Evidence map›Paper›PMID 25975440›Full record

ArticleEnvironmental management2015

Unraveling Landscape Complexity: Land Use/Land Cover Changes and Landscape Pattern Dynamics (1954-2008) in Contrasting Peri-Urban and Agro-Forest Regions of Northern Italy.

D Smiraglia, T Ceccarelli, S Bajocco, L Perini, L Salvati

Abstract read
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Article in Environmental management, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

5 authors.

D SmiragliaConsiglio per la ricerca in agricoltura e l'analisi dell'economia agraria - Research Unit of Climatology and Meteorology applied to Agriculture (CRA-CMA), Via del Caravita 7/a, 00186, Rome, Italy, daniela.smiraglia@entecra.it.
T Ceccarelli
S Bajocco
L Perini
L Salvati

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study implements an exploratory data analysis of landscape metrics and a change detection analysis of land use and population density to assess landscape dynamics (1954-2008) in two physiographic zones (plain and hilly-mountain area) of Emilia Romagna, northern Italy. The two areas are characterized by different landscape types: a mixed urban-rural landscape dominated by arable land and peri-urban settlements in the plain and a traditional agro-forest landscape in the hilly-mountain area with deciduous and conifer forests, scrublands, meadows, and crop mosaic. Urbanization and, to a lesser extent, agricultural intensification were identified as the processes underlying landscape change in the plain. Land abandonment determining natural forestation and re-forestation driven by man was identified as the process of change most representative of the hilly-mountain area. Trends in landscape metrics indicate a shift toward more fragmented and convoluted patterns in both areas. Number of patches, the interspersion and juxtaposition index, and the large patch index are the metrics discriminating the two areas in terms of landscape patterns in 1954. In 2008, mean patch size, edge density, interspersion and juxtaposition index, and mean Euclidean nearest neighbor distance were the metrics with the most different spatial patterns in the two areas. The exploratory data analysis of landscape metrics contributed to link changes over time in both landscape composition and configuration providing a comprehensive picture of landscape transformations in a wealthy European region. Evidence from this study are hoped to inform sustainable land management designed for homogeneous landscape units in similar socioeconomic contexts.

Indexed as

ForestsAgricultureEnvironmental MonitoringItalyMultivariate AnalysisUrbanization

Identifiers

What OpenQuestion holds

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Registered trials

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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.