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1. Considerable debate surrounds the extent to which tropical forests can be managed for resource extraction while conserving biodiversity and ecosystem properties, which depend on functional composition. Here we evaluate the compatibility of these aims by examining the effects of logging on taxonomic and functional diversity and composition in a tropical forest. 2. Twenty years after selective logging, we inventoried 4140 stems regenerating in logging gaps and adjacent undisturbed areas, and we integrated a database of 13 functional traits describing leaf and wood economics of tropical trees. 3. We found no differences in taxonomic and functional richness among habitats, but logging gaps had significantly higher taxonomic and functional evenness. 4. Logging also effected striking, long-term changes in both species and functional composition. In particular, the xylem density of recruits in logging gaps was 6% less than in unlogged forests, leaves were 11% less tough and had 6—13% greater mineral nutrient concentrations. 5. Synthesis and applications. Our results suggest that managers of tropical forests should limit overall surface area converted to logging gaps by creating fewer, larger gaps during selective logging, to reduce impacts on the taxonomic and functional composition of the regenerating stand.

Studying regeneration processes in oak-dominated forests requires a multi-faceted approach that considers local factors, disturbances, management actions, and tree responses. Our aims were to quantify the carbon and water-use responses of saplings and evaluate ecological consequences at the early tree regeneration phase of a pedunculate oak-hornbeam forest. We measured plant eco-physiological parameters using an open-chamber IRGA equipment in large experimental canopy gaps (instantaneous field data) and greenhouse (climate-controlled reference data) conditions. We used the non-parametric Kruskal–Wallis ANOVA test to analyze differences and similarities in the gas-exchange response. Functional fingerprints indicated shared resource use and efficiency functions at species-specific performance levels with temporal variations. Medium-level and seasonally balanced carbon uptake and water-use functions characterized pedunculate oak (Quercus robur L.) and European hornbeam (Carpinus betulus L.). In contrast, the response patterns in wild cherry (Prunus avium (L.) L.) and green ash (Fraxinus pennsylvanica Marshall) were dominated by water use. Goat willow (Salix caprea L.) had consistently elevated gas-exchange levels with the largest seasonal variation among the study species. We found that trees could be ranked on a relative isohydric-to-anisohydric scale regarding their species–environment interaction. According to the carbon-gain response pattern coupling with a non-structural carbohydrate exchange scheme, we were able to classify tree species as having medium- and long-term carbon resource management. In conclusion, spatially heterogeneous and temporally balanced canopy gaps facilitate tree species’ development and mixed-stand regeneration by providing a functionally diversifying recruiting environment.

1. Variation in forest gap size and duration are a result of spatial contiguity and continuity of gap infilling and tree mortality over time, which influences both species recruitment and successional pathways. 2. As many gaps in boreal forests are small, their size and duration will affect the conditions influencing species recruitment. We investigate the spatial dynamics of these gaps (i.e. those which are persistent, ephemeral, expanding, displaced or disappearing) and tested whether gap spatio-temporal patterns are consistent over different temporal periods (1998—2003 and 2003—2007). 3. Forest canopy gaps were reconstructed for three plots (10, 10 and 6 ha in size) in southern boreal mixedwood forests around Lake Duparquet, north-western Quebec (Canada), using a time series of high-resolution canopy surface profiles from three light and ranging detection (lidar) system surveys during a 9-year window. High-resolution images were used to individually identify early and late successional gap makers. Dynamic changes in canopy gaps over a 9-year period were investigated by implementing concepts of random set theory within a temporal GIS framework. Mortality was higher on the gap edges than in the forest interior, and shade tolerant species were more likely to be gap makers than shade intolerant species. Edge trees that died causing the expansion of gaps were much smaller than trees creating new gaps. Although the overall gap size distribution was consistent over the 9 years studied, the proportion of the total area opening and closing varied between periods. Independent analyses of time windows show an abundance of small gaps (below 40 cm²) appearing and disappearing; however, analysis of spatial contiguity shows that the majority (over 80%) of gaps of all sizes were displaced and/or expanded. 4. Synthesis. Contrary to the previous perception that small gaps are ephemeral, which would favour the recruitment of late successional species, our findings indicate that gap displacement and expansion may be a mechanism explaining the maintenance of favourable conditions for the recruitment of shade intolerant individuals, which has been previously observed in high-latitude old-growth boreal forests.

