Gentrification drives patterns of alpha and beta diversity in cities.

While there is increasing recognition that social processes in cities like gentrification have ecological consequences, we lack nuanced understanding of the ways gentrification affects urban biodiversity. We analyzed a large camera trap dataset of mammals (>500 g) to evaluate how gentrification impacts species richness and community composition across 23 US cities. After controlling for the negative effect of impervious cover, gentrified parts of cities had the highest mammal species richness. Change in community composition was associated with gentrification in a few cities, which were mostly located along the West Coast. At the species level, roughly half (11 of 21 mammals) had higher occupancy in gentrified parts of a city, especially when impervious cover was low. Our results indicate that the impacts of gentrification extend to nonhuman animals, which provides further evidence that some aspects of nature in cities, such as wildlife, are chronically inaccessible to marginalized human populations.

Using global remote camera data of a solitary species complex to evaluate the drivers of group formation.

The social system of animals involves a complex interplay between physiology, natural history, and the environment. Long relied upon discrete categorizations of "social" and "solitary" inhibit our capacity to understand species and their interactions with the world around them. Here, we use a globally distributed camera trapping dataset to test the drivers of aggregating into groups in a species complex (martens and relatives, family Mustelidae, Order Carnivora) assumed to be obligately solitary. We use a simple quantification, the probability of being detected in a group, that was applied across our globally derived camera trap dataset. Using a series of binomial generalized mixed-effects models applied to a dataset of 16,483 independent detections across 17 countries on four continents we test explicit hypotheses about potential drivers of group formation. We observe a wide range of probabilities of being detected in groups within the solitary model system, with the probability of aggregating in groups varying by more than an order of magnitude. We demonstrate that a species' context-dependent proclivity toward aggregating in groups is underpinned by a range of resource-related factors, primarily the distribution of resources, with increasing patchiness of resources facilitating group formation, as well as interactions between environmental conditions (resource constancy/winter severity) and physiology (energy storage capabilities). The wide variation in propensities to aggregate with conspecifics observed here highlights how continued failure to recognize complexities in the social behaviors of apparently solitary species limits our understanding not only of the individual species but also the causes and consequences of group formation.

The racial composition of road users, traffic citations, and police stops.

This paper exploits the potential of Global Positioning System datasets sourced from mobile phones to estimate the racial composition of road users, leveraging data from their respective Census block group. The racial composition data encompasses approximately 46 million trips in the Chicago metropolitan region. The research focuses on the relationship between camera tickets and racial composition of drivers vs. police stops for traffic citations and the racial composition in these locations. Black drivers exhibit a higher likelihood of being ticketed by automated speed cameras and of being stopped for moving violations on roads, irrespective of the proportion of White drivers present. The research observes that this correlation attenuates as the proportion of White drivers on the road increases. The citation rate measured by cameras better matches the racial composition of road users on the links with cameras than do stops by police officers. This study therefore presents an important contribution to understanding racial disparities in moving violation stops, with implications for policy interventions and social justice reforms.

REVEALS: an open-source multi-camera GUI for rodent behavior acquisition.

Deciphering the rich repertoire of mouse behavior is crucial for understanding the functions of both the healthy and diseased brain. However, the current landscape lacks effective, affordable, and accessible methods for acquiring such data, especially when employing multiple cameras simultaneously. We have developed REVEALS (Rodent Behavior Multi-Camera Laboratory Acquisition), a graphical user interface for acquiring rodent behavioral data via commonly used USB3 cameras. REVEALS allows for user-friendly control of recording from one or multiple cameras simultaneously while streamlining the data acquisition process, enabling researchers to collect and analyze large datasets efficiently. We release this software package as a stand-alone, open-source framework for researchers to use and modify according to their needs. We describe the details of the graphical user interface implementation, including the camera control software and the video recording functionality. We validate results demonstrating the graphical user interface's stability, reliability, and accuracy for capturing rodent behavior using DeepLabCut in various behavioral tasks. REVEALS can be incorporated into existing DeepLabCut, MoSeq, or other custom pipelines to analyze complex behavior. In summary, REVEALS offers an interface for collecting behavioral data from single or multiple perspectives, which, when combined with deep learning algorithms, enables the scientific community to identify and characterize complex behavioral phenotypes.

Human disturbance compresses the spatiotemporal niche.

