Forestry An International Journal of Forest Research · 2016 · 59 citations · 51 references
Natural ResourcesEcologyCommunity EcologyForest EcologyForest InventoryForest GrowthForest ProductivityForest Stand DynamicsGrowth MeasurementCompetition In Mixed StandsComplementarity In Mixed StandsGrowth EfficiencyGrowth Of Mixed StandsInter-specific CompetitionIntra-specific CompetitionStand Density IndicesTree Growth Analysis
Increased interest in mixed forests is due to evidence of them being more resource-use efficient and stable forest systems. However, intrinsic and extrinsic factors moderate interspecific species interactions generating different effects in productivity. Here, we explore a method to detect mixing effects in a specific mixture com_x0002_bination (Pinus sylvestris L. and Pinus pinaster Ait.), comparing the growth of mixed stands with that of mono_x0002_cultures. Combined tree and stand-level analyses also helped determine which mixing effects are most important for forest functioning and how changes at one level influence patterns at another level. Data from the Spanish National Forest Inventory were used to compare growth efficiency in mixed and pure stands; we relied on relative stand density indices to determine species-specific site occupancy. This same concept was used to evaluate competition status and inter/intra-specific competition effects as modifiers of potential growth at the tree-level. We observed that growth efficiency in both species increased with the proportion of the complementary species in the stand. At the tree-level, intraspecific competition was higher than interspe_x0002_cific competition in Scots pine tree growth, showing that it had benefited from the mixture. In contrast, mari_x0002_time pine did not show a competitive response to the interspecific interaction, indicating that tree growth was more strongly influenced by the competition structure (size-symmetric and size-asymmetric) than by the spe_x0002_cies of the competitors. Our results highlight the importance of combining stand-level analysis with that of tree-specific competition relationships when studying mixed-species forests.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 353K citations · Full text
Natural Sciences, Computer Science, Statistical Computing +10
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Jordan S. Rosenfeld · Oikos · 2002 · 786 citations