Species-area curves, spatial aggregation, and habitat specialization in tropical forests

The relationship between species diversity and sampled area is fundamental to ecology. Traditionally, theories of the species-area relationship have been dominated by random-placement models. Such models were used to formulate the canonical theory of species-area curves and species abundances. In this paper, however, armed with a detailed data set from a moist tropical forest, we investigate the validity of random placement and suggest improved models based upon spatial aggregation. By accounting for intraspecific, small-scale aggregation, we develop a cluster model which reproduces empirical species-area curves with high fidelity. We find that inter-specific aggregation patterns, on the other hand, do not affect the species-area curves significantly. We demonstrate that the tendency for a tree species to aggregate, as well as its average clump size, is not significantly correlated with the species' abundance. In addition, we investigate hierarchical clumping and the extent to which aggregation is driven by topography. We conclude that small-scale phenomena such as dispersal and gap recruitment determine individual tree placement more than adaptation to larger-scale topography.     

森林动态模型概论

讨论了模拟森林林分动态变化的模型,并把模型分为森林生长模型和演替模型。森林生长模型包括：全林分模型、林分级模型和单木模型;演替模型包括马尔可夫类模型和林窗模型。文中给出了演替模型的基本原理和适用性,在比较早期和最新发展的林窗模型后,叙述了林窗模型的新进展。生长和演替模型的结构和数据要求不同决定了它们的在时间和空间上的适应性,最后指出模型将向综合总体方向发展     

Estimating local interaction from spatiotemporal forest data, and Monte Carlo bias correction

We point out a general problem in fitting continuous time spatially explicit models to a temporal sequence of spatial data observed at discrete times. To illustrate the problem, we examined the continuous time Markov model for forest gap dynamics. A forest is assumed to be apportioned into discrete cells (or sites) arranged in a regular square lattice. Each site is characterized as either a gap or a non-gap site according to the vegetation height of trees. The model incorporates the influence of neighboring sites on transition rate: transition rate from a non-gap to a gap site increases linearly with the number of neighbors that are currently in the gap state, and vice versa. We fitted the model to the spatiotemporal data of canopy height observed at the permanent plot in Barro Colorado Island (BCI). When we used the approximate maximum likelihood method to estimate the parameters of the model, the estimated transition rates included a large bias-in particular, the strength of interaction between nearby sites was underestimated. This bias originated from the assumption that each transition between two observation times is independent. The interaction between sites at local scale creates a long chain of transitions within a single census interval, which violates the independence of each transition. We show that a computer-intensive method, called Monte Carlo bias correction (MCBC), is very effective in removing the bias included in the estimate. The global and local gap densities measuring spatial aggregation of gap sites were computed from simulated and real gap dynamics to assess the model. When the approximate likelihood estimates were applied to the model, the predicted local gap density was clearly lower than the observed one. The use of MCBC estimates, suggesting a strong interaction between sites, improved this discrepancy.     

Modelling forest dynamics: a perspective from point process methods

This paper reviews the main applications of (marked) point process theory in forestry including functions to analyse spatial variability and the main (marked) point process models. Although correlation functions do describe spatial variability at distinct range of scale, they are clearly restricted to the analysis of few dominant species since they are based on pairwise analysis. This has over-simplified the spatial analysis of complex forest dynamics involving "large" number of species. Moreover, although process models can reproduce, to some extent, real forest spatial patterns of trees, the biological forest-ecological interpretation of the resulting spatial structures is difficult since these models usually lack of biological realism. This problem gains in strength as usually most of these point process models are defined in terms of purely spatial relationships, though in real life, forest develop through time. We thus aim to discuss the applicability of such formulations to analyse and simulate "real" forest dynamics and unwrap their shortcomes. We present a unified approach of modern spatially explicit forest growth models. Finally, we focus on a continuous space-time stochastic process as an alternative approach to generate marked point patterns evolving through space and time.     

