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Selection: with tag presence-absence [14 articles] 


Integrating biodiversity distribution knowledge: toward a global map of life

Trends in Ecology & Evolution, Vol. 27, No. 3. (March 2012), pp. 151-159,


Global knowledge about the spatial distribution of species is orders of magnitude coarser in resolution than other geographically-structured environmental datasets such as topography or land cover. Yet such knowledge is crucial in deciphering ecological and evolutionary processes and in managing global change. In this review, we propose a conceptual and cyber-infrastructure framework for refining species distributional knowledge that is novel in its ability to mobilize and integrate diverse types of data such that their collective strengths overcome individual weaknesses. The ultimate ...


The uncertain nature of absences and their importance in species distribution modelling

Ecography, Vol. 33, No. 1. (1 February 2010), pp. 103-114,


Species distribution models (SDM) are commonly used to obtain hypotheses on either the realized or the potential distribution of species. The reliability and meaning of these hypotheses depends on the kind of absences included in the training data, the variables used as predictors and the methods employed to parameterize the models. Information about the absence of species from certain localities is usually lacking, so pseudo-absences are often incorporated to the training data. We explore the effect of using different kinds of ...


Estimating abundance from repeated presence-absence data or point counts

Ecology, Vol. 84, No. 3. (March 2003), pp. 777-790,[0777:eafrpa];2


We describe an approach for estimating occupancy rate or the proportion of area occupied when heterogeneity in detection probability exists as a result of variation in abundance of the organism under study. The key feature of such problems, which we exploit, is that variation in abundance induces variation in detection probability. Thus, heterogeneity in abundance can be modeled as heterogeneity in detection probability. Moreover, this linkage between heterogeneity in abundance and heterogeneity in detection probability allows one to exploit a heterogeneous ...


Simultaneous estimation of multinomial cell probabilities

Journal of the American Statistical Association, Vol. 68, No. 343. (1 September 1973), pp. 683-691,


A new estimator, p*, of the multinomial parameter vector is proposed, and it is shown to be a better choice in most situations than the usual estimator, (the vector of observed proportions). The risk functions (expected squared-error loss) of these two estimators are examined in three ways using: (a) exact calculations, (b) standard asymptotic theory, and (c) a novel asymptotic framework in which the number of cells is large and the number of observations per cell is moderate. The general superiority ...


(INRMM-MiD internal record) List of keywords of the INRMM meta-information database - part 28

(February 2014)
Keywords: inrmm-list-of-tags   power-law   ppm   practice   pre-alpine   pre-print   precaution   precaution-principle   precipitation   precisely-wrong   precursor-research   predation   predator-satiation   predatory-publishers   prediction   prediction-bias   predictive-modelling   predictors   predisposition   premature-optimization   preparedness   preprints   prescribed-burn   presence-absence   presence-only   pressure-volume-curves   pressures   prestoea-montana   pretreatment   prey-predator   pricing   primary-productivity   principal-components-regression   prisoners-dilemma   pristiphora-abietina   probability-vs-possibility   problem-driven   processes   processing   production-rules   productivity   programming   progressive-learning   prolog   proportion   prosopis-alba   prosopis-glandulosa   prosopis-pallida   protected-areas   protected-species   protection   protective-forest   protocol-uncertainty   provenance   provisioning-services   pruning   prunus-avium   prunus-cerasifera   prunus-domestica   prunus-dulcis   prunus-fruticosa   prunus-ilicifolia   prunus-laurocerasus   prunus-mahaleb   prunus-malaheb   prunus-padus   prunus-salicina   prunus-serotina   prunus-spinosa   prunus-spp   prunus-tenella   pseudo-absences   pseudo-random   pseudoaraucaria-spp   pseudolarix-spp   pseudomonas-avellanae   pseudomonas-spp   pseudomonas-syringae   pseudotsuga   pseudotsuga-macrocarpa   pseudotsuga-menziesii   pseudotsuga-spp   psychology   pterocarpus-indicus   pterocarpus-officinalis   pterocarya-pterocarpa   public-domain   publication-bias   publication-delay   publication-errors   publish-or-perish   puccinia-coronata   pull-push-pest-control   pulp   punica-granatum   purdiaea-nutans   pyrenees-region   pyrolysis   pyrus-amygdaliformis   pyrus-browiczii  


List of indexed keywords within the transdisciplinary set of domains which relate to the Integrated Natural Resources Modelling and Management (INRMM). In particular, the list of keywords maps the semantic tags in the INRMM Meta-information Database (INRMM-MiD). [\n] The INRMM-MiD records providing this list are accessible by the special tag: inrmm-list-of-tags ( ). ...


Dutch Vegetation Database (LVD)



Description The Dutch Vegetation Database (LVD) hosts information on all plant communities in the Netherlands. This substantial archive consists of over 600.000 recent and historic vegetation descriptions. The data provide information on more than 85 years of vegetation recording in various habitats covering terrestrial and aquatic ecosystems from natural, semi-natural as well as cultural landscapes. For the purpose of the GBIF data-publishing vegetation plot data are converted into species occurrence data. Purpose The Dutch Vegetation Database (LVD) is used for many ...


