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Aim: Large trees (d.b.h. ≥70 cm) store large amounts of biomass. Several studies suggest that large trees may be vulnerable to changing climate, potentially leading to declining forest biomass storage. Here we determine the importance of large trees for tropical forest biomass storage and explore which intrinsic (species trait) and extrinsic (environment) variables are associated with the density of large trees and forest biomass at continental and pan-tropical scales. Location: Pan-tropical. Methods: Aboveground biomass (AGB) was calculated for 120 intact lowland moist forest locations. Linear regression was used to calculate variation in AGB explained by the density of large trees. Akaike information criterion weights (AICcwi) were used to calculate averaged correlation coefficients for all possible multiple regression models between AGB/density of large trees and environmental and species trait variables correcting for spatial autocorrelation. Results: Density of large trees explained c. 70% of the variation in pan-tropical AGB and was also responsible for significantly lower AGB in Neotropical [287.8 (mean) ± 105.0 (SD) Mg ha⁻¹] versus Palaeotropical forests (Africa 418.3 ± 91.8 Mg ha⁻¹; Asia 393.3 ± 109.3 Mg ha⁻¹). Pan-tropical variation in density of large trees and AGB was associated with soil coarseness (negative), soil fertility (positive), community wood density (positive) and dominance of wind dispersed species (positive), temperature in the coldest month (negative), temperature in the warmest month (negative) and rainfall in the wettest month (positive), but results were not always consistent among continents. Main conclusions: Density of large trees and AGB were significantly associated with climatic variables, indicating that climate change will affect tropical forest biomass storage. Species trait composition will interact with these future biomass changes as they are also affected by a warmer climate. Given the importance of large trees for variation in AGB across the tropics, and their sensitivity to climate change, we emphasize the need for in-depth analyses of the community dynamics of large trees.

Understanding how plants are constructed-i.e., how key size dimensions and the amount of mass invested in different tissues varies among individuals-is essential for modeling plant growth, carbon stocks, and energy fluxes in the terrestrial biosphere. Allocation patterns can differ through ontogeny, but also among coexisting species and among species adapted to different environments. While a variety of models dealing with biomass allocation exist, we lack a synthetic understanding of the underlying processes. This is partly due to the lack of suitable data sets for validating and parameterizing models. To that end, we present the Biomass And Allometry Database (BAAD) for woody plants. The BAAD contains 259 634 measurements collected in 176 different studies, from 21 084 individuals across 678 species. Most of these data come from existing publications. However, raw data were rarely made public at the time of publication. Thus, the BAAD contains data from different studies, transformed into standard units and variable names. The transformations were achieved using a common workflow for all raw data files. Other features that distinguish the BAAD are: (i) measurements were for individual plants rather than stand averages; (ii) individuals spanning a range of sizes were measured; (iii) plants from 0.01-100 m in height were included; and (iv) biomass was estimated directly, i.e., not indirectly via allometric equations (except in very large trees where biomass was estimated from detailed sub-sampling). We included both wild and artificially grown plants. The data set contains the following size metrics: total leaf area; area of stem cross-section including sapwood, heartwood, and bark; height of plant and crown base, crown area, and surface area; and the dry mass of leaf, stem, branches, sapwood, heartwood, bark, coarse roots, and fine root tissues. We also report other properties of individuals (age, leaf size, leaf mass per area, wood density, nitrogen content of leaves and wood), as well as information about the growing environment (location, light, experimental treatment, vegetation type) where available. It is our hope that making these data available will improve our ability to understand plant growth, ecosystem dynamics, and carbon cycling in the world's vegetation.

In coming decades, global climate changes are expected to produce large shifts in vegetation distributions at unprecedented rates. These shifts are expected to be most rapid and extreme at ecotones, the boundaries between ecosystems, particularly those in semiarid landscapes. However, current models do not adequately provide for such rapid effects--particularly those caused by mortality--largely because of the lack of data from field studies. Here we report the most rapid landscape-scale shift of a woody ecotone ever documented: in northern New Mexico in the 1950s, the ecotone between semiarid ponderosa pine forest and pinon-juniper woodland shifted extensively (2 km or more) and rapidly (5 years) through mortality of ponderosa pines in response to a severe drought. This shift has persisted for 40 years. Forest patches within the shift zone became much more fragmented, and soil erosion greatly accelerated. The rapidity and the complex dynamics of the persistent shift point to the need to represent more accurately these dynamics, especially the mortality factor, in assessments of the effects of climate change