The Effects of Seed Dispersal on the Simulation of Long-Term Forest Landscape Change

The study of forest landscape change requires an understanding of the complex interactions of both spatial and temporal factors. Traditionally, forest gap models have been used to simulate change on small and independent plots. While gap models are useful in examining forest ecological dynamics across temporal scales, large, spatial processes, such as seed dispersal, cannot be realistically simulated across large landscapes. To simulate seed dispersal, spatially explicit landscape models that track individual species distribution are needed. We used such a model, LANDIS, to illustrate the implications of seed dispersal for simulating forest landscape change. On an artificial open landscape with a uniform environment, circular-shaped tree species establishment patterns resulted from the simulations, with areas near seed sources more densely covered than areas further from seed sources. Because LANDIS simulates at 10-y time steps, this pattern reflects an integration of various possible dispersal shapes and establishment that are caused by the annual variations in climate and other environmental variables. On real landscapes, these patterns driven only by species dispersal radii are obscured by other factors, such as species competition, disturbance, and landscape structure. To further demonstrate the effects of seed dispersal, we chose a fairly disturbed and fragmented forest landscape (approximately 500,000 ha) in northern Wisconsin. We compared the simulation results of a map with tree species (seed source locations) realistically parameterized (the real scenario) against a randomly parameterized species map (the random scenario). Differences in the initial seed source distribution lead to different simulation results of species abundance with species abundance starting at identical levels under the two scenarios. This is particularly true for the first half of the model run (0–250 y). Under the random scenario, infrequently occurring and shade tolerant species tend to be overestimated, while midabundant and midshade tolerant species tend to be underestimated. The over- and underestimation of species abundance diminish when examining long-term (500 y) landscape dynamics, because stochastic factors, such as fire, tend to make the landscapes under both scenarios converge. However, differences in spatial patterns, and especially species age-cohort distributions, can persist under the two scenarios for several hundred years. Received 24 November 1998; accepted 17 March 1999.     

Extinction threshold for spatial forest dynamics with height structure

We present a pair-approximation model for spatial forest dynamics defined on a regular lattice. The model assumes three possible states for a lattice site: empty (gap site), occupied by an immature tree, and occupied by a mature tree, and considers three nonlinearities in the dynamics associated to the processes of light interference, gap expansion, and recruitment. We obtain an expression of the basic reproduction number R₀ which, in contrast to the one obtained under the mean-field approach, uses information about the spatial arrangement of individuals close to extinction. Moreover, we analyze the corresponding survival-extinction transition of the forest and the spatial correlations among gaps, immature and mature trees close to this critical point. Predictions of the pair-approximation model are compared with those of a cellular automaton.     

Spatial scale and sampling resolution affect measures of gap disturbance in a lowland tropical forest: implications for understanding forest regeneration and carbon storage

Treefall gaps play an important role in tropical forest dynamics and in determining above-ground biomass (AGB). However, our understanding of gap disturbance regimes is largely based either on surveys of forest plots that are small relative to spatial variation in gap disturbance, or on satellite imagery, which cannot accurately detect small gaps. We used high-resolution light detection and ranging data from a 1500 ha forest in Panama to: (i) determine how gap disturbance parameters are influenced by study area size, and the criteria used to define gaps; and (ii) to evaluate how accurately previous ground-based canopy height sampling can determine the size and location of gaps. We found that plot-scale disturbance parameters frequently differed significantly from those measured at the landscape-level, and that canopy height thresholds used to define gaps strongly influenced the gap-size distribution, an important metric influencing AGB. Furthermore, simulated ground surveys of canopy height frequently misrepresented the true location of gaps, which may affect conclusions about how relatively small canopy gaps affect successional processes and contribute to the maintenance of diversity. Across site comparisons need to consider how gap definition, scale and spatial resolution affect characterizations of gap disturbance, and its inferred importance for carbon storage and community composition.     

Simulating forest ecosystem response to climate warming incorporating spatial effects in north-eastern China

