Evidence map›Paper›PMID 30847061›Full record

ArticleEcology and evolution2019

SPECIES: A platform for the exploration of ecological data.

Christopher R Stephens, Raúl Sierra-Alcocer, Constantino González-Salazar, Juan M Barrios, Juan Carlos Salazar Carrillo, Everardo Robredo Ezquivelzeta, Enrique Del Callejo Canal

Abstract read
In one paragraph

Article in Ecology and evolution, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Toward New Epidemiological Landscapes ofTropical medicine and infectious disease · 2022
    Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Christopher R StephensCentro de Ciencias de la Complejidad Universidad Nacional Autónoma de México Mexico City Mexico.
Raúl Sierra-AlcocerCentro de Ciencias de la Complejidad Universidad Nacional Autónoma de México Mexico City Mexico.ORCID https://orcid.org/0000-0002-6686-2266
Constantino González-SalazarCentro de Ciencias de la Complejidad Universidad Nacional Autónoma de México Mexico City Mexico.ORCID https://orcid.org/0000-0001-7347-714X
Juan M BarriosComisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO) Mexico City Mexico.
Juan Carlos Salazar CarrilloComisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO) Mexico City Mexico.
Everardo Robredo EzquivelzetaComisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO) Mexico City Mexico.
Enrique Del Callejo CanalCentro de Ciencias de la Complejidad Universidad Nacional Autónoma de México Mexico City Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The modeling of ecological data that include both abiotic and biotic factors is fundamental to our understanding of ecosystems. Repositories of biodiversity data, such as GBIF, iDigBio, Atlas of Living Australia, and SNIB (Mexico's National System of Biodiversity Information), contain a great deal of information that can lead to knowledge discovery about ecosystems. However, there is a lack of tools with which to efficiently extract such knowledge. In this paper, we present SPECIES, an open, web-based platform designed to extract implicit information contained in large scale sets of ecological data. SPECIES is based on a tested methodology, wherein the correlations of variables of arbitrary type and spatial resolution, both biotic and abiotic, discrete and continuous, may be explored from both niche and network perspectives. In distinction to other modeling systems, SPECIES is a full stack exploratory tool that integrates the three basic components: data (which is incrementally growing), a statistical modeling and analysis engine, and an interactive visualization front end. Combined, these components provide a powerful tool that may guide ecologists toward new insights. SPECIES is optimized to support fast hypothesis prototyping and testing, analyzing thousands of biotic and abiotic variables, and presenting descriptive results to the user at different levels of detail. SPECIES is an open-access platform available online (http://species.conabio.gob.mx), that is, powerful, flexible, and easy to use. It allows for the exploration and incorporation of ecological data and its subsequent integration into predictive models for both potential ecological niche and geographic distribution. It also provides an ecosystemic, network-based analysis that may guide the researcher in identifying relations between different biota, such as the relation between disease vectors and potential disease hosts.

Indexed as

data miningecologynetworksniche modeling

Identifiers

PMID30847061
PMCPMC6392378

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.