The oak, to gain its present most northerly position in North Britain after being driven out by the cold probably had to travel fully six hundred miles, and this without external aid would take something like a million years. (Reid 1899)

Some alien tree species used in commercial forestry and agroforestry cause major problems as invaders of natural and seminatural ecosystems. The magnitude of the problem has increased significantly over the past few decades, with a rapid increase in afforestation and changes in land use. Trends can be explained by analyzing natural experiments created by the widespread planting of a small number of species in different parts of the world. The species that cause the greatest problems are generally those that have been planted most widely and for the longest time. The most affected areas have the longest histories of intensive planting. Pinus spp. are especially problematic, and at least 19 species are invasive over large areas in the southern hemisphere, where some species cause major problems. The most invasive Pinus species have a predictable set of life-history attributes, including low seed mass, short juvenile period, and short interval between large seed crops. Pine invasions have severely impacted large areas of grassland and scrub-brushland in the southern hemisphere by causing shifts in life-form dominance, reduced structural diversity, increased biomass, disruption of prevailing vegetation dynamics, and changing nutrient cycling patterns. The (unavoidable) negative impacts of forestry with alien species are thus spilling over into areas set aside for conservation or water production. There is an urgent need to integrate the various means available for reducing the negative impacts of current invaders and to implement protocols to regulate the translocation of species that are known to be invasive.

The relationship between tree height and diameter is an important element in growth and yield models, in carbon budget and timber volume models, and in the description of stand dynamics. Six non-linear growth functions (i.e. Chapman-Richards, Schnute, Lundqvist/Korf, Weibull, Modified Logistic and Exponential) were fitted to tree height-diameter data of oriental beech in the Hyrcanian mixed hardwood forests of Iran. The predictive performance of these models was in the first place assessed by means of different model evaluation criteria such as adjusted R squared (adj R2), root mean square error (RMSE), Akaike information criterion (AIC), mean difference (MD), mean absolute difference (MAD) and mean square (MS) error criteria. Although each of the six models accounted for approximately 75% of total variation in height, a large difference in asymptotic estimates was observed. Apart from this, the predictive performance of the models was also evaluated by means of cross-validation and by splitting the data into 5-cm diameter classes. Plotting the MD in relation to these diameter at breast height (DBH) classes showed for all growth functions, except for the Modified Logistic function, similar mean prediction errors for small- and medium-sized trees. Large-sized trees, however, showed a higher mean prediction error. The Modified Logistic function showed the worst performance due to a large model bias. The Exponential and Lundqvist/Korf models were discarded due to their showing biologically illogical behavior and unreasonable estimates for the asymptotic coefficient, respectively. Considering all the above-mentioned criteria, the Chapman-Richards, Weibull, and Schnute functions provided the most satisfactory height predictions. However, we would recommend the Chapman-Richards function for further analysis because of its higher predictive performance.

We quantified soil acidity and exchangeable cations in the forest floor and upper 7.5 cm of mineral soil beneath the canopies of individual trees of six different species in a mixed-species forest in northwestern Connecticut. Soil pH decreased in a sequence starting with sugar maple (Acer saccharum) > white ash (Fraxinus americana) > red maple (Acer rubrum) > beech (Fagus grandifolia) > red oak (Quercus rubra) > eastern hemlock (Tsuga canadensis). The differences among species were largest in the forest floor and the top 7.5 cm of mineral soil. Exchangeable Ca and Mg in the 0-7.5 cm mineral soil layer were significantly higher beneath sugar maple than all other species, with the exception of white ash. There were negligible differences among species in the quantity of exchangeable Ca and Mg in the forest floor. In the 0-7.5 cm mineral soil layer, exchangeable Ca was positively correlated with the content of unweathered Ca in the parent material, but the relationship differed among species. There was a large increase in exchangeable Ca in the soils beneath sugar maple but a negligible increase in the soils beneath hemlock and red maple. Exchangeable Al and Fe were highest beneath hemlock and lowest beneath sugar maple. The differences in pH and exchangeable cations between sugar maple and hemlock are likely due to interspecific differences in the introduction of acidity (e.g., organic acids) and Ca uptake and allocation. Observing an association between tree species and specific soil chemical properties within mixed-species stands implies that changes in the distribution and abundance of tree species alters the spatial and temporal pattern of soil acidity and cation cycling in this forest.