Human disturbance may fundamentally alter the way that species interact, a prospect that remains poorly understood. We investigated whether anthropogenic landscape modification increases or decreases co-occurrence-a prerequisite for species interactions-within wildlife communities. Using 4 y of data from >2,000 camera traps across a human disturbance gradient in Wisconsin, USA, we considered 74 species pairs (classifying pairs as low, medium, or high antagonism to account for different interaction types) and used the time between successive detections of pairs as a measure of their co-occurrence probability and to define co-occurrence networks. Pairs averaged 6.1 [95% CI: 5.3, 6.8] d between detections in low-disturbance landscapes (e.g., national forests) but 4.1 [3.5, 4.7] d between detections in high-disturbance landscapes, such as those dominated by urbanization or intensive agriculture. Co-occurrence networks showed higher connectance (i.e., a larger proportion of the possible co-occurrences) and greater proportions of low-antagonism pairs in disturbed landscapes. Human-mediated increases in species abundance (possibly via resource subsidies) appeared more important than behavioral mechanisms (e.g., changes in daily activity timing) in driving these patterns of compressed co-occurrence in disturbed landscapes. The spatiotemporal compression of species co-occurrences in disturbed landscapes likely strengthens interactions like competition, predation, and infection unless species can avoid each other at fine spatiotemporal scales. Regardless, human-mediated increases in co-occurrence with-and hence increased exposure to-predators or competitors might elevate stress levels in individual animals, with possible cascading effects across populations, communities, and ecosystems.

Nanoporous Submicron Gold Particles Enable Nanoparticle-Based Localization Optoacoustic Tomography (nanoLOT).

Localization optoacoustic tomography (LOT) has recently emerged as a transformative super-resolution technique breaking through the acoustic diffraction limit in deep-tissue optoacoustic (OA) imaging via individual localization and tracking of particles in the bloodstream. However, strong light absorption in red blood cells has previously restricted per-particle OA detection to relatively large microparticles, ≈5 µm in diameter. Herein, it is demonstrated that submicron-sized porous gold nanoparticles, ≈600 nm in diameter, can be individually detected for noninvasive super-resolution imaging with LOT. Ultra-high-speed bright-field microscopy revealed that these nanoparticles generate microscopic plasmonic vapor bubbles, significantly enhancing opto-acoustic energy conversion through a nano-to-micro size transformation. Comprehensive in vitro and in vivo tests further demonstrated the biocompatibility and biosafety of the particles. By reducing the detectable particle size by an order of magnitude, nanoLOT enables microangiographic imaging with a significantly reduced risk of embolisms from particle aggregation and opens new avenues to visualize how nanoparticles reach vascular and potentially extravascular targets. The performance of nanoLOT for non-invasive imaging of microvascular networks in the murine brain anticipates new insights into neurovascular coupling mechanisms and longitudinal microcirculatory changes associated with neurodegenerative diseases.

The moon's influence on the activity of tropical forest mammals.

Changes in lunar illumination alter the balance of risks and opportunities for animals, influencing activity patterns and species interactions. We examined if and how terrestrial mammals respond to the lunar cycle in some of the darkest places: the floors of tropical forests. We analysed long-term camera trapping data on 86 mammal species from 17 protected forests on three continents. Conservative categorization of activity during the night revealed pronounced avoidance of moonlight (lunar phobia) in 12 species, compared with pronounced attraction to moonlight (lunar philia) in only three species. However, half of all species in our study responded to lunar phases, either changing how nocturnal they were, altering their overall level of activity, or both. Avoidance of full moon was more common, exhibited by 30% of all species compared with 20% of species that exhibited attraction. Nocturnal species, especially rodents, were over-represented among species that avoided full moon. Artiodactyla were more prominent among species attracted to full moon. Our findings indicate that lunar phases influence animal behaviour even beneath the forest canopy. Such impacts may be exacerbated in degraded and fragmented forests. Our study offers a baseline representing relatively intact and well-protected contexts together with an intuitive approach for detecting activity shifts in response to environmental change.

The influence of habitat alteration is widespread, but the impact of climate cannot continue to be discounted.

In Dickie et al. (2024), we contrasted the effects of climate and habitat alteration on white-tailed deer density, recognizing the role of both these factors. Barnas et al.'s (2024) critique raised concerns about data transformations, model overfitting, and inference methods, but our analysis demonstrates that these criticisms are either unfounded or align with our original conclusions. We reaffirm that while both climate and habitat alteration contribute to deer densities, management decisions cannot ignore the strong role of climate, which is only predicted to increase in coming decades.

Habitat alteration or climate: What drives the densities of an invading ungulate?

