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1.
  1. Many animal personality traits have implicit movement‐based definitions and can directly or indirectly influence ecological and evolutionary processes. It has therefore been proposed that animal movement studies could benefit from acknowledging and studying consistent interindividual differences (personality), and, conversely, animal personality studies could adopt a more quantitative representation of movement patterns.
  2. Using high‐resolution tracking data of three‐spined stickleback fish (Gasterosteus aculeatus), we examined the repeatability of four movement parameters commonly used in the analysis of discrete time series movement data (time stationary, step length, turning angle, burst frequency) and four behavioral parameters commonly used in animal personality studies (distance travelled, space use, time in free water, and time near objects).
  3. Fish showed repeatable interindividual differences in both movement and behavioral parameters when observed in a simple environment with two, three, or five shelters present. Moreover, individuals that spent less time stationary, took more direct paths, and less commonly burst travelled (movement parameters), were found to travel farther, explored more of the tank, and spent more time in open water (behavioral parameters).
  4. Our case study indicates that the two approaches—quantifying movement and behavioral parameters—are broadly equivalent, and we suggest that movement parameters can be viewed as “micropersonality” traits that give rise to broad‐scale consistent interindividual differences in behavior. This finding has implications for both personality and movement ecology research areas. For example, the study of movement parameters may provide a robust way to analyze individual personalities in species that are difficult or impossible to study using standardized behavioral assays.
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2.
  1. A time‐consuming challenge faced by camera trap practitioners is the extraction of meaningful data from images to inform ecological management. An increasingly popular solution is automated image classification software. However, most solutions are not sufficiently robust to be deployed on a large scale due to lack of location invariance when transferring models between sites. This prevents optimal use of ecological data resulting in significant expenditure of time and resources to annotate and retrain deep learning models.
  2. We present a method ecologists can use to develop optimized location invariant camera trap object detectors by (a) evaluating publicly available image datasets characterized by high intradataset variability in training deep learning models for camera trap object detection and (b) using small subsets of camera trap images to optimize models for high accuracy domain‐specific applications.
  3. We collected and annotated three datasets of images of striped hyena, rhinoceros, and pigs, from the image‐sharing websites FlickR and iNaturalist (FiN), to train three object detection models. We compared the performance of these models to that of three models trained on the Wildlife Conservation Society and Camera CATalogue datasets, when tested on out‐of‐sample Snapshot Serengeti datasets. We then increased FiN model robustness by infusing small subsets of camera trap images into training.
  4. In all experiments, the mean Average Precision (mAP) of the FiN trained models was significantly higher (82.33%–88.59%) than that achieved by the models trained only on camera trap datasets (38.5%–66.74%). Infusion further improved mAP by 1.78%–32.08%.
  5. Ecologists can use FiN images for training deep learning object detection solutions for camera trap image processing to develop location invariant, robust, out‐of‐the‐box software. Models can be further optimized by infusion of 5%–10% camera trap images into training data. This would allow AI technologies to be deployed on a large scale in ecological applications. Datasets and code related to this study are open source and available on this repository: https://doi.org/10.5061/dryad.1c59zw3tx.
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3.
  1. Understanding the mechanisms underlying spatial variability of exploited fish is critical for the sustainable management of fish stocks. Empirical studies suggest that size‐selective fishing can elevate fish population spatial variability (i.e., more heterogeneous distribution) through age truncation, making the population less resilient to changing environment. However, species differ in how their spatial variability responds to age truncation and the underlying mechanisms remain unclear.
  2. We hypothesize that age‐specific habitat preference, together with environmental carrying capacity and landscape structure, determines the response of population spatial variability to fishing‐induced age truncation. To test these hypotheses, we design an individual‐based model of an age‐structured fish population on a two‐dimensional landscape under size‐selective fishing. Individual fish reproduces and survives, and moves between habitats according to age‐specific habitat preference and density‐dependent habitat selection.
