Explore the vast range of titles available.

European forests have a prominent role in the global carbon cycle and an increase in carbon storage has been consistently reported during the twentieth century. Any further increase in forest carbon storage, however, could be hampered by increases in aridity and extreme climatic events. Here, we use forest inventory data to identify the relative importance of stand structure (stand basal area and mean d.b.h.), mean climate (water availability), and recent climate change (temperature and precipitation anomalies) on forest basal area change during the late twentieth century in three major European biomes. Using linear mixed-effects models we observed that stand structure, mean climate, and recent climatic change strongly interact to modulate basal area change. Although we observed a net increment in stand basal area during the late twentieth century, we found the highest basal area increments in forests with medium stand basal areas and small to medium-sized trees. Stand basal area increases correlated positively with water availability and were enhanced in warmer areas. Recent climatic warming caused an increase in stand basal area, but this increase was offset by water availability. Based on recent trends in basal area change, we conclude that the potential rate of aboveground carbon accumulation in European forests strongly depends on both stand structure and concomitant climate warming, adding weight to suggestions that European carbon stocks may saturate in the near future.

The stand basal area, closely related to age, site quality, and stand density, is an important factor for predicting forest growth and yield. The accurate estimation of site quality is especially a key component in the stand basal area model. We utilized sample plots with Picea asperata Mast. as the dominant species in the multi-period National Forest Inventory (NFI) dataset to establish a site index (SI) model including climate effects through the difference form of theoretical growth equations and mixed-effects models. We combined the SI calculated from the SI model, stand age, and stand density index to construct a basal area growth model for Picea asperata Mast. stands. The results show that the Korf model is the best SI base model for Picea asperata Mast. The mean temperatures in summer and winter precipitation were used as the fixed parameters to construct a nonlinear model. Ultimately, elevation, origin, and region, as random effects, were incorporated into the mixed-effects model. The coefficients (R2) of determination of the base model, the nonlinear model including climate, and the nonlinear mixed-effects model are 0.869, 0.899, and 0.921, with root-mean-square errors (RMSEs) of 1.320, 1.315, and 1.301, respectively. Among the basal area models, the Richards model has higher precision. And the basal area model including an SI incorporating climatic factors had a higher determination coefficient (R2) of 0.918 than that of the model including an SI without considering climatic effects. The mixed-effects model incorporating climatic and topographic factors shows a better fitting performance of SI, resulting in a higher precision of the basal area model. This indicates that in the development of forest growth models, both biophysical and climatic factors should be comprehensively considered.

Stand basal area (SBA) is an important variable in the prediction of forest growth and harvest yield. However, achieving the additivity of SBA models for multiple tree species in the complex structure of broad-leaved mixed forests is an urgent scientific issue in the study of accurately predicting the SBA of mixed forests. This study used data from 58 sample plots (30 m × 30 m) for Populus davidiana × Betula platyphylla broad-leaved mixed forests to construct the SBA basic model based on nonlinear least squares regression (NLS). Adjustment in proportion (AP) and nonlinear seemingly unrelated regression (NSUR) were used to construct a multi-species additive basal area prediction model. The results identified the Richards model (M6) and Korf model (M1) as optimal for predicting the SBA of P. davidiana and B. platyphylla, respectively. The SBA models incorporate site quality, stand density index, and age at 1.3 m above ground level, which improves the prediction accuracy of basal area. Compared to AP, NSUR is an effective method for addressing the additivity of basal area in multi-species mixed forests. The results of this study can provide a scientific basis for optimizing stand structure and accurately predicting SBA in multi-species mixed forests.

Stand growth and yield models include whole-stand models, individual-tree models, and diameter-distribution models. Based on the growth data of Chinese pine (Pinus tabulaeformis Carr.) in Beijing, forecast combination was used to adjust predicted stand basal areas from these three types of models. The forecast combination method combines information and disperses errors from different models to improve forecast performance. In this study, weights of the three model estimates used in the forecast combination estimator were determined by the optimal weight method. Results showed that the forecast combination method provided overall better predictions of stand basal area than the three types of models. It also improved the compatibility of stand basal area growth predicted from models of different resolutions and provided a method for integration of stand basal area.