Anthropogenic habitat alteration and climate change are two well-known contributors to biodiversity loss through changes to species distribution and abundance; yet, disentangling the effects of these two factors is often hindered by their inherent confound across both space and time. We leveraged a contrast in habitat alteration associated with the jurisdictional boundary between two Canadian provinces to evaluate the relative effects of spatial variation in habitat alteration and climate on white-tailed deer (Odocoileus virginianus) densities. White-tailed deer are an invading ungulate across much of North America, whose expansion into Canada's boreal forest is implicated in the decline of boreal caribou (Rangifer tarandus caribou), a species listed as Threatened in Canada. We estimated white-tailed deer densities using 300 remote cameras across 12 replicated 50 km2 landscapes over 5 years. White-tailed deer densities were significantly lower in areas where winter severity was higher. For example, predicted deer densities declined from 1.83 to 0.35 deer/km2 when winter severity increased from the lowest value to the median value. There was a tendency for densities to increase with increasing habitat alteration; however, the magnitude of this effect was approximately half that of climate. Our findings suggest that climate is the primary driver of white-tailed deer populations; however, understanding the mechanisms underpinning this relationship requires further study of over-winter survival and fecundity. Long-term monitoring at the invasion front is needed to evaluate the drivers of abundance over time, particularly given the unpredictability of climate change and increasing prevalence of extreme weather events.

Nature 4.0: A networked sensor system for integrated biodiversity monitoring.

Ecosystem functions and services are severely threatened by unprecedented global loss in biodiversity. To counteract these trends, it is essential to develop systems to monitor changes in biodiversity for planning, evaluating, and implementing conservation and mitigation actions. However, the implementation of monitoring systems suffers from a trade-off between grain (i.e., the level of detail), extent (i.e., the number of study sites), and temporal repetition. Here, we present an applied and realized networked sensor system for integrated biodiversity monitoring in the Nature 4.0 project as a solution to these challenges, which considers plants and animals not only as targets of investigation, but also as parts of the modular sensor network by carrying sensors. Our networked sensor system consists of three main closely interlinked components with a modular structure: sensors, data transmission, and data storage, which are integrated into pipelines for automated biodiversity monitoring. We present our own real-world examples of applications, share our experiences in operating them, and provide our collected open data. Our flexible, low-cost, and open-source solutions can be applied for monitoring individual and multiple terrestrial plants and animals as well as their interactions. Ultimately, our system can also be applied to area-wide ecosystem mapping tasks, thereby providing an exemplary cost-efficient and powerful solution for biodiversity monitoring. Building upon our experiences in the Nature 4.0 project, we identified ten key challenges that need to be addressed to better understand and counteract the ongoing loss of biodiversity using networked sensor systems. To tackle these challenges, interdisciplinary collaboration, additional research, and practical solutions are necessary to enhance the capability and applicability of networked sensor systems for researchers and practitioners, ultimately further helping to ensure the sustainable management of ecosystems and the provision of ecosystem services.

Ultra-fast whole-body bone tomoscintigraphies achieved with a high-sensitivity 360° CZT camera and a dedicated deep-learning noise reduction algorithm.

This study aimed to determine whether the whole-body bone Single Photon Emission Computed Tomography (SPECT) recording times of around 10 min, routinely provided by a high-sensitivity 360° cadmium and zinc telluride (CZT) camera, can be further reduced by a deep-learning noise reduction (DLNR) algorithm. METHODS: DLNR was applied on whole-body images recorded after the injection of 545 ± 33 MBq of [99mTc]Tc-HDP in 19 patients (14 with bone metastasis) and reconstructed with 100%, 90%, 80%, 70%, 60%, 50%, 40%, and 30% of the original SPECT recording times. RESULTS: Irrespective of recording time, DLNR enhanced the contrast-to-noise ratios and slightly decreased the standardized uptake values of bone lesions. Except in one markedly obese patient, the quality of DLNR processed images remained good-to-excellent down to 60% of the recording time, corresponding to around 6 min SPECT-recording. CONCLUSION: Ultra-fast SPECT recordings of 6 min can be achieved when DLNR is applied on whole-body bone 360° CZT-SPECT.

Integrating optical and electrical sensing with machine learning for advanced particle characterization.

