Dataset Information

The glocal forest.

ABSTRACT: Spatial ecological patterns reflect the underlying processes that shape the structure of species and communities. Mechanisms like intra- and inter-specific competition, dispersal and host-pathogen interactions can act over a wide range of scales. Yet, the inference of such processes from patterns is a challenging task. Here we call attention to a quite unexpected phenomenon in the extensively studied tropical forest at the Barro-Colorado Island (BCI): the spatial deployment of (almost) all tree species is statistically equivalent, once distances are normalized by ?0, the typical distance between neighboring conspecific trees. Correlation function, cluster statistics and nearest-neighbor distance distribution become species-independent after this rescaling. Global observables (species frequencies) and local spatial structure appear to be interrelated. This "glocality" suggests a radical interpretation of recent experiments that show a correlation between species' abundance and the negative feedback among conspecifics. For the forest to be glocal, the negative feedback must govern spatial patterns over all scales.

SUBMITTER: Seri E

PROVIDER: S-EPMC4425529 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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The glocal forest.

Seri Efrat E Shtilerman Elad E Shnerb Nadav M NM

PloS one 20150508 5

Spatial ecological patterns reflect the underlying processes that shape the structure of species and communities. Mechanisms like intra- and inter-specific competition, dispersal and host-pathogen interactions can act over a wide range of scales. Yet, the inference of such processes from patterns is a challenging task. Here we call attention to a quite unexpected phenomenon in the extensively studied tropical forest at the Barro-Colorado Island (BCI): the spatial deployment of (almost) all tree ...[more]

PMID: 25955587

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Project description:BackgroundThe ability to apply standard and interoperable solutions for implementing and managing medical registries as well as aggregate, reproduce, and access data sets from legacy formats and platforms to advanced standard formats and operating systems are crucial for both clinical healthcare and biomedical research settings.PurposeOur study describes a reproducible, highly scalable, standard framework for a device registry implementation addressing both local data quality components and global linking problems.Methods and resultsWe developed a device registry framework involving the following steps: (1) Data standards definition and representation of the research workflow, (2) Development of electronic case report forms using REDCap (Research Electronic Data Capture), (3) Data collection according to the clinical research workflow and, (4) Data augmentation by enriching the registry database with local electronic health records, governmental database and linked open data collections, (5) Data quality control and (6) Data dissemination through the registry Web site. Our registry adopted all applicable standardized data elements proposed by American College Cardiology / American Heart Association Clinical Data Standards, as well as variables derived from cardiac devices randomized trials and Clinical Data Interchange Standards Consortium. Local interoperability was performed between REDCap and data derived from Electronic Health Record system. The original data set was also augmented by incorporating the reimbursed values paid by the Brazilian government during a hospitalization for pacemaker implantation. By linking our registry to the open data collection repository Linked Clinical Trials (LinkedCT) we found 130 clinical trials which are potentially correlated with our pacemaker registry.ConclusionThis study demonstrates how standard and reproducible solutions can be applied in the implementation of medical registries to constitute a re-usable framework. Such approach has the potential to facilitate data integration between healthcare and research settings, also being a useful framework to be used in other biomedical registries.

Dataset Information

The glocal forest.

Publications

The glocal forest.

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