Is my species distribution model fit for purpose? Matching data and models to applications

Global Ecology and Biogeography, Vol. 24, No. 3. (February 2015), pp. 276-292,


Species distribution models (SDMs) are used to inform a range of ecological, biogeographical and conservation applications. However, users often underestimate the strong links between data type, model output and suitability for end-use. We synthesize current knowledge and provide a simple framework that summarizes how interactions between data type and the sampling process (i.e. imperfect detection and sampling bias) determine the quantity that is estimated by a SDM. We then draw upon the published literature and simulations to illustrate and evaluate the ...

Visual summary


Presence-absence versus presence-only modelling methods for predicting bird habitat suitability

Ecography, Vol. 27, No. 4. (August 2004), pp. 437-448,


Habitat suitability models can be generated using methods requiring information on species presence or species presence and absence. Knowledge of the predictive performance of such methods becomes a critical issue to establish their optimal scope of application for mapping current species distributions under different constraints. Here, we use breeding bird atlas data in Catalonia as a working example and attempt to analyse the relative performance of two methods: the Ecological Niche factor Analysis (ENFA) using presence data only and Generalised Linear ...


Sample Proportion

In MathWorld - A Wolfram Web Resource (2014)


[Excerpt] Let there be x successes out of n Bernoulli trials. The sample proportion is the fraction of samples which were successes, so p=x/n. ...


A fast and unbiased procedure to randomize ecological binary matrices with fixed row and column totals

Nature Communications, Vol. 5 (11 June 2014),


A well-known problem in numerical ecology is how to recombine presence-absence matrices without altering row and column totals. A few solutions have been proposed, but all of them present some issues in terms of statistical robustness (that is, their capability to generate different matrix configurations with the same probability) and their performance (that is, the computational effort that they require to generate a null matrix). Here we introduce the ‘Curveball algorithm’, a new procedure that differs from existing methods in that ...


A statistical explanation of MaxEnt for ecologists

Diversity and Distributions, Vol. 17, No. 1. (1 January 2011), pp. 43-57,


MaxEnt is a program for modelling species distributions from presence-only species records. This paper is written for ecologists and describes the MaxEnt model from a statistical perspective, making explicit links between the structure of the model, decisions required in producing a modelled distribution, and knowledge about the species and the data that might affect those decisions. To begin we discuss the characteristics of presence-only data, highlighting implications for modelling distributions. We particularly focus on the problems of sample bias and lack ...


Classification of Natural and Semi-natural Vegetation

In Vegetation Ecology (07 January 2013), pp. 28-70,


This chapter covers classification of natural and semi-natural vegetation, including classification frameworks, components of classification, project planning and data acquisition, data preparation and integration, community entitation, cluster assessment, community characterization and determination, classification integration, documentation, and future directions and challenges. ...


Novel methods improve prediction of species' distributions from occurrence data

Ecography, Vol. 29, No. 2. (1 April 2006), pp. 129-151,


Prediction of species’ distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only ...


Exploring the effects of quantity and location of pseudo-absences and sampling biases on the performance of distribution models with limited point occurrence data

Journal for Nature Conservation, Vol. 19, No. 1. (12 January 2011), pp. 1-7,


In the last decade, the application of predictive models of species distribution in ecology, evolution, and conservation biology has increased dramatically. However, limited available data and the lack of reliable absence data have become a major challenge to overcome. At least two approaches have been proposed to generate pseudo-absences; however it is not clear how the number of pseudo-absences created affect model performance. Moreover, the spatial bias in the collecting localities of a species (presence data) may add extra noise to ...

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Integrated Natural Resources Modelling and Management - Meta-information Database.

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Meta-information Database (INRMM-MiD).
This database integrates a dedicated meta-information database in CiteULike (the CiteULike INRMM Group) with the meta-information available in Google Scholar, CrossRef and DataCite. The Altmetric database with Article-Level Metrics is also harvested. Part of the provided semantic content (machine-readable) is made even human-readable thanks to the DCMI Dublin Core viewer. Digital preservation of the meta-information indexed within the INRMM-MiD publication records is implemented thanks to the Internet Archive.
The library of INRMM related pubblications may be quickly accessed with the following links.
Search within the whole INRMM meta-information database:
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Full-text and abstracts of the publications indexed by the INRMM meta-information database are copyrighted by the respective publishers/authors. They are subject to all applicable copyright protection. The conditions of use of each indexed publication is defined by its copyright owner. Please, be aware that the indexed meta-information entirely relies on voluntary work and constitutes a quite incomplete and not homogeneous work-in-progress.
INRMM-MiD was experimentally established by the Maieutike Research Initiative in 2008 and then improved with the help of several volunteers (with a major technical upgrade in 2011). This new integrated interface is operational since 2014.