Particle classification plays a crucial role in various scientific and technological applications, such as differentiating between bacteria and viruses in healthcare applications or identifying and classifying cancer cells. This technique requires accurate and efficient analysis of particle properties. In this study, we investigated the integration of electrical and optical features through a multimodal approach for particle classification. Machine learning classifier algorithms were applied to evaluate the impact of combining these measurements. Our results demonstrate the superiority of the multimodal approach over analyzing electrical or optical features independently. We achieved an average test accuracy of 94.9% by integrating both modalities, compared to 66.4% for electrical features alone and 90.7% for optical features alone. This highlights the complementary nature of electrical and optical information and its potential for enhancing classification performance. By leveraging electrical sensing and optical imaging techniques, our multimodal approach provides deeper insights into particle properties and offers a more comprehensive understanding of complex biological systems.

Human activities reshape the spatial overlap between North Chinese leopard and its wild ungulate prey.

BACKGROUND: Rapidly expanding human activities have profoundly changed the habitat use of both large carnivores and their prey, but whether and how human activities affect the interactions between them has received relatively less attention. In this study, we conducted a systematically designed camera-trapping survey on an endangered large carnivore (North Chinese leopard Panthera pardus japonensis) and its wild ungulate prey (Siberian roe deer Capreolus pygargus and wild boar Sus scrofa) in the Taihang Mountains of central North China. Using conditional two-species occupancy model based on data derived from the extensive sampling effort (15,654 camera-days at 102 camera sites), we examined the relationship of spatial use between leopards and each prey species under the effects of human presence, free-ranging cattle, roads and settlements. RESULTS: Humans and cattle had contrasting effects on the relationship of spatial use between leopard and roe deer, with higher and lower spatial segregation between them at human and cattle-frequented sites, respectively. Roads might create a shelter for wild boar from leopard predation, with less spatial segregation between them at sites close to the roads. CONCLUSIONS: Our findings demonstrate that human activities are reshaping the spatial overlap between large carnivores and their prey, and have non-equivalent effects among different types of human activity. Such effects may further alter the strength of interspecific interactions between predator and prey, with far-reaching influences on the community and ecosystem that require more research.

A flexible framework for spatial capture-recapture with unknown identities.

Camera traps or acoustic recorders are often used to sample wildlife populations. When animals can be individually identified, these data can be used with spatial capture-recapture (SCR) methods to assess populations. However, obtaining animal identities is often labor-intensive and not always possible for all detected animals. To address this problem, we formulate SCR, including acoustic SCR, as a marked Poisson process, comprising a single counting process for the detections of all animals and a mark distribution for what is observed (eg, animal identity, detector location). The counting process applies equally when it is animals appearing in front of camera traps and when vocalizations are captured by microphones, although the definition of a mark changes. When animals cannot be uniquely identified, the observed marks arise from a mixture of mark distributions defined by the animal activity centers and additional characteristics. Our method generalizes existing latent identity SCR models and provides an integrated framework that includes acoustic SCR. We apply our method to estimate density from a camera trap study of fisher (Pekania pennanti) and an acoustic survey of Cape Peninsula moss frog (Arthroleptella lightfooti). We also test it through simulation. We find latent identity SCR with additional marks such as sex or time of arrival to be a reliable method for estimating animal density.

Disturbance-mediated changes to boreal mammal spatial networks in industrializing landscapes.

Compound effects of anthropogenic disturbances on wildlife emerge through a complex network of direct responses and species interactions. Land-use changes driven by energy and forestry industries are known to disrupt predator-prey dynamics in boreal ecosystems, yet how these disturbance effects propagate across mammal communities remains uncertain. Using structural equation modeling, we tested disturbance-mediated pathways governing the spatial structure of multipredator multiprey boreal mammal networks across a landscape-scale disturbance gradient within Canada's Athabasca oil sands region. Linear disturbances had pervasive direct effects, increasing site use for all focal species, except black bears and threatened caribou, in at least one landscape. Conversely, block (polygonal) disturbance effects were negative but less common. Indirect disturbance effects were widespread and mediated by caribou avoidance of wolves, tracking of primary prey by subordinate predators, and intraguild dependencies among predators and large prey. Context-dependent responses to linear disturbances were most common among prey and within the landscape with intermediate disturbance. Our research suggests that industrial disturbances directly affect a suite of boreal mammals by altering forage availability and movement, leading to indirect effects across a range of interacting predators and prey, including the keystone snowshoe hare. The complexity of network-level direct and indirect disturbance effects reinforces calls for increased investment in addressing habitat degradation as the root cause of threatened species declines and broader ecosystem change.

Leveraging camera traps and artificial intelligence to explore thermoregulation behaviour.

