Bibliography - J W. Lichstein

1. Lichstein, J W., and Stephen W. Pacala, 2011: Local diversity in heterogeneous landscapes: quantitative assessment with a height-structured forest metacommunity model. Theoretical Ecology, Springer, 4, doi:10.1007/s12080-011-0121-5 269-281
   [ Abstract ]

   "Mass effects," in which "sink populations" of locally inferior competitors are maintained by dispersal from "source populations" elsewhere in the landscape, are thought to play an important role in maintaining plant diversity. However, due to the complexity of most quasirealistic forest models, there is little theoretical understanding of the strength of mass effects in forests. Here, we develop a metacommunity version of a mathematically and computationally tractable height-structured forest model, the Perfect Plasticity Approximation, to quantify the strength of mass effects (i.e., the degree of mixing of locally dominant and subordinate species) in heterogeneous landscapes comprising different patch types (e.g., soil types). For realistic levels of inter-patch dispersal, mass effects are weak at equilibrium (i.e., in the absence of disturbance), even in some cases where differences in growth, mortality, and fecundity rates between locally dominant and subordinate species are too small to be reliably detected from field data. However, patch-scale transient dynamics are slow following catastrophic disturbance (in which post-disturbance initial abundances are determined exclusively by immigration) so that at any given time, subordinate species are present in appreciable numbers in most patches. Less severe disturbance regimes, in which some seeds or individuals survive the disturbance, should result in faster transient dynamics (i.e., faster approach to the low-diversity equilibrium). Our results suggest that in order for mass effects to play an important role in tree coexistence, niche differences must be strong enough to prevent neutral drift, yet too weak to be reliably detected from field data.

2. Lichstein, J W., J. Dushoff, Kiona Ogle, Anping Chen, D. W. Purves, J. P. Caspersen, and Stephen W. Pacala, 2010: Unlocking the forest inventory data: relating individual tree performance to unmeasured environmental factors. Ecological Applications, (20(3)), doi:10.1890/08-2334.1 684-699
   [ Abstract ]

   Geographically extensive forest inventories, such as the USDA Forest Service's Forest Inventory and Analysis (FIA) program, contain millions of individual tree growth and mortality records that could be used to develop broad-scale models of forest dynamics. A limitation of inventory data, however, is that individual-level measurements of light (L) and other environmental factors are typically absent. Thus, inventory data alone cannot be used to parameterize mechanistic models of forest dynamics in which individual performance depends on light, water, nutrients, etc. To overcome this limitation, we developed methods to estimate species-specific parameters (θ_G) relating sapling growth (G) to L using data sets in which G, but not L, is observed for each sapling. Our approach involves: (1) using calibration data that we collected in both eastern and western North America to quantify the probability that saplings receive different amounts of light, conditional on covariates x that can be obtained from inventory data (e.g., sapling crown class and neighborhood crowding); and (2) combining these probability distributions with observed G and x to estimate θ_G using Bayesian computational methods. Here, we present a test case using a data set in which G, L, and x were observed for saplings of nine species. This test data set allowed us to compare estimates of θ_G obtained from the standard approach (where G and L are observed for each sapling) to our method (where G and x, but not L, are observed). For all species, estimates of θ_G obtained from analyses with and without observed L were similar. This suggests that our approach should be useful for estimating light-dependent growth functions from inventory data that lack direct measurements of L. Our approach could be extended to estimate parameters relating sapling mortality to L from inventory data, as well as to deal with uncertainty in other resources (e.g., water or nutrients) or environmental factors (e.g., temperature).

3. Lichstein, J W., C. Wirth, H. S. Horn, and Stephen W. Pacala, 2009: Biomass Chronosequences of United States Forests: Implications for Carbon Storage and Forest Management. Old-growth forests, 207, doi:10.1007/978-3-540-92706-8_14 301-341
   [ Abstract ]

   A variety of mechanisms have been identified that may result in late-successional declines in forest biomass, including synchronous mortality of even-aged early-successional cohorts, increased susceptibility of mature forests to wind or insect damage, and, in some systems, reduced stature of late-successional species. We used data from the United States (US) Forest Service’s Forest Inventory and Analysis (FIA) program, and a literature database on old-growth biomass, to quantify late-successional biomass trajectories in different US forest types. Our results suggest that late-successional biomass declines are rare in US forests. Thus, in most cases, there is no conflict between maximizing carbon storage in forest biomass and protecting or restoring old-growth forests.