  3. Population spatial variability elevates with increasing age truncation, and the response is stronger for populations with stronger age‐specific habitat preference. On a gradient landscape, reducing carrying capacity elevates the relative importance of density dependence in habitat selection, which weakens the response of spatial variability to age truncation for populations with strong age‐specific habitat preference. On a fragmented landscape, both populations with strong and weak age‐specific habitat preferences are restricted at local optimal habitats, and reducing carrying capacity weakens the responses of spatial variability to age truncation for both populations.
  4. Synthesis and applications. We demonstrate that to track and predict the changes in population spatial variability under exploitation, it is essential to consider the interactive effects of age‐specific habitat preference, carrying capacity, and landscape structure. To improve spatial management in fisheries, it is crucial to enhance empirical and theoretical developments in the methodology to quantify age‐specific habitat preference of marine fish, and to understand how climatic change influences carrying capacity and landscape continuity.
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4.
  1. Recent advances in digital data collection have spurred accumulation of immense quantities of data that have potential to lead to remarkable ecological insight, but that also present analytic challenges. In the case of biologging data from birds, common analytical approaches to classifying movement behaviors are largely inappropriate for these massive data sets.
  2. We apply a framework for using K‐means clustering to classify bird behavior using points from short time interval GPS tracks. K‐means clustering is a well‐known and computationally efficient statistical tool that has been used in animal movement studies primarily for clustering segments of consecutive points. To illustrate the utility of our approach, we apply K‐means clustering to six focal variables derived from GPS data collected at 1–11 s intervals from free‐flying bald eagles (Haliaeetus leucocephalus) throughout the state of Iowa, USA. We illustrate how these data can be used to identify behaviors and life‐stage‐ and age‐related variation in behavior.
  3. After filtering for data quality, the K‐means algorithm identified four clusters in >2 million GPS telemetry data points. These four clusters corresponded to three movement states: ascending, flapping, and gliding flight; and one non‐moving state: perching. Mapping these states illustrated how they corresponded tightly to expectations derived from natural history observations; for example, long periods of ascending flight were often followed by long gliding descents, birds alternated between flapping and gliding flight.
  4. The K‐means clustering approach we applied is both an efficient and effective mechanism to classify and interpret short‐interval biologging data to understand movement behaviors. Furthermore, because it can apply to an abundance of very short, irregular, and high‐dimensional movement data, it provides insight into small‐scale variation in behavior that would not be possible with many other analytical approaches.
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5.
  1. Individual space and resource use are central issues in ecology and conservation. Recent technological advances such as automated tracking techniques are boosting ecological research in this field. However, the development of a robust method to track space and resource use is still challenging for at least one important ecosystem component: motile aquatic macroinvertebrates. The challenges are mostly related to the small body size and rapid movement of many macroinvertebrate species and to light scattering and wave signal interference in aquatic habitats.
  2. We developed a video tracking method designed to reliably assess space use behavior among individual aquatic macroinvertebrates under laboratory (microcosm) conditions. The approach involves the use of experimental apparatus integrating a near infrared backlight source, a Plexiglas multi‐patch maze, multiple infrared cameras, and automated video analysis. It allows detection of the position of fast‐moving (~ 3 cm/s) and translucent individuals of small size (~ 5 mm in length, ~1 mg in dry weight) on simulated resource patches distributed over an experimental microcosm (0.08 m2).
  3. To illustrate the adequacy of the proposed method, we present a case study regarding the size dependency of space use behavior in the model organism Gammarus insensibilis, focusing on individual patch selection, giving‐up times, and cumulative space used.
  4. In the case study, primary data were collected on individual body size and individual locomotory behavior, for example, mean speed, acceleration, and step length. Individual entrance and departure times were recorded for each simulated resource patch in the experimental maze. Individual giving‐up times were found to be characterized by negative size dependency, with patch departure occurring sooner in larger individuals than smaller ones, and individual cumulative space used (treated as the overall surface area of resource patches that individuals visited) was found to scale positively with body size.