Behavioural thermoregulation has critical ecological and physiological consequences that profoundly influence individual fitness and species distributions, particularly in the context of climate change. However, field monitoring of this behaviour remains labour-intensive and time-consuming. With the rise of camera-based surveys and artificial intelligence (AI) approaches in computer vision, we should try to build better tools for characterizing animals' behavioural thermoregulation. In this study, we developed a deep learning framework to automate the detection and classification of thermoregulation behaviour. We used lizards, the Rough-tail rock agama (Laudakia vulgaris), as a model animal for thermoregulation. We colour-marked the lizards and curated a diverse dataset of images captured by trail cameras under semi-natural conditions. Subsequently, we trained an object-detection model to identify lizards and image classification models to determine their microclimate usage (activity in sun or shade), which may indicate thermoregulation preferences. We then evaluated the performance of each model and analysed how the classification of thermoregulating lizards performed under different solar conditions (sun or shade), times of day and marking colours. Our framework's models achieved high scores in several performance metrics. The behavioural thermoregulation classification model performed significantly better on sun-basking lizards, achieving the highest classification accuracy with white-marked lizards. Moreover, the hours of activity and the microclimate choices (sun vs shade-seeking behaviour) of lizards, generated by our framework, are closely aligned with manually annotated data. Our study underscores the potential of AI in effectively tracking behavioural thermoregulation, offering a promising new direction for camera trap studies. This approach can potentially reduce the labour and time associated with ecological data collection and analysis and help gain a deeper understanding of species' thermal preferences and risks of climate change on species behaviour.

Duo photoprotective effect via silica-coated zinc oxide nanoparticles and Vitamin C nanovesicles composites.

OBJECTIVE: Zinc Oxide nanoparticles (ZnO NPs) are used widely in nowadays personal care products, especially sunscreens, as a protector against UV irradiation. Yet, they have some reports of potential toxicity. Silica is widely used to cage ZnO NPs to reduce their potential toxicity. Vitamin C derivative, Magnesium Ascorpyl Phosphate (MAP), is a potent antioxidant that can efficiently protect human skin from harmful impacts of UV irradiation and oxidative stress. The combination of silica coated ZnO NPs and MAP nanovesicles could have potential synergistic protective effect against skin photodamage. METHODS: Silica coated ZnO NPs and MAP nanovesicles (ethosomes and niosomes) were synthesized, formulated, and evaluated as topical gels. These gel formulations were evaluated in mice for their photoprotective effect against UV irradiation through histopathology and immuno-histochemistry study. Split-face clinical study was conducted to compare the effect of application of silica coated ZnO NPs either alone or combined with MAP nanovesicles. Their photoprotective action was evaluated, using Antera 3D® camera, for melanin level, roughness index and wrinkles depth. RESULTS: Silica coated ZnO NPs when combined with MAP nanovesicles protected mice skin from UV irradiation and decreased the expression of the proinflammatory cytokines, NF-κB. Clinically, silica coated ZnO NPs, alone or combined with MAP nanovesicles, could have significant effect to decrease melanin level, roughness index and wrinkles depth with higher effect for the combination. CONCLUSION: A composite of silica coated ZnO NPs and MAP nanovesicles could be a promising cosmetic formulation for skin protection against photodamage signs such as hyperpigmentation, roughness, and wrinkles.

Time for a paradigm shift? Small carnivores' sensitivity highlights the importance of monitoring mid-rank predators in future global change studies.

Research Highlight: Jachowski, D. S., Marneweck, C. J., Olfenbuttel, C., & Harris, S. N. (2024). Support for the size-mediated sensitivity hypothesis within a diverse carnivore community. Journal of Animal Ecology, https://doi.org/10.1111/1365-2656.13916. A current paradigm in ecological research suggests that top predators are suitable sentinel species to identify ecosystem dysfunctions and monitor the effects of climate change. However, the adequacy of top predators to systematically take this function may be mistakenly inferred or unintentionally conflated from the fact that these species are regarded as biodiversity indicators or keystone, umbrella and flagship species in most ecosystems. Regarding terrestrial mammalian carnivores (order Carnivora), some researchers recently suggested that the smaller species likely possess a higher sensitivity to environmental changes than large carnivores because of their biological attributes and their intermediate position in food webs. To test this hypothesis, Jachowski et al. (2024) used camera trapping followed by occupancy and structural equation modelling to explore the dynamics of a diverse carnivore community and the factors that influence them. Their results confirmed that small carnivores are more sensitive to habitat changes and are interconnected by a greater number of significant pathways compared with larger carnivores. This support for the size-mediated sensitivity hypothesis strengthens the proposition that small carnivores (and other mid-rank predators) are ideal sentinel species for monitoring the effects of the wide range of contemporary and future environmental changes. Time will tell whether this new 'middle-out ecology' paradigm will be considered in future global change studies.