Forest diversity-productivity relationships have been intensively investigated in recent decades. However, few studies have considered the interplay between species and structural diversity in driving productivity. We analyzed these factors using data from 52 permanent plots in southwestern Germany with more than 53,000 repeated tree measurements. We used basal area increment as a proxy for productivity and hypothesized that: (1) structural diversity would increase tree and stand productivity, (2) diversity-productivity relationships would be weaker for species diversity than for structural diversity, and (3) species diversity would also indirectly impact stand productivity via changes in size structure. We measured diversity using distance-independent indices indices. We fitted separate linear mixed-effects models for fir, spruce and beech at the tree level, whereas at the stand level we pooled all available data. We tested our third hypothesis using structural equation modeling. Structural and species diversity acted as direct and independent drivers of stand productivity, with structural diversity being a slightly better predictor. Structural diversity, but not species diversity, had a significant, albeit asymmetric, effect on tree productivity. The functioning of structurally diverse, mixed forests is influenced by both structural and species diversity. These sources of trait diversity contribute to increased vertical stratification and crown plasticity, which in turn diminish competitive interferences and lead to more densely packed canopies per unit area. Our research highlights the positive effects of species diversity and structural diversity on forest productivity and ecosystem dynamics.

Significance Although forest succession has been approached as a predictable process, successional trajectories vary widely, even among nearby stands with similar environmental conditions and disturbance histories. We quantified predictability and uncertainty during tropical forest succession using dynamical models describing the interactions among stem density, basal area, and species density over time. We showed that the trajectories of these forest attributes were poorly predicted by stand age and varied significantly within and among sites. Our models reproduced the general successional trends observed, but high levels of noise were needed to increase model predictability. These levels of uncertainty call into question the premise that successional processes are consistent over space and time, and challenge the way ecologists view tropical forest regeneration. Although forest succession has traditionally been approached as a deterministic process, successional trajectories of vegetation change vary widely, even among nearby stands with similar environmental conditions and disturbance histories. Here, we provide the first attempt, to our knowledge, to quantify predictability and uncertainty during succession based on the most extensive long-term datasets ever assembled for Neotropical forests. We develop a novel approach that integrates deterministic and stochastic components into different candidate models describing the dynamical interactions among three widely used and interrelated forest attributes—stem density, basal area, and species density. Within each of the seven study sites, successional trajectories were highly idiosyncratic, even when controlling for prior land use, environment, and initial conditions in these attributes. Plot factors were far more important than stand age in explaining successional trajectories. For each site, the best-fit model was able to capture the complete set of time series in certain attributes only when both the deterministic and stochastic components were set to similar magnitudes. Surprisingly, predictability of stem density, basal area, and species density did not show consistent trends across attributes, study sites, or land use history, and was independent of plot size and time series length. The model developed here represents the best approach, to date, for characterizing autogenic successional dynamics and demonstrates the low predictability of successional trajectories. These high levels of uncertainty suggest that the impacts of allogenic factors on rates of change during tropical forest succession are far more pervasive than previously thought, challenging the way ecologists view and investigate forest regeneration.

Some disturbances can drive ecological systems to abrupt shifts between alternative stages (tipping points) when critical transitions occur. Drought‐induced tree death can be considered as a nonlinear shift in tree vigour and growth. However, at what point do trees become predisposed to drought‐related dieback and which factors determine this (tipping) point? We investigated these questions by characterizing the responses of three tree species, silver fir (Abies alba), Scots pine (Pinus sylvestris) and Aleppo pine (Pinus halepensis), to a severe drought event. We compared basal area increment (BAI) trends and responses to climate and drought in declining (very defoliated and dying) vs. non‐declining (slightly or not defoliated) trees by using generalized additive mixed models. Defoliation, BAI and sapwood production were related to functional proxies of tree vigour measured at the onset and end of the drought (non‐structural carbohydrate concentrations, needle N content and C isotopic discrimination, presence of wood‐inhabiting fungi). We evaluated whether early warning signals (increases in synchronicity among trees or in autocorrelation and standard deviation) could be extracted from the BAI series prior to tree death. Declining silver fir and Scots pine trees showed less growth than non‐declining trees one to three decades, respectively, before the drought event, whereas Aleppo pines showed growth decline irrespective of tree defoliation. At the end of the drought period, all species showed increased defoliation and a related reduction in the concentration of sapwood soluble sugars. Defoliation was constrained by the BAI of the previous 5 years and sapwood production. No specific wood‐inhabiting fungi were found in post‐drought declining trees apart from blue‐stain fungi, which extensively affected damaged Scots pines. Declining silver firs showed increases in BAI autocorrelation and variability prior to tree death. Synthesis. Early warning signals of drought‐triggered mortality seem to be species specific and reflect how different tree species cope with drought stress. Highly correlated declining growth patterns during drought can serve as a signal in silver fir, whereas changes in the content of sapwood soluble sugars are suitable vigour proxies for Scots and Aleppo pines. Longer growth and defoliation series, additional vigour parameters and multi‐species comparisons are required to understand and predict drought‐induced tree death.