Remote sensing of foliar chemistry has been recognized as an important element in producing large-scale, spatially explicit estimates of forest ecosystem function. This study was designed to determine whether data from NASA's Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) could be used to determine forest canopy chemistry at a spatial resolution of 20 m, and if so, to use that information to drive an ecosystem productivity model. Foliage and leaf litter were sampled on 40 plots at Blackhawk Island, Wisconsin, and Harvard Forest, Massachusetts, to determine canopy-level nitrogen and lignin concentrations. At the time of the field sampling, AVIRIS data were acquired for both study areas. Calibration equations were developed, relating nitrogen and lignin to selected first-difference spectral bands ($R^2$ = 0.87 and 0.77, respectively). Calibration equations were evaluated on the basis of inter- and intrasite statistics. These equations were applied to all image pixels to make spatially explicit estimates of canopy nitrogen and lignin for both study sites. These estimates of nitrogen and lignin concentrations were then used with existing models to predict net ecosystem productivity at Harvard Forest and nitrogen mineralization rates at Blackhawk Island.

A spatial and mechanistic model is developed for the dynamics of transition oak-northern hardwoods forests in northeastern North America. The purpose of the model is to extrapolate from measurable fine-scale and short-term interactions among individual trees to large-scale and long-term dynamics of forest communities. Field methods, statistical estimators, and model structure were designed simultaneously to ensure that parameters could be estimated from data collected in the field. This paper documents eight aspects of a three-year study to calibrate, test, and analyze the model for the nine dominant and subdominant tree species in transition oak-northern hardwoods forests: 1) Design and structure of the model. The model makes population dynamic forecasts by predicting the fate of every individual tree throughout its life. Species-specific functions predict each tree's dispersal, establishment, growth, mortality, and fecundity. Trees occupy unique spatial positions, and individual performance is affected by the local availability of resources. Competition is mechanistic; resources available to each tree are reduced by neighbors. Although the model was developed to include light, water, and nitrogen, the version described here includes only competition for light (shading and light-dependent performance) because the field data provide little evidence of competition for nitrogen and water over the range of sites examined. 2) Estimates of the model's parameters for each species. The estimates reveal a variety of \"strategic trade-offs\" among the species. For example, species that grow quickly under high light tend to cast relatively little shade, have low survivorship under low light, and have high dispersal. In contrast, species that grow slowly under high light tend to cast relatively dark shade, and to have high survivorship under low light and low dispersal. These trade-offs define one of two dominant \"axes\" of strategic variation. 3) Community level predictions of the model. The model predicts succession from early dominance by species such as Quercus rubra and Prunus serotina, to late dominance by Fagus grandifolia and Tsuga canadensis, with Betula alleganiensis present as a gap phase species in old-growth stands. The model also predicts that old-growth communities will have intraspecifically clumped and interspecifically segregated spatial distributions. 4) An error analysis that identifies community level predictions that are robust given the level of sampling uncertainty in the study. This analysis translates the statistical uncertainty associated with each parameter estimate into statistical uncertainty in the model's predictions. The robust predictions include those mentioned in aspect (3) above. 5) Sensitivity of the model to changes in initial conditions and to changes in the three parameters not included in the error analysis. For example, the model predicts that initial abundances continue to affect community composition well into succession (> 300 yr for some species). 6) Tests of the system- and community-level predictions of the model against independent data gleaned from other studies. These tests support the predictions found to be robust in the error analysis, including those predictions mentioned in aspect (3) above. 7) Modeling experiments that determine which aspects of individual performance and inter-neighbor competition are responsible for each of the robust predictions identified in aspect (4) above and tested in aspect (6) above. This analysis reveals a wide variety of causal relationships, with most parameters contributing to at least one community level phenomenon. 8) An explanation of the diversity of individual level causes identified in aspect (7). The two \"axes\" describing most of the strategic variation among the species (see [2]), provide a simple explanation of community level pattern in terms of individual level processes.

Using an enrichment procedure, we have cloned and sequenced microsatellite loci from black poplar (Populus nigra L.) and developed primers for sequence-tagged microsatellite (STMS) analysis. Twelve primer pairs for dinucleotide repeats produced fragments of sufficient quality which were polymorphic in P. nigra. Some of them also showed amplification in other Populus species (P deltoides, P. tricocarpa, P. tremula, P. tremuloides, P. candicans, and/or P. lasiocarpa). The best nine and (GT) (GA) microsatellite markers were tested on a set of 23 P. nigra genotypes from all over Europe. The microsatellites were highly polymorphic, with 10-19 different alleles per microsatellite locus among these 23 genotypes. WPMS08 sometimes amplified three fragments. Using the other eight marker loci, the level of heterozygosity among the plants was on average 0.71 (range 0.25-1.00). The microsatellite markers developed will be useful for screening the genetic diversity in natural populations and in gene bank collections.