Aim Predictions of ecosystem responses to climate warming are often made using gap models, which are among the most effective tools for assessing the effects of climate change on forest composition and structure. Gap models do not generally account for broad‐scale effects such as the spatial configuration of the simulated forest ecosystems, disturbance, and seed dispersal, which extend beyond the simulation plots and are important under changing climates. In this study we incorporate the broad‐scale spatial effects (spatial configurations of the simulated forest ecosystems, seed dispersal and fire disturbance) in simulating forest responses to climate warming. We chose the Changbai Natural Reserve in China as our study area. Our aim is to reveal the spatial effects in simulating forest responses to climate warming and make new predictions by incorporating these effects in the Changbai Natural Reserve. Location Changbai Natural Reserve, north‐eastern China. Method We used a coupled modelling approach that links a gap model with a spatially explicit landscape model. In our approach, the responses (establishment) of individual species to climate warming are simulated using a gap model (linkages ) that has been utilized previously for making predictions in this region; and the spatial effects are simulated using a landscape model (LANDIS) that incorporates spatial configurations of the simulated forest ecosystems, seed dispersal and fire disturbance. We used the recent predictions of the Canadian Global Coupled Model (CGCM2) for the Changbai Mountain area (4.6 °C average annual temperature increase and little precipitation change). For the area encompassed by the simulation, we examined four major ecosystems distributed continuously from low to high elevations along the northern slope: hardwood forest, mixed Korean pine hardwood forest, spruce‐fir forest, and sub‐alpine forest. Results The dominant effects of climate warming were evident on forest ecosystems in the low and high elevation areas, but not in the mid‐elevation areas. This suggests that the forest ecosystems near the southern and northern ranges of their distributions will have the strongest response to climate warming. In the mid‐elevation areas, environmental controls exerted the dominant influence on the dynamics of these forests (e.g. spruce‐fir) and their resilience to climate warming was suggested by the fact that the fluctuations of species trajectories for these forests under the warming scenario paralleled those under the current climate scenario. Main conclusions With the spatial effects incorporated, the disappearance of tree species in this region due to the climate warming would not be expected within the 300‐year period covered by the simulation. Neither Korean pine nor spruce‐fir was completely replaced by broadleaf species during the simulation period. Even for the sub‐alpine forest, mountain birch did not become extinct under the climate warming scenario, although its occurrence was greatly reduced. However, the decreasing trends characterizing Korean pine, spruce, and fir indicate that in simulations beyond 300 years these species could eventually be replaced by broadleaf tree species. A complete forest transition would take much longer than the time periods predicted by the gap models.     

Cluster analysis of spatial patterns in Malaysian tree species

Tree species in tropical rain forests exhibit a rich panoply of spatial patterns that beg ecological explanation. The analysis of tropical census data typically relies on spatial statistics, which quantify the average aggregation tendency of a species. In this article we develop a cluster-based approach that complements traditional spatial statistics in the exploration and analysis of ecological hypotheses for spatial pattern. We apply this technique to six study species within a fully mapped 50-ha forest census in peninsular Malaysia. For each species we identify the scale(s) of spatial aggregation and the corresponding tree clusters. We study the correlation between cluster locations and abiotic variables such as topography. We find that the distribution of cluster sizes exhibits equilibrium and nonequilibrium behavior depending on species life history. The distribution of tree diameters within clusters also varies according to species life history. At different spatial scales, we find evidence for both niche-based and dispersal-limited processes producing spatial pattern. Our methodology for identifying scales of aggregation and clusters is general; we discuss the method's applicability to spatial problems outside of tropical plant ecology.     

西双版纳热带雨林林窗空间分布格局及其特征数与林窗下植物多样性的相关性

林窗作为森林群落中一种重要的干扰方式, 对林下物种构成有着重要的影响。开展林窗空间格局及其特征指数与林下植物多样性关系研究对于探讨林窗对林下生物多样性的影响有重要意义, 有助于进一步了解群落动态, 在物种多样性保护方面也具有指导作用。本研究在西双版纳热带雨林地区随机选取3块大小为1 ha的热带雨林为研究样地, 采用轻小型六旋翼无人机搭载Sony ILCE-A7r可见光传感器, 分别获取各个样地的高清数字影像, 结合数字表面高程模型以及各个样地的地形数据用以确定各样区的林窗分布格局, 并进一步提取出各林窗的景观格局指数。结合地面样方基础调查数据, 对各样地各林窗下植物多样性情况进行统计, 旨在分析热带雨林林窗空间分布格局以及林窗下植物多样性对各林窗空间格局特征的响应情况。研究表明, 西双版纳州热带雨林林窗呈大而分散的空间分布, 林窗空间格局特征指数如林窗形状复杂性指数、林窗面积都与林下植物多样性呈显著正相关关系。在面积小的林窗下, 较之林窗形状复杂性因子, 林窗面积大小对林下植物多样性影响更显著; 在面积达到一定程度后, 相对于面积因子, 林窗形状复杂性指数对林下植物多样性影响更显著, 各样地林窗皆趋于向各自所处样地顶极群落发展。     

Modeling landscape patterns of understory tree regeneration in the Pacific Northwest,USA