4. Purves, D. W., J W. Lichstein, N. Strigul, and Stephen W. Pacala, August 2008: Predicting and understanding forest dynamics using a simple tractable model. Proceedings of the National Academy of Sciences of the United States of America, www.pnas.org cgi doi 10.1073 pnas.0807754105, 105(44), 17018-17022,
   [ Abstract ]

   The perfect-plasticity approximation (PPA) is an analytically tractable model of forest dynamics, defined in terms of parameters for individual trees, including allometry, growth, and mortality. We estimated these parameters for the eight most common species on each of four soil types in the US Lake states (Michigan, Wisconsin, and Minnesota) by using short-term (<15-year) inventory data from individual trees. We implemented 100-year PPA simulations given these parameters and compared these predictions to chronosequences of stand development. Predictions for the timing and magnitude of basal area dynamics and ecological succession on each soil were accurate, and predictions for the diameter distribution of 100-year-old stands were correct in form and slope. For a given species, the PPA provides analytical metrics for early-successional performance (H₂₀, height of a 20-year-old open-grown tree) and late-successional performance (Z^*, equilibrium canopy height in monoculture). These metrics predicted which species were early or late successional on each soil type. Decomposing Z^*, showed that (i) succession is driven both by superior understory performance and superior canopy performance of late-successional species, and (ii) performance differences primarily reflect differences in mortality rather than growth. The predicted late-successional dominants matched chronosequences on xeromesic (Quercus rubra) and mesic (codominance by Acer rubrum and Acer saccharum) soil. On hydromesic and hydric soils, the literature reports that the current dominant species in old stands (Thuja occidentalis) is now failing to regenerate. Consistent with this, the PPA predicted that, on these soils, stands are now succeeding to dominance by other latesuccessional species (e.g., Fraxinus nigra, A. rubrum).

5. Lichstein, J W., J. Dushoff, S. A. Levin, and Stephen W. Pacala, 2007: Intraspecific variation and species coexistence. American Naturalist, 170(6), doi:10.1086/522937 807-818
   [ Abstract ]

   We use a two-species model of plant competition to explore the effect of intraspecific variation on community dynamics. The competitive ability (“performance”) of each individual is assigned by an independent random draw from a species-specific probability distribution. If the density of individuals competing for open space is high (e.g., because fecundity is high), species with high maximum (or large variance in) performance are favored, while if density is low, species with high typical (e.g., mean) performance are favored. If there is an interspecific mean-variance performance trade-off, stable coexistence can occur across a limited range of intermediate densities, but the stabilizing effect of this trade-off appears to be weak. In the absence of this trade-off, one species is superior. In this case, intraspecific variation can blur interspecific differences (i.e., shift the dynamics toward what would be expected in the neutral case), but the strength of this effect diminishes as competitor density increases. If density is sufficiently high, the inferior species is driven to extinction just as rapidly as in the case where there is no overlap in performance between species. Intraspecific variation can facilitate coexistence, but this may be relatively unimportant in maintaining diversity in most real communities.

6. Purves, D. W., J W. Lichstein, and Stephen W. Pacala, 2007: Crown Plasticity and Competition for Canopy Space: A New Spatially Implicit Model Parameterized for 250 North American Tree Species. PLOS one, (9), doi:10.1371/journal.pone.0000870
   [ Abstract ]

   Background. Canopy structure, which can be defined as the sum of the sizes, shapes and relative placements of the tree crowns in a forest stand, is central to all aspects of forest ecology. But there is no accepted method for deriving canopy structure from the sizes, species and biomechanical properties of the individual trees in a stand. Any such method must capture the fact that trees are highly plastic in their growth, forming tessellating crown shapes that fill all or most of the canopy space. Methodology/Principal Findings. We introduce a new, simple and rapidly-implemented model–the Ideal Tree Distribution, ITD–with tree form (height allometry and crown shape), growth plasticity, and space-filling, at its core. The ITD predicts the canopy status (in or out of canopy), crown depth, and total and exposed crown area of the trees in a stand, given their species, sizes and potential crown shapes. We use maximum likelihood methods, in conjunction with data from over 100,000 trees taken from forests across the coterminous US, to estimate ITD model parameters for 250 North American tree species. With only two free parameters per species–one aggregate parameter to describe crown shape, and one parameter to set the so-called depth bias–the model captures between-species patterns in average canopy status, crown radius, and crown depth, and within-species means of these metrics vs stem diameter. The model also predicts much of the variation in these metrics for a tree of a given species and size, resulting solely from deterministic responses to variation in stand structure. Conclusions/Significance. This new model, with parameters for US tree species, opens up new possibilities for understanding and modeling forest dynamics at local and regional scales, and may provide a new way to interpret remote sensing data of forest canopies, including LIDAR and aerial photography.

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