feeding and defense sides of trophic interactions would greatly improve our understanding of OA responses across individual to ecosystem scales. More generally, measurements of morphological, biomechanical, and physiological responses to OA can be made in individuals to help predict higher level ecological responses, which would greatly contribute to broader predictions of whole ecosystem responses to OA.

Fishes use their mechanosensory lateral line (LL) system to detect local water flows in different behavioral contexts, including the detection of prey. The LL system is comprised of neuromast receptor organs on the skin (superficial neuromasts) and within bony canals (canal neuromasts). Most fishes have one cranial LL canal phenotype, but the silverjaw minnow (Ericymba buccata) has two: narrow canals dorsal and caudal to the eye and widened canals ventral to the eye and along the mandible. The ventrally directed widened LL canals have been hypothesized to be an adaptation for detection of their benthic prey. Multiple morphological methods were used to describe the narrow and widened canals and canal neuromasts in detail. The primary distribution of hundreds of superficial neuromasts and taste buds ventral to the eye and on the mandible (described here for the first time) suggests additional sensory investment for detecting flow and chemical stimuli emanating from benthic prey. The hypothesis that the LL system mediates prey localization was tested by measuring five parameters in behavioral trials in which the combination of sensory modalities available to fish was manipulated (four experimental treatments). Fish detected and localized prey regardless of available sensory modalities and they were able to detect prey in the dark in the absence of LL input (LL ablation with neomycin sulfate) revealing that chemoreception was sufficient to mediate benthic prey detection, localization, and consumption. However, elimination of LL input resulted in a change in the angle of approach to live (mobile) prey even when visual input was available, suggesting that mechanosensory input contributes to the successful detection and localization of prey. The results of this study demonstrate that the extraordinary LL canal system of the silverjaw minnow, in addition to the large number of superficial neuromasts, and the presence of numerous extraoral taste buds, likely represent adaptations for multimodal integration of sensory inputs contributing to foraging behavior in this species. The morphological and behavioral results of this study both suggest that this species would be an excellent model for future comparative structural and functional studies of sensory systems in fishes.

Climate change is accelerating the increase of temperatures across the planet and resulting in the warming of oceans. Ocean warming threatens the survival of many aquatic species, including squids, and has introduced physiological, behavioral, and developmental changes, as well as physical changes in their biological materials composition, structure, and properties. Here, we characterize and analyze how the structure, morphology, and mechanical properties of European common squid Loligo vulgaris sucker ring teeth (SRT) are affected by temperature. SRT are predatory teethed structures located inside the suction cups of squids that are used to capture prey and are composed of semicrystalline structural proteins with a high modulus (GPa-range). We observed here that this biological material reversibly softens with temperature, undergoing a glass transition at ∼35°C, to a MPa-range modulus. We analyzed the SRT protein nanostructures as a function of temperature, as well as microscale and macroscale morphological changes, to understand their impact in the material properties. The results suggested that even small deviations from their habitat temperatures can result in significant softening of the material (up to 40% in modulus loss). Temperature changes following recent global climate trends and predictions might affect environmental adaptation in squid species and pose emerging survival challenges to adapt to increasing ocean temperatures.