Abstract. Vegetation maps serve as the basis for spatial analysis of forest ecosystems and provide initial information for simulations of forest landscape change. Because of the limitations of current remote sensing technology, it is not possible to directly measure forest understory attributes across large spatial extents. Instead we used a predictive vegetation mapping approach to model Tsuga heterophylla and Picea sitchensis seedling patterns in a 3900‐ha landscape in the Oregon Coast Range, USA, as a function of Landsat TM imagery, aerial photographs, digital elevation models, and stream maps. Because the models explained only moderate amounts of variability (R² values of 0.24–0.56), we interpreted the predicted patterns as qualitative spatial trends rather than precise maps. P. sitchensis seedling patterns were tightly linked to the riparian network, with highest densities in coastal riparian areas. T. heterophylla seedlings exhibited complex patterns related to topography and overstory forest cover, and were also spatially clustered around patches of old‐growth forest. We hypothesize that the old growth served as refugia for this fire‐sensitive species following wildfires in the late 19th and early 20th centuries. Low levels of T. heterophylla regeneration in hardwood‐dominated forests suggest that these patches may succeed to shrublands rather than to conifer forest. Predictive models of seedling patterns could be developed for other landscapes where georeferenced inventory plots, remote sensing data, digital elevation models, and climate maps are available.     

Integrating terrestrial laser scanning with functional–structural plant models to investigate ecological and evolutionary processes of forest communities

BackgroundWoody plants (trees and shrubs) play an important role in terrestrial ecosystems, but their size and longevity make them difficult subjects for traditional experiments. In the last 20 years functional–structural plant models (FSPMs) have evolved: they consider the interplay between plant modular structure, the immediate environment and internal functioning. However, computational constraints and data deficiency have long been limiting factors in a broader application of FSPMs, particularly at the scale of forest communities. Recently, terrestrial laser scanning (TLS), has emerged as an invaluable tool for capturing the 3-D structure of forest communities, thus opening up exciting opportunities to explore and predict forest dynamics with FSPMs.ScopeThe potential synergies between TLS-derived data and FSPMs have yet to be fully explored. Here, we summarize recent developments in FSPM and TLS research, with a specific focus on woody plants. We then evaluate the emerging opportunities for applying FSPMs in an ecological and evolutionary context, in light of TLS-derived data, with particular consideration of the challenges posed by scaling up from individual trees to whole forests. Finally, we propose guidelines for incorporating TLS data into the FSPM workflow to encourage overlap of practice amongst researchers.ConclusionsWe conclude that TLS is a feasible tool to help shift FSPMs from an individual-level modelling technique to a community-level one. The ability to scan multiple trees, of multiple species, in a short amount of time, is paramount to gathering the detailed structural information required for parameterizing FSPMs for forest communities. Conventional techniques, such as repeated manual forest surveys, have their limitations in explaining the driving mechanisms behind observed patterns in 3-D forest structure and dynamics. Therefore, other techniques are valuable to explore how forests might respond to environmental change. A robust synthesis between TLS and FSPMs provides the opportunity to virtually explore the spatial and temporal dynamics of forest communities.     

Historical climate modelling predicts patterns of current biodiversity in the Brazilian Atlantic forest

Aim We aim to propose validated, spatially explicit hypotheses for the late Quaternary distribution of the Brazilian Atlantic forest, and thereby provide a framework for integrating analyses of species and genetic diversity in the region. Location The Atlantic forest, stretching along the Brazilian coast. Methods We model the spatial range of the forest under three climatic scenarios (current climate, 6000 and 21,000 years ago) with BIOCLIM and MAXENT. Historically stable areas or refugia are identified as the set of grid cells for which forest presence is inferred in all models and time projections. To validate inferred refugia, we test whether our models are matched by the current distribution of the forest and by fossil pollen data. We then investigate whether the location of inferred forest refugia is consistent with current patterns of species endemism and existing phylogeographical data. Results Forest models agree with pollen records and predict a large area of historical forest stability in the central corridor (Bahia), as well as a smaller refuge (Pernambuco) along the Brazilian coast, matching current centres of endemism in multiple taxa and mtDNA diversity patterns in a subset of the species examined. Less historical stability is predicted in coastal areas south of the Doce river, which agrees with most phylogeographical studies in that region. Yet some widely distributed taxa show high endemism in the southern Atlantic forest. This may be due to limitations of the modelling approach, differences in ecology and dispersal capability, historical processes not contemplated by the current study or inadequacy of the available test data sets. Main conclusions Palaeoclimatic models predict the presence of historical forest refugia in the Atlantic rain forest and suggest spatial variation in persistence of forests through the Pleistocene, predicting patterns of biodiversity in several local taxa. The results point to the need for further studies to document genetic and species endemism in the relatively poorly known and highly impacted areas of Atlantic rain forests of north‐eastern Brazil.     