We provide a study on long-term canopy gap dynamics in the Žofin Virgin Forest (total area 98 ha), which has been strictly protected since 1838. Our aims were i) to describe the size distribution of gaps at a given time; ii) to determine the area where dynamic processes occurred within a given period; and iii) to determine the role of deciduous versus coniferous trees in gap formation. The fate of individual gaps was followed in a 47-ha beech-dominated part of the reserve by analyzing aerial photographs taken in 1971, 1983, 1991, and 2004. The role of individual trees in canopy gap dynamics was studied by combining gap distribution maps with stem position maps of 1975 and 1997 for a 10-ha sample plot. We showed that i) total gap area (9–11%) and average gap size (88–99 m2) was stable during the 33-y study period; ii) canopy dynamics occurred in 0.1% of the area annually; iii) most gaps were created by the simultaneous death of 1–3 canopy trees; iv) death of deciduous trees played a more important role in the creation of gaps than their proportion among dead trees would suggest; and v) tree size and neighbourhood also determined if a dead tree became a gap maker. Nomenclature: Jalas & Suominen, 1988.

Patch dynamics, tree injury and mortality, and coarse woody detritus were quantified to examine the ecological impacts of Hurricane Fran on an oak-hickory-pine forest near Chapel Hill, NC. Data from long-term vegetation plots (1990-1997) and aerial photographs (1998) indicated that this 1996 storm caused patchy disturbance of intermediate severity (10-50% tree mortality; Woods, J Ecol 92:464-476, 2004). The area in large disturbance patches (>0.1 ha) increased from <1% to approximately 4% of the forested landscape. Of the forty-two 0.1-ha plots that were studied, 23 were damaged by the storm and lost 1-66% of their original live basal area. Although the remaining 19 plots gained basal area (1-15% increase), across all 42 stands basal area decreased by 17% because of storm impacts. Overall mortality of trees >10 cm dbh was 18%. The basal area of standing dead trees after the storm was 0.9 m²/ha, which was not substantially different from the original value of 0.7 m²/ha. In contrast, the volume and mass of fallen dead trees after the storm (129 m³/ha; 55 Mg/ha) were 6.1 and 7.9 times greater than the original levels (21 m³/ha; 7 Mg/ha), respectively. Uprooting was the most frequent type of damage, and it increased with tree size. However, two other forms of injury, severe canopy breakage and toppling by other trees, decreased with increasing tree size. Two dominant oak species of intermediate shade-tolerance suffered the largest losses in basal area (30-41% lost). Before the storm they comprised almost half of the total basal area in a forest of 13% shade-tolerant, 69% intermediate, and 18% shade-intolerant trees. Recovery is expected to differ with respect to vegetation (e.g., species composition and diversity) and ecosystem properties (e.g., biomass, detritus mass, and carbon balance). Vegetation may not revert to its former composition; however, reversion of biomass, detritus mass, and carbon balance to pre-storm conditions is projected to occur within a few decades. For example, the net change in ecosystem carbon balance may initially be negative from losses to decomposition, but it is expected to be positive within a decade after the storm. Repeated intermediate-disturbance events of this nature would likely have cumulative effects, particularly on vegetation properties.