  5. This approach to studying space use behavior can deepen our understanding of species coexistence, yielding insights into mechanistic models on larger spatial scales, for example, home range, with implications for ecological and evolutionary processes, as well as for the management and conservation of populations and ecosystems. Despite being specifically developed for aquatic macroinvertebrates, this method can also be applied to other small aquatic organisms such as juvenile fish and amphibians.
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6.
  1. A central theme for conservation is understanding how animals differentially use, and are affected by change in, the landscapes they inhabit. However, it has been challenging to develop conservation schemes for habitat‐specific behaviors.
  2. Here we use behavioral change point analysis to identify behavioral states of golden eagles (Aquila chrysaetos) in the Sonoran and Mojave Deserts of the southwestern United States, and we identify, for each behavioral state, conservation‐relevant habitat associations.
  3. We modeled behavior using 186,859 GPS points from 48 eagles and identified 2,851 distinct segments comprising four behavioral states. Altitude above ground level (AGL) best differentiated behavioral states, with two clusters of short‐distance movement behaviors characterized by low AGL (state 1 AGL = 14 m (median); state 2 AGL = 11 m) and two associated with longer‐distance movement behaviors and characterized by higher AGL (state 3 AGL = 108 m; state 4 AGL = 450 m).
  4. Behaviors such as perching and low‐altitude hunting were associated with short‐distance movements in updraft‐poor environments, at higher elevations, and over steeper and more north‐facing terrain. In contrast, medium‐distance movements such as hunting and transiting were over gentle and south‐facing slopes. Long‐distance transiting occurred over the desert habitats that generate the best updraft.
  5. This information can guide management of this species, and our approach provides a template for behavior‐specific habitat associations for other species of management concern.
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7.
  1. Advances in individual marking methods have facilitated detailed studies of animal populations and behavior as they allow tracking of individuals through time and space. Hemimetabolous insects, representing a wide range of commonly used model organisms, present a unique challenge to individual marking as they are not only generally small‐bodied, but also molt throughout development, meaning that traditional surface marks are not persistent.
  2. Visible implant elastomer (VIE) offers a potential solution as small amounts of the inert polymer can be implanted under the skin or cuticle of an animal. VIE has proved useful for individually marking fish, crustaceans, and amphibians in both field and laboratory studies and has recently been successfully trialed in laboratory populations of worms and fly larvae. We trialed VIE in the single‐piece nesting termite Zootermopsis angusticollis, a small hemimetabolous insect.
  3. We found that there was no effect of VIE on survival and that marks persisted following molting. However, we found some evidence that marked termites performed less allogrooming and trophallaxis than controls, although effect sizes were very small.
  4. Our study suggests that VIE is an effective technique for marking small hemimetabolous insects like termites but we advocate that caution is applied, particularly when behavioral observation is important.
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8.
  1. Insect populations are changing rapidly, and monitoring these changes is essential for understanding the causes and consequences of such shifts. However, large‐scale insect identification projects are time‐consuming and expensive when done solely by human identifiers. Machine learning offers a possible solution to help collect insect data quickly and efficiently.
  2. Here, we outline a methodology for training classification models to identify pitfall trap‐collected insects from image data and then apply the method to identify ground beetles (Carabidae). All beetles were collected by the National Ecological Observatory Network (NEON), a continental scale ecological monitoring project with sites across the United States. We describe the procedures for image collection, image data extraction, data preparation, and model training, and compare the performance of five machine learning algorithms and two classification methods (hierarchical vs. single‐level) identifying ground beetles from the species to subfamily level. All models were trained using pre‐extracted feature vectors, not raw image data. Our methodology allows for data to be extracted from multiple individuals within the same image thus enhancing time efficiency, utilizes relatively simple models that allow for direct assessment of model performance, and can be performed on relatively small datasets.