Ecological memory at millennial time-scales: the importance of data constraints,species longevity and niche features

Ecological memory describes how antecedent conditions drive the dynamics of an ecological system. Palaeoecological records are paramount to understand ecological memory at millennial time-scales, but the concept is widely neglected in the literature, and a formal approach is lacking. Here, we fill such a gap by introducing a quantitative framework for ecological memory in palaeoecology, and assessing how data constraints and taxa traits shape ecological memory patterns. We simulate the population dynamics and pollen abundance of 16 virtual taxa with different life and niche traits as a response to an environmental driver. The data is processed to mimic a realistic sediment deposition and sampled at increasing depth intervals. We quantify ecological memory with Random Forests, and assess how data properties and taxa traits shape ecological memory. We find that life-span and niche features modulate the relative importance of the antecedent values of the driver and the pollen abundance over periods of 240 yr and longer. Additionally, we find that accumulation rate and decreasing pollen-sampling resolution inflate the importance of antecedent pollen abundance. Our results suggest that: 1) ecological memory patterns are sensitive to varying accumulation rates. A better understanding on the numerical basis of this effect may enable the assimilation of ecological memory concepts and methods in palaeoecology; 2) incorporating niche theory and models is essential to better understand the nature of ecological memory patterns at millennial time-scales. 3) Long-lived generalist taxa are highly decoupled from the environmental signal. This finding has implications on how we interpret the abundance-environment relationship of real taxa with similar traits, and how we use such knowledge to forecast their distribution or reconstruct past climate.     

Modelling Direct Radiation and Canopy Gap Regimes in Tropical Forests

Spatial and temporal variation in the below‐canopy light environment of tropical forests is not well known and its measurement is technically challenging. Distributions of gap and understory areas in forests are likewise little known because of the resource requirements of forest structural censuses and a lack of consensus over how gaps should be defined. A basic model of forest structure, based on tree allometries from the 50 ha Forest Dynamics Plot on Barro Colorado Island (BCI), Panama, and a solar positioning algorithm were used to predict spatial and temporal variation in the distribution of direct light at the forest floor. Predicted duration of direct sunlight was then compared with the distribution of gap and understory areas, delimited according to four standard gap definitions, giving predictions for the correspondence between direct light regimes and forest structure. At least 36 percent of the areas of gaps of all sizes was predicted to receive < 1 h of direct sunlight per day, and the understory to receive direct sunlight for ≥ 1 h per day in up to 15 percent of its area, even when not in proximity to gaps. The predicted distribution of light changed over the course of the year with the greatest spread of light throughout the forest floor coinciding with the months when maximum daily solar elevation peaked. These predictions suggest a partial decoupling of light regimes from canopy structure, with implications for gap definitions, patch models of forest development and current understanding of tree seedling recruitment patterns.     

Variations in resistance to canopy disturbances and their interactions with the spatial structure of major species in a cool‐temperate forest

Question: How does typhoon‐related disturbance (more specifically, disturbance in the understorey due to tree‐fall and branch‐fall) affect different species mortality rates in a vertically well‐structured forest community? Location: Cool‐temperate, old‐growth forest in the Daisen Forest Reserve, Japan. Methods: We investigated the canopy dynamics and mortality rate trends of trees ≥5 cm diameter at breast height in a 4‐ha study plot, and analysed the effects of tree diameter and spatial structure on the mortality risks for major tree species in the understorey. Results: Significant differences were found in the mortality rates and proportions of injured dead stems between census periods, which were more pronounced in the understorey than in the canopy. Acer micranthum, which showed increased mortality during typhoon disturbance periods, had a clumped distribution. In contrast, Acer japonicum and Viburnum furcatum, which showed similar mortality rates between census periods, had a loosely clumped spatial distribution and a negative association with canopy trees, respectively. In the understorey stems of Acanthopanax sciadophylloides and Fagus crenata, whose spatial distribution patterns depended on canopy gaps, significant increases in mortality rates were observed only during severe typhoon‐related disturbance periods. Conclusions: The sensitivity of trees to typhoon‐related canopy disturbance is more pronounced in the lower layers of vertically structured forest communities. Differences in mortality patterns generated through the combined effects of spatial variation in disturbance regime and species‐specific spatial distribution patterns (spatial aggregation, association with canopy trees, and canopy gap dependency) contribute to the co‐existence of understorey species in forest communities that are subject to typhoon‐related disturbance.     