Despite considerable interest in the dynamics of populations subject to temporally varying environments, alternate population growth rates and their sensitivities remain incompletely understood. For a Markovian environment, we compare and contrast the meanings of the stochastic growth rate ( \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $\\lambda _{\\mathrm{S}\\,}$ \\end{document} ), the growth rate of average population ( \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $\\lambda _{\\mathrm{M}\\,}$ \\end{document} ), the growth rate for average transition rates ( \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $\\lambda _{\\mathrm{A}\\,}$ \\end{document} ), and the growth rate of an aggregate represented by a megamatrix (shown here to equal \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $\\lambda _{\\mathrm{M}\\,}$ \\end{document} ). We distinguish these growth rates by the averages that define them. We illustrate our results using data on an understory shrub in a hurricane‐disturbed landscape, employing a range of hurricane frequencies. We demonstrate important differences among growth rates: \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $\\lambda _{\\mathrm{S}\\,}< \\lambda _{\\mathrm{M}\\,}$ \\end{document} , but \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $\\lambda _{\\mathrm{A}\\,}$ \\end{document} can be < or > \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $\\lambda _{\\mathrm{M}\\,}$ \\end{document} . We show that stochastic elasticity, \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $E^{\\mathrm{S}\\,}_{ij}$ \\end{document} , and megamatrix elasticity, \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $E^{\\mathrm{M}\\,}_{ij}$ \\end{document} , describe a complex perturbation of both means and variances of rates by the same proportion. Megamatrix elasticities respond slightly and stochastic elasticities respond strongly to changing the frequency of disturbance in the habitat (in our example, the frequency of hurricanes). The elasticity \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $E^{\\mathrm{A}\\,}_{ij}$ \\end{document} of \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $\\lambda _{\\mathrm{A}\\,}$ \\end{document} does not predict changes in the other elasticities. Because \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $E^{\\mathrm{S}\\,}$ \\end{document} , although commonly utilized, is difficult to interpret, we introduce elasticities with a more direct interpretation: \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $E^{\\mathrm{S}\\,\\mu }$ \\end{document} for perturbations of means and \\documentclass{aastex} \\usepackage{amsbsy} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{bm} \\usepackage{mathrsfs} \\usepackage{pifont} \\usepackage{stmaryrd} \\usepackage{textcomp} \\usepackage{portland,xspace} \\usepackage{amsmath,amsxtra} \\usepackage[OT2,OT1]{fontenc} \\newcommand\\cyr{ \\renewcommand\\rmdefault{wncyr} \\renewcommand\\sfdefault{wncyss} \\renewcommand\\encodingdefault{OT2} \\normalfont \\selectfont} \\DeclareTextFontCommand{\\textcyr}{\\cyr} \\pagestyle{empty} \\DeclareMathSizes{10}{9}{7}{6} \\begin{document} \\landscape $E^{\\mathrm{S}\\,\\sigma }$ \\end{document} for variances. We argue that a fundamental tool for studying selection pressures in varying environments is the response of growth rate to vital rates in all habitat states.

Interspecific differences in tree performance due to variation in resource availability are expected to influence the structure and dynamics of tropical forest communities. Patterns of mortality and growth over 32 mo in 11 species of Macaranga were analyzed to investigate factors influencing tree spatial distributions and the dynamics of early successional communities. Tree performance was assessed in relation to variation in light levels, soil texture, and tree ontogeny. Rates of mortality and growth varied by over an order of magnitude among species. Species common in high-light microsites had higher mortality and growth rates. Higher low-light mortality for these species reflected lower shade tolerances, supporting the view that shade tolerance involves a trade-off between high-light growth and low-light mortality. Logistic and multiple regressions were used to test for independent effects of tree size and microenvironment on performance in the 11 species. Mortality and growth were significantly related to tree size in nine and eight species, respectively. Higher mortality and lower growth rates for juvenile trees were common. Despite positive correlations between light availability and tree size, mortality rates increased in three species, and growth rates decreased in four species at larger tree sizes. This pattern was particularly strong in smaller statured shade-intolerant species and may reflect changes in biomass allocation following reproductive onset. Declines in growth at larger tree sizes for only some species resulted in changes in species' performance rankings through succession. Low-light mortality rates were strongly correlated with species' distributions in the forest with respect to light levels, whereas biases in distributions with respect to soil texture were not supported by differential mortality. For all trees pooled and in several species, growth showed a threshold response to light levels, being light-limited in low light but not in high light. Across all light levels, soil texture significantly influenced growth in six species. Five species and all trees pooled had significantly lower growth on the more nutrient-poor and potentially drought-prone sandy soils. The dynamics of Macaranga-dominated early successional communities are strongly influenced by soil resource and light availability, coupled with species-specific ontogenetic trajectories of performance.

