Hasil untuk "Ecology"

M. Lynch, J. Neufeld

J. Wiens, D. Ackerly, A. P. Allen et al.

Jason P. Sexton, P. McIntyre, A. Angert et al.

Melanie Ghoul, Sara Mitri

L. Jawad

M. Kéry, J. Andrew Royle

Applied Hierarchical Modeling in Ecology: Distribution, Abundance, Species Richness offers a new synthesis of the state-of-the-art of hierarchical models for plant and animal distribution, abundance, and community characteristics such as species richness using data collected in metapopulation designs. These types of data are extremely widespread in ecology and its applications in such areas as biodiversity monitoring and fisheries and wildlife management. This first volume explains static models/procedures in the context of hierarchical models that collectively represent a unified approach to ecological research, taking the reader from design, through data collection, and into analyses using a very powerful class of models. Applied Hierarchical Modeling in Ecology, Volume 1 serves as an indispensable manual for practicing field biologists, and as a graduate-level text for students in ecology, conservation biology, fisheries/wildlife management, and related fields. * Provides a synthesis of important classes of models about distribution, abundance, and species richness while accommodating imperfect detection* Presents models and methods for identifying unmarked individuals and species* Written in a step-by-step approach accessible to non-statisticians and provides fully worked examples that serve as a template for readers' analyses* Includes companion website containing data sets, code, solutions to exercises, and further information

T. Dawson, S. Mambelli, A. Plamboeck et al.

R. Forman, D. Sperling, J. Bissonette et al.

Raymond L. Lindeman

J. Yoder, C. Walsh, T. Bestor

Most of the 5-methylcytosine in mammalian DNA resides in transposons, which are specialized intragenomic parasites that represent at least 35% of the genome. Transposon promoters are inactive when methylated and, over time, C-->T transition mutations at methylated sites destroy many transposons. Apart from that subset of genes subject to X inactivation and genomic imprinting, no cellular gene in a non-expressing tissue has been proven to be methylated in a pattern that prevents transcription. It has become increasingly difficult to hold that reversible promoter methylation is commonly involved in developmental gene control; instead, suppression of parasitic sequence elements appears to be the primary function of cytosine methylation, with crucial secondary roles in allele-specific gene expression as seen in X inactivation and genomic imprinting.

J. Schultz, R. Tollrian, C. Harvell

Inducible defenses are responses activated through a previous encounter with a consumer or competitor that confer some degree of resistance to subsequent attacks. While the importance of inducible resistance has long been known in host-parasite interactions, it is only recently that its importance has emerged in other natural systems. Althought the structural defenses produced by invertebrates to their competitors and predators are by no means the same as an immune response triggered by parasites, these responses all share the properties of (1) specificity, (2) amplification and (3) memory. This review discusses the following ecological consequences and evolutionary causes of inducible defenses: (1) Inducible defenses render historical factors important in biological interactions and can affect the probability of individual survival and growth, as well as affect population dynamics of consumers in some circumstances. (2) Although the benefits of inducible defenses are often balanced by fitness costs, including reduced growth, reproductive output and survivorship, the role of costs and benefits in the evolution of inducible defenses is by no means clear. A more integrated approach would involve a multivariate analysis of the role of natural selection on the inducible characters of interest, their norms of reaction and correlated fitness characters. (3) The disproporcionate representation of inducible, morphological defenses among clonal organisms may be due to both a higher rate of origination and enhanced selection to maintain these defenses in clonal taxa. (4) Inducible defenses should be most common when reliable cues are available, attacks by biological agents are unpredictable, and the fitness gains of defenses are balanced by the costs. An integrated approach to studying inducible defenses would thus combine mechanistic estimates of costs, population-level estimates of defense effectiveness, and genetic estimates of correlations between fitness and inducible characters. This will allow us to estimate rates of evolution in these phenotypically plastic threshold characters.

D. Schluter

N. Gotelli, G. Graves

J. Nekola, P. White

J. Wiens, M. Donoghue

D. Barton

Ben. G. Weinstein

J. Freeland

A. Jentsch, P. White

Abstract We propose four postulates as the minimum set of logical propositions necessary for a theory of pulse dynamics and disturbance in ecosystems: (1) resource dynamics characterizes the magnitude, rate, and duration of resource change caused by pulse events, including the continuing changes in resources that are the result of abiotic and biotic processes; (2) energy flux characterizes the energy flow that controls the variation in the rates of resource assimilation across ecosystems; (3) patch dynamics characterizes the distribution of resource patches over space and time, and the resulting patterns of biotic diversity, ecosystem structure, and cross‐scale feedbacks of pulses processes; and (4) biotic trait diversity characterizes the evolutionary responses to pulse dynamics and, in turn, the way trait diversity affects ecosystem dynamics during and after pulse events. We apply the four postulates to an important class of pulse events, biomass‐altering disturbances, and derive seven generalizations that predict disturbance magnitude, resource trajectory, rate of resource change, disturbance probability, biotic trait diversification at evolutionary scales, biotic diversity at ecological scales, and functional resilience. Ultimately, theory must define the variable combinations that result in dynamic stability, comprising resistance, recovery, and adaptation.

Quan Nguyen, Adji Bousso Dieng

While monitoring biodiversity through camera traps has become an important endeavor for ecological research, identifying species in the captured image data remains a major bottleneck due to limited labeling resources. Active learning -- a machine learning paradigm that selects the most informative data to label and train a predictive model -- offers a promising solution, but typically focuses on uncertainty in the individual predictions without considering uncertainty across the entire dataset. We introduce a new active learning policy, Vendi information gain (VIG), that selects images based on their impact on dataset-wide prediction uncertainty, capturing both informativeness and diversity. We applied VIG to the Snapshot Serengeti dataset and compared it against common active learning methods. VIG needs only 3% of the available data to reach 75% accuracy, a level that baselines require more than 10% of the data to achieve. With 10% of the data, VIG attains 88% predictive accuracy, 12% higher than the best of the baselines. This improvement in performance is consistent across metrics and batch sizes, and we show that VIG also collects more diverse data in the feature space. VIG has broad applicability beyond ecology, and our results highlight its value for biodiversity monitoring in data-limited environments.