  3. The best performing algorithm, linear discriminant analysis (LDA), reached an accuracy of 84.6% at the species level when naively identifying species, which was further increased to >95% when classifications were limited by known local species pools. Model performance was negatively correlated with taxonomic specificity, with the LDA model reaching an accuracy of ~99% at the subfamily level. When classifying carabid species not included in the training dataset at higher taxonomic levels species, the models performed significantly better than if classifications were made randomly. We also observed greater performance when classifications were made using the hierarchical classification method compared to the single‐level classification method at higher taxonomic levels.
  4. The general methodology outlined here serves as a proof‐of‐concept for classifying pitfall trap‐collected organisms using machine learning algorithms, and the image data extraction methodology may be used for nonmachine learning uses. We propose that integration of machine learning in large‐scale identification pipelines will increase efficiency and lead to a greater flow of insect macroecological data, with the potential to be expanded for use with other noninsect taxa.
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9.
  1. The early detection of invasive non‐native species (INNS) is important for informing management actions. Established monitoring methods require the collection or observation of specimens, which is unlikely at the beginning of an invasion when densities are likely to be low. Environmental DNA (eDNA) analysis is a highly promising technique for the detection of INNS—particularly during the early stages of an invasion.
  2. Here, we compared the use of traditional kick‐net sampling with two eDNA approaches (targeted detection using both conventional and quantitative PCR and passive detection via metabarcoding with conserved primers) for detection of quagga mussel, Dreissena rostriformis bugensis, a high priority INNS, along a density gradient on the River Wraysbury, UK.
  3. All three molecular tools outperformed traditional sampling in terms of detection. Conventional PCR and qPCR both had 100% detection rate in all samples and outperformed metabarcoding when the target species was at low densities. Additionally, quagga mussel DNA copy number (qPCR) and relative read count (metabarcoding) were significantly influenced by both mussel density and distance from source population, with distance being the most significant predictor.
  4. Synthesis and application. All three molecular approaches were more sensitive than traditional kick‐net sampling for the detection of the quagga mussel in flowing water, and both qPCR and metabarcoding enabled estimates of relative abundance. Targeted approaches were more sensitive than metabarcoding, but metabarcoding has the advantage of providing information on the wider community and consequently the impacts of INNS.
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10.
11.
  1. Fishing is a strong selective force and is supposed to select for earlier maturation at smaller body size. However, the extent to which fishing‐induced evolution is shaping ecosystems remains debated. This is in part because it is challenging to disentangle fishing from other selective forces (e.g., size‐structured predation and cannibalism) in complex ecosystems undergoing rapid change.
  2. Changes in maturation size from fishing and predation have previously been explored with multi‐species physiologically structured models but assumed separation of ecological and evolutionary timescales. To assess the eco‐evolutionary impact of fishing and predation at the same timescale, we developed a stochastic physiologically size‐structured food‐web model, where new phenotypes are introduced randomly through time enabling dynamic simulation of species'' relative maturation sizes under different types of selection pressures.
  3. Using the model, we carried out a fully factorial in silico experiment to assess how maturation size would change in the absence and presence of both fishing and predation (including cannibalism). We carried out ten replicate stochastic simulations exposed to all combinations of fishing and predation in a model community of nine interacting fish species ranging in their maximum sizes from 10 g to 100 kg. We visualized and statistically analyzed the results using linear models.
  4. The effects of fishing on maturation size depended on whether or not predation was enabled and differed substantially across species. Fishing consistently reduced the maturation sizes of two largest species whether or not predation was enabled and this decrease was seen even at low fishing intensities (F = 0.2 per year). In contrast, the maturation sizes of the three smallest species evolved to become smaller through time but this happened regardless of the levels of predation or fishing. For the four medium‐size species, the effect of fishing was highly variable with more species showing significant and larger fishing effects in the presence of predation.
  5. Ultimately our results suggest that the interactive effects of predation and fishing can have marked effects on species'' maturation sizes, but that, at least for the largest species, predation does not counterbalance the evolutionary effect of fishing. Our model also produced relative maturation sizes that are broadly consistent with empirical estimates for many fish species.
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12.