1. There is increasing evidence that species diversity enhances the temporal stability (TS) of community productivity in different ecosystems, although its effect at the population and tree levels seems to be negative or neutral. Asynchrony in species responses to environmental conditions was found to be one of the main drivers of this stabilizing process. However, the effect of species mixing on the stability of productivity, and the relative importance of the associated mechanisms, remain poorly understood in forest communities. 2. We investigated the way mixing species influenced the TS of productivity in Pinus sylvestris L. and Fagus sylvatica L. forests, and attempted to determine the main drivers among overyielding, asynchrony between species annual growth responses to environmental conditions, and temporal shifts in species interactions. We used a network of 93 experimental plots distributed across Europe to compare the TS of basal area growth over a 15-year period (1999-2013) in mixed and monospecific forest stands at different organizational levels, namely the community, population and individual tree levels. 3. Mixed stands showed a higher TS of basal area growth than monospecific stands at the community level, but not at the population or individual tree levels. The TS at the community level was related to asynchrony between species growth in mixtures, but not to overyielding nor to asynchrony between species growth in monospecific stands. Temporal shifts in species interactions were also related to asynchrony and to the mixing effect on the TS. 4. Synthesis. Our findings confirm that species mixing can stabilize productivity at the community level, whereas there is a neutral or negative effect on stability at the population and individual tree levels. The contrasting findings regarding the relationships between the temporal stability and asynchrony in species growth in mixed and monospecific stands suggest that the main driver in the stabilizing process may be the temporal niche complementarity between species rather than differences in species' intrinsic responses to environmental conditions.

Mixing of complementary tree species may increase stand productivity, mitigate the effects of drought and other risks, and pave the way to forest production systems which may be more resource-use efficient and stable in the face of climate change. However, systematic empirical studies on mixing effects are still missing for many commercially important and widespread species combinations. Here we studied the growth of Scots pine (Pinus sylvestris L.) and European beech (Fagus sylvatica L.) in mixed versus pure stands on 32 triplets located along a productivity gradient through Europe, reaching from Sweden to Bulgaria and from Spain to the Ukraine. Stand inventory and taking increment cores on the mainly 60–80 year-old trees and 0.02–1.55 ha sized, fully stocked plots provided insight how species mixing modifies the structure, dynamics and productivity compared with neighbouring pure stands. In mixture standing volume (+12 %), stand density (+20 %), basal area growth (+12 %), and stand volume growth (+8 %) were higher than the weighted mean of the neighbouring pure stands. Scots pine and European beech contributed rather equally to the overyielding and overdensity. In mixed stands mean diameter (+20 %) and height (+6 %) of Scots pine was ahead, while both diameter and height growth of European beech were behind (−8 %). The overyielding and overdensity were independent of the site index, the stand growth and yield, and climatic variables despite the wide variation in precipitation (520–1175 mm year⁻¹), mean annual temperature (6–10.5 °C), and the drought index by de Martonne (28–61 mm °C⁻¹) on the sites. Therefore, this species combination is potentially useful for increasing productivity across a wide range of site and climatic conditions. Given the significant overyielding of stand basal area growth but the absence of any relationship with site index and climatic variables, we hypothesize that the overyielding and overdensity results from several different types of interactions (light-, water-, and nutrient-related) that are all important in different circumstances. We discuss the relevance of the results for ecological theory and for the ongoing silvicultural transition from pure to mixed stands and their adaptation to climate change.

We document changes in forest structure between historical (1930s) and contemporary (2000s) surveys of California vegetation through comparisons of tree abundance and size across the state and within several ecoregions. Across California, tree density in forested regions increased by 30% between the two time periods, whereas forest biomass in the same regions declined, as indicated by a 19% reduction in basal area. These changes reflect a demographic shift in forest structure: larger trees (>61 cm diameter at breast height) have declined, whereas smaller trees (<30 cm) have increased. Large tree declines were found in all surveyed regions of California, whereas small tree increases were found in every region except the south and central coast. Large tree declines were more severe in areas experiencing greater increases in climaticwater deficit since the 1930s, based on a hydrologic model of water balance for historical climates through the 20th century. Forest composition in California in the last century has also shifted toward increased dominance by oaks relative to pines, a pattern consistent with warming and increased water stress, and also with paleohistoric shifts in vegetation in California over the last 150,000 y.