Dispersal evolution in temporally variable environments: implications for plant range dynamics

Dispersal—the movement of an individual from the site of birth to a different site for reproduction—is an ecological and evolutionary driver of species ranges that shapes patterns of colonization, connectivity, gene flow, and adaptation. In plants, the traits that influence dispersal often vary within and among species, are heritable, and evolve in response to the fitness consequences of moving through heterogeneous landscapes. Spatial and temporal variation in the quality and quantity of habitat are important sources of selection on dispersal strategies across species ranges. While recent reviews have evaluated the interactions between spatial variation in habitat and dispersal dynamics, the extent to which geographic variation in temporal variability can also shape range-wide patterns in dispersal traits has not been synthesized. In this paper, we summarize key predictions from metapopulation models that evaluate how dispersal evolves in response to spatial and temporal habitat variability. Next, we compile empirical data that quantify temporal variability in plant demography and patterns of dispersal trait variation across species ranges to evaluate the hypothesis that higher temporal variability favors increased dispersal at plant range limits. We found some suggestive evidence supporting this hypothesis while more generally identifying a major gap in empirical work evaluating plant metapopulation dynamics across species ranges and geographic variation in dispersal traits. To address this gap, we propose several future research directions that would advance our understanding of the interplay between spatiotemporal variability and dispersal trait variation in shaping the dynamics of current and future species ranges.     

Detecting successional changes in tropical forest structure using GatorEye drone-borne lidar

Drone-based remote sensing is a promising new technology that combines the benefits of ground-based and satellite-derived forest monitoring by collecting fine-scale data over relatively large areas in a cost-effective manner. Here, we explore the potential of the GatorEye drone-lidar system to monitor tropical forest succession by canopy structural attributes including canopy height, spatial heterogeneity, gap fraction, leaf area density (LAD) vertical distribution, canopy Shannon index (an index of LAD), leaf area index (LAI), and understory LAI. We focus on these variables’ relationship to aboveground biomass (AGB) stocks and species diversity. In the Caribbean lowlands of northeastern Costa Rica, we analyze nine tropical forests stands (seven second-growth and two old-growth). Stands were relatively homogenous in terms of canopy height and spatial heterogeneity, but not in their gap fraction. Neither species density nor tree community Shannon diversity index was significantly correlated with the canopy Shannon index. Canopy height, LAI, and AGB did not show a clear pattern as a function of forest age. However, gap fraction and spatial heterogeneity increased with forest age, whereas understory LAI decreased with forest age. Canopy height was strongly correlated with AGB. The heterogeneous mosaic created by successional forest patches across human-managed tropical landscapes can now be better characterized. Drone-lidar systems offer the opportunity to improve assessment of forest recovery and develop general mechanistic carbon sequestration models that can be rapidly deployed to specific sites, an essential step for monitoring progress within the UN Decade on Ecosystem Restoration.     

Scale and resolution of forest structural pattern

An individual tree-based forest succession model was modified to simulate a forest stand as a grid of contiguous 0.01-ha cells. We simulated a 9 ha stand for 750 years and sampled the stand at 50 yr intervals, outputting structural variables for each grid cell. Principal components analysis was used to depict temporal patterns in forest structure as observed in 0.01 ha samples (individual grid cells). We then resampled the grid using square aggregates of 4 to 100 grid cells as quadrats. Principal component scores recalculated for the aggregates, using the original (0.01 ha scale) scoring matrix, depict the effects of obervational scale on perceived patterns in forest structure. Larger quadrats reduce the apparent variation in forest structure and decrease the apparent rate of structural dynamics. Results support a scale-dependent conceptualization of forest systems by illustrating the qualitative difference in forest dynamics as viewed at the scale of individual gap elements as compared to the larger scale steady state mosaic. The aggregation exercise emphasizes the relationship between these two observational scales and serves as a general framework for understanding scaling relationships in ecological phenomena.