  1. Global road networks continue to expand, and the wildlife responses to these landscape‐level changes need to be understood to advise long‐term management decisions. Roads have high mortality risk to snakes because snakes typically move slowly and can be intentionally targeted by drivers.
  2. We investigated how radio‐tracked King Cobras (Ophiophagus hannah) traverse a major highway in northeast Thailand, and if reproductive cycles were associated with road hazards.
  3. We surveyed a 15.3 km stretch of Highway 304 to determine if there were any locations where snakes could safely move across the road (e.g., culverts and bridges). We used recurse analyses to detect possible road‐crossing events, and used dynamic Brownian Bridge Movement Models (dBBMMs) to show movement pathways association with possible unintentional crossing structures. We further used Integrated Step Selection Functions (ISSF) to assess seasonal differences in avoidance of major roads for adult King Cobras in relation to reproductive state.
  4. We discovered 32 unintentional wildlife crossing locations capable of facilitating King Cobra movement across the highway. While our dBBMMs broadly revealed underpasses as possible crossing points, they failed to identify specific underpasses used by telemetered individuals; however, the tracking locations pre‐ and post‐crossing and photographs provided strong evidence of underpass use. Our ISSF suggested a lower avoidance of roads during the breeding season, although the results were inconclusive. With the high volume of traffic, large size of King Cobras, and a 98.8% success rate of crossing the road in our study (nine individuals: 84 crossing attempts with one fatality), we strongly suspect that individuals are using the unintentional crossing structures to safely traverse the road.
  5. Further research is needed to determine the extent of wildlife underpass use at our study site. We propose that more consistent integration of drainage culverts and bridges could help mitigate the impacts of roads on some terrestrial wildlife.
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13.
  1. Climate change is commonly associated with many species redistributions and the influence of other factors may be marginalized, especially in the rapidly warming Arctic.
  2. The Barents Sea, a high latitude large marine ecosystem in the Northeast Atlantic has experienced above‐average temperatures since the mid‐2000s with divergent bottom temperature trends at subregional scales.
  3. Concurrently, the Barents Sea stock of Atlantic cod Gadus morhua, one of the most important commercial fish stocks in the world, increased following a large reduction in fishing pressure and expanded north of 80°N.
  4. We examined the influence of food availability and temperature on cod expansion using a comprehensive data set on cod stomach fullness stratified by subregions characterized by divergent temperature trends. We then tested whether food availability, as indexed by cod stomach fullness, played a role in cod expansion in subregions that were warming, cooling, or showed no trend.
  5. The greatest increase in cod occupancy occurred in three northern subregions with contrasting temperature trends. Cod apparently benefited from initial high food availability in these regions that previously had few large‐bodied fish predators.
  6. The stomach fullness in the northern subregions declined rapidly after a few years of high cod abundance, suggesting that the arrival of cod caused a top‐down effect on the prey base. Prolonged cod residency in the northern Barents Sea is, therefore, not a certainty.
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14.
15.
  1. High‐throughput sequencing of amplicons (HTSA) has been proposed as an effective approach to evaluate taxonomic and genetic diversity at the same time. However, there are still uncertainties as to how the results produced by different bioinformatics treatments impact the conclusions drawn on biodiversity and population genetics indices.
  2. We evaluated the ability of six bioinformatics pipelines to recover taxonomic and genetic diversity from HTSA data obtained from controlled assemblages. To that end, 20 assemblages were produced using 354 colonies of Botrylloides spp., sampled in the wild in ten marinas around Brittany (France). We used DNA extracted from preservative ethanol (ebDNA) after various time of storage (3, 6, and 12 months), and from a bulk of preserved specimens (bulkDNA). DNA was amplified with primers designed for targeting this ascidian genus. Results obtained from HTSA data were compared with Sanger sequencing on individual zooids (i.e., individual barcoding).
