Ecological Applications · 2013 · 39 citations · 49 references
Natural ResourcesEcologyForestryForest InventoryForest ManagementRestoration EcologyForest HistoryForest Land ManagementForest RegenerationForest SuccessionLand UseRegeneration InventoryDensity Dependence In RegenerationForest PlantationsForest Use ChangeHistorical Land Use AnalysisHistorical Land-use PatternsNative Species RegenerationNatural Forest RegenerationTree Density Effects
Most of the world's plantations were established on previously disturbed sites with an intensive land-use history. Our general hypothesis was that native forest regeneration within forest plantations depends largely on in situ biological legacies as a source of propagules. To test this hypothesis, we analyzed native oak regeneration in 168 pine plantation plots in southern Spain in relation to land use in 1956, oak patch proximity, and pine tree density. Historical land-use patterns were determined from aerial photography from 1956, and these were compared with inventory data from 2004-2005 and additional orthophoto images. Our results indicate that oak forest regeneration in pine plantations depends largely on land-use legacies, although nearby, well-conserved areas can provide propagules for colonization from outside the plantation, and pine tree density also affected oak recruit density. More intense land uses in the past meant fewer biological legacies and, therefore, lower likelihood of regenerating native forest. That is, oak recruit density was lower when land use in 1956 was croplands (0.004 +/- 0.002 recruits/m2 [mean +/- SE]) or pasture (0.081 +/- 0.054 recruits/m2) instead of shrubland (0.098 +/- 0.031 recruits/m2) or oak formations (0.314 +/- 0.080 recruits/m2). Our study shows that land use in the past was more important than propagule source distance or pine tree density in explaining levels of native forest regeneration in plantations. Thus, strategies for restoring native oak forests in pine plantations may benefit from considering land-use legacies as well as distance to propagule sources and pine density.
49
R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses
Quang Vuong · Econometrica · 1989 · 6K citations
Regression Models for Count Data in<i>R</i>
Achim Zeileis, Christian Kleiber, Simon Jackman · Journal of Statistical Software · 2008 · 2.4K citations · Full text