Cove forests of the Great Smoky Mountains are North American examples of old-growth temperate forest. Ecological attributes of seven stands were studied using one 0.6 - 1.0 ha plot per stand. Stand basal area (39 - 55 m2/ha) and biomass (326 - 471 Mg/ha) were high for temperate deciduous forest. Density ranged from 577 to 1075 stems/ha. All stands had a mixture of deciduous canopy species. Only rarely did a single species comprise more than half of the stand by density, basal area or biomass. Shade-intolerant species were present at low levels (1 - 5 % of total stand density). A wide range of stem diameters was characteristic of most species. However, some species lacked small stems, indicating discontinuous regeneration. Stands tended to have 10 - 20 tree species per ha and at least five species had biomass levels > 10 Mg/ha, indicating high evenness. Canopy gaps covered 10 % of the total area (2 - 21 % by stand). Gaps and conspecific patches of canopy trees > 0.05 ha in size were infrequent. Spatial analyses revealed a variety of patterns among species at inter-tree distances of 1 to 25 m. When all species were combined, juveniles showed aggregation, and adults were often hyperdispersed. Analyses for individual species confirmed that the mosaic of canopy species is influenced by non-random spatial processes. Adults of several species were aggregated at distances > 10 m. Juveniles of all major species exhibited aggregation. Several species exhibited regeneration near conspecific adults. This pattern suggested limited mobility for such species within the shifting mosaic. A diverse patchwork resulted despite the fact that many species did not exhibit segregation of adults and juveniles. Further understanding of patch dynamics and the potential for compositional steady state in cove forests requires long-term study with spatial data.

At Murder Creek Research Natural Area, Georgia, USA, we compared structural characteristics of late-successional pine-hardwood stands two to three years after infestation by southern pine beetle (Dendroctonus frontalis Zimmerman) to those of adjacent noninfested stands. Death of up to eight Pinus taeda L. and P. echinata Mill, per mortality patch reduced stem density of pines from 399 to 205 trees ha⁻¹. Stand basal area and average diameter of pines in beetle-infested stands (9.0 m² ha⁻¹ and 26.9 cm, respectively) were less than those of noninfested stands (30.6 m² ha⁻¹ and 38.5 cm, respectively). Stand basal area of hardwoods in southern pine beetle-infested stands (9.1 m² ha⁻¹) was less than that of noninfested stands (14.5 m² ha⁻¹) primarily because of lower abundances of Liquidambar styraciflua L. and Acer barbatum Michx. However, tree species diversity in beetle-infested stands exceeded that of noninfested stands (Simpson's indices of 0.69 and 0.55, respectively) because proportionate abundance of hardwoods (67% and 33% of total stand basal area, respectively) was increased by the death of pines. Results indicate that small patch mortality from southern pine beetle increased structural complexity of late-successional pine-hardwood stands by causing localized reductions in stem density of large pines (and therefore reduced susceptibility to future beetle attacks) and associated increases in tree species diversity. Development of several old-growth characteristics, particularly increased abundance of snags and dominance by late-successional hardwood species, has been accelerated by southern pine beetle infestation.

Tropical tree regeneration results from a complex interplay of biotic and abiotic factors: the actions of seed dispersers, seed predators, pathogens, and herbivores influence the distribution patterns of seedlings within an environment that is heterogeneous with respect to the light, water, and soil nutrients required for eventual growth to the canopy. Continuation of observations for six years has now provided long-term data on differential seedling performance that suggests how canopy gap dynamics may influence Dipteryx regeneration.