  3. Species identification and relative abundance determined with HTSA data from either ebDNA or bulkDNA were similar to those obtained with traditional individual barcoding. However, after 12 months of storage, the correlation between HTSA and individual‐based data was lower than after shorter durations. The six bioinformatics pipelines were able to depict accurately the genetic diversity using standard population genetics indices (HS and FST), despite producing false positives and missing rare haplotypes. However, they did not perform equally and dada2 was the only pipeline able to retrieve all expected haplotypes.
  4. This study showed that ebDNA is a nondestructive alternative for both species identification and haplotype recovery, providing storage does not last more than 6 months before DNA extraction. Choosing the bioinformatics pipeline is a matter of compromise, aiming to retrieve all true haplotypes while avoiding false positives. We here recommend to process HTSA data using dada2, including a chimera‐removal step. Even if the possibility to use multiplexed primer sets deserves further investigation to expand the taxonomic coverage in future similar studies, we showed that primers targeting a particular genus allowed to reliably analyze this genus within a complex community.
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16.
  1. Mutualism is a form of symbiosis whereby both parties benefit from the relationship. An example is cleaning symbiosis, which has been observed in terrestrial and marine environments. The most recognized form of marine cleaning symbiosis is that of cleaner fishes and their clients.
  2. Cleaner species set up cleaning stations on the reef, and other species seek out their services. However, it is not well understood how the presence of cleaning stations influence movements of large highly mobile species. We examined the role of cleaning stations as a driver of movement and habitat use in a mobile client species.
  3. Here, we used a combination of passive acoustic telemetry and in‐water surveys to investigate cleaning station attendance by the reef manta ray Mobula alfredi. We employed a novel approach in the form of a fine‐scale acoustic receiver array set up around a known cleaning area and tagged 42 rays. Within the array, we mapped structural features, surveyed the distribution of cleaner wrasse, and observed the habitat use of the rays.
  4. We found manta ray space use was significantly associated with blue‐streak cleaner wrasse Labroides dimidiatus distribution and hard coral substrate. Cleaning interactions dominated their habitat use at this site, taking precedence over other life history traits such as feeding and courtship.
  5. This study has demonstrated that cleaning symbiosis is a driver for highly mobile, and otherwise pelagic, species to visit inshore reef environments. We suggest that targeted and long‐term use of specific cleaning stations reflects manta rays having a long‐term memory and cognitive map of some shallow reef environments where quality cleaning is provided. We hypothesize that animals prefer cleaning sites in proximity to productive foraging regions.
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17.
  1. Plants typically interact with multiple above‐ and below‐ground organisms simultaneously, with their symbiotic relationships spanning a continuum ranging from mutualism, such as with arbuscular mycorrhizal fungi (AMF), to parasitism, including symbioses with plant‐parasitic nematodes (PPN).
  2. Although research is revealing the patterns of plant resource allocation to mutualistic AMF partners under different host and environmental constraints, the root ecosystem, with multiple competing symbionts, is often ignored. Such competition is likely to heavily influence resource allocation to symbionts.
  3. Here, we outline and discuss the competition between AMF and PPN for the finite supply of host plant resources, highlighting the need for a more holistic understanding of the influence of below‐ground interactions on plant resource allocation. Based on recent developments in our understanding of other symbiotic systems such as legume–rhizobia and AMF‐aphid‐plant, we propose hypotheses for the distribution of plant resources between contrasting below‐ground symbionts and how such competition may affect the host.
  4. We identify relevant knowledge gaps at the physiological and molecular scales which, if resolved, will improve our understanding of the true ecological significance and potential future exploitation of AMF‐PPN‐plant interactions in order to optimize plant growth. To resolve these outstanding knowledge gaps, we propose the application of well‐established methods in isotope tracing and nutrient budgeting to monitor the movement of nutrients between symbionts. By combining these approaches with novel time of arrival experiments and experimental systems involving multiple plant hosts interlinked by common mycelial networks, it may be possible to reveal the impact of multiple, simultaneous colonizations by competing symbionts on carbon and nutrient flows across ecologically important scales.
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18.