Infection risk associated with carnivore carcasses may govern trophic interactions between maggots and insectivorous passerine birds.

Infection risk by pathogenic agents motivates hosts to avoid using resources with high risks. This, in turn, results in increased availability of these resources for other species that are more tolerant of infections. For instance, carcasses of mammalian carnivores are frequently avoided by conspecific or closely related carnivores, allowing them to be almost exclusively used by maggots. This may lead to novel interactions with other species. This study investigated the consumption of maggots from carnivore carcasses by non-corvid passerines. We successfully monitored 66 raccoon carcasses in Hokkaido, Japan, from 2016 to 2019. Vertebrates only scavenged 14 carcasses before maggot dispersal; the other 52 carcasses produced abundant maggots that regularly fed at least 12 species of non-corvid passerines. Surprisingly, predation occurred at a distance from the carcasses, mainly after maggot dispersal for pupation, despite the higher efficiency of feeding on maggot masses on the carcasses. Birds are likely to reduce the potential risk of infection from the carcass and/or from maggots on the carcasses. Overall, only 1% of maggots were consumed. Our results suggest that necrophagous flies could benefit from the infection risk associated with carnivore carcasses, which may decrease scavenging by other carnivores and constrain maggot consumption by insectivorous birds.

Establishing a protected area network in Xinlong with other effective area-based conservation measures.

Protected areas (PAs) are pivotal to biodiversity conservation, yet their efficacy is compromised by insufficient funding and management. So-called other effective area-based conservation measures (OECMs) present a paradigm shift and address PA limitations. Such measures can expand conservation areas, enhance connectivity, and improve the existing system. To assess the conservation status of biodiversity in Tibetan cultural areas in China, we investigated the spatial distribution of wildlife vulnerable to human disturbance (large- and medium-sized mammals and terrestrial birds) in Xinlong, a traditional Tibetan cultural area. In particular, we compared a PA (Xionglongxi Nature Reserve) and OECMs targeting species conservation. We also investigated the relationship of wildlife with human temporal and spatial activities. The OECMs complemented areas not covered by PA, especially in rich understory biodiversity regions. More species in OECMs tolerated human presence than species in the PA. Existing biodiversity reserves failed to cover areas of high conservation value in Tibet and offered limited protection capacity. Expanding PAs and identifying OECMs improved Xinlong's system by covering most biodiversity hotspots. Building on the tradition of wildlife conservation in Tibet, harnessing OECMs may be an effective means of augmenting biodiversity conservation capacity. We recommend further evaluation of OECMs effectiveness and coverage in Tibetan area as a way to enhance the current PA system.

自然保护地(protected areas, PAs)被认为是生物多样性保护的最重要且最有效的措施之一。然而, 由于资金不足和管理缺失等因素, 自然保护地体系的有效性被大幅度削弱。"其他有效的基于区域的保护措施(other effective area­based conservation measures, OECMs)"引起了基于区域的保护范式转变, 能够有效弥补PAs的不足。OECMs能够有效实现保护面积的扩大, 加强保护地之间的连通性, 完善现有保护地体系。基于此, 为进一步了解中国藏文化地区生物多样性的保护情况, 评估PAs和OECMs在物种保护上的差异。我们以中国新龙县为例, 调查了当地大中型哺乳动物和地栖鸟类这类容易受人为干扰的野生动物的空间分布和与人类互作的时空活动关系。结果表明, 在保护区无法覆盖的区域, OECMs能够提供有效的补充, 如林下区域的生物多样性保护。在OECMs范围内, 更多的物种能够在时空活动上容忍人类的存在, 尤其是猎物物种。在当前生物多样性优先保护区无法涵盖藏区高保护价值区域以及现有保护区保护能力有限的情况下, 藏区野生动物的保护需要采取更多针对性的措施。通过扩大保护区和确定OECMs区域, 能够覆盖新龙绝大部分生物多样性热点地区。鉴于藏区的野生动物保护传统, 借助OECMs的力量是完善和提高藏区生物多样性保护保护能力的有效手段。我们建议未来进一步评估藏区的OECMs的有效性及覆盖情况, 完善自然保护地体系。 基于其他有效的区域保护措施的中国新龙县保护地体系构建.