Lyons  J.  Lucas  M. C. 《Hydrobiologia》2002,483(1-3):265-273
Spatial behaviour and distribution of fishes along a 7.6-km lowland reach of the River Trent, England, were examined using two complementary telemetry techniques: acoustic tracking to assess the movement and activity of common bream Abramis brama (L.) and quantitative echosounding for measuring the density and distribution of fish shoals. Nine adult bream (39.3–53.2 cm) were tracked by means of intraperitoneally implanted acoustic transmitters from 19 July to 12 September 2000. Home range size varied between 0.35 and 5.40 km of river length over this period. Bream were relatively inactive during daylight hours, began moving near dusk, and tended to move throughout the night. A distinct daytime residence area was occupied by most tagged fish on most occasions, while river use at night was more variable between individuals. Mobile echosounding surveys, with the transducer beaming horizontally across the river, conducted at night between July and September 2000, showed a highly contagious fish distribution within the study reach. For 200-m sections of river, there was a negative correlation between the relative frequency of acoustic tracking fixes at night and mean fish densities, as measured by echosounding for targets larger than –50 dB (c. 5-cm long). However, there was a highly significant positive rank correlation between the relative frequency of acoustic tracking fixes and acoustic targets larger than –30 dB (c. 22-cm long), most of which in this river are bream. This suggests that telemetry and echosounding can, in this part of the River Trent, be combined to provide valuable spatial information at individual and population scales for bream.  相似文献   

19.
  1. Mutual reinforcement between abiotic and biotic factors can drive small populations into a catastrophic downward spiral to extinction—a process known as the “extinction vortex.” However, empirical studies investigating extinction dynamics in relation to species'' traits have been lacking.
  2. We assembled a database of 35 vertebrate populations monitored to extirpation over a period of at least ten years, represented by 32 different species, including 25 birds, five mammals, and two reptiles. We supplemented these population time series with species‐specific mean adult body size to investigate whether this key intrinsic trait affects the dynamics of populations declining toward extinction.
  3. We performed three analyses to quantify the effects of adult body size on three characteristics of population dynamics: time to extinction, population growth rate, and residual variability in population growth rate.
  4. Our results provide support for the existence of extinction vortex dynamics in extirpated populations. We show that populations typically decline nonlinearly to extinction, while both the rate of population decline and variability in population growth rate increase as extinction is approached. Our results also suggest that smaller‐bodied species are particularly prone to the extinction vortex, with larger increases in rates of population decline and population growth rate variability when compared to larger‐bodied species.
  5. Our results reaffirm and extend our understanding of extinction dynamics in real‐life extirpated populations. In particular, we suggest that smaller‐bodied species may be at greater risk of rapid collapse to extinction than larger‐bodied species, and thus, management of smaller‐bodied species should focus on maintaining higher population abundances as a priority.
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20.
  1. Saltmarsh‐mangrove ecotones occur at the boundary of the natural geographic distribution of mangroves and salt marshes. Climate warming and species invasion can also drive the formation of saltmarsh‐mangrove mixing communities. How these coastal species live together in a “new” mixed community is important in predicting the dynamic of saltmarsh‐mangrove ecosystems as affected by ongoing climate change or human activities. To date, the understanding of species interactions has been rare on adult species in these ecotones.
  2. Two typical coastal wetlands were selected as cases to understand how mangrove and saltmarsh species living together in the ecotones. The leaves of seven species were sampled from these coastal wetlands based on their distribution patterns (living alone or coexisting) in the high tidal zone, and seven commonly used functional traits of these species were analyzed.
  3. We found niche separation between saltmarsh and mangrove species, which is probably due to the different adaptive strategies they adopted to deal with intertidal environments.
  4. Weak interactions between coexisting species were dominated in the high tidal zone of the two saltmarsh‐mangrove communities, which could be driven by both niche differentiation and neutral theory.
  5. Synthesis. Our field study implies a potential opportunity to establish a multispecies community in the high tidal zone of saltmarsh‐mangrove ecotones, where the sediment was characterized by low salinity and high nitrogen.
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