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Tree mortality is a key driver of forest dynamics and its occurrence is projected to increase in the future due to climate change. Despite recent advances in our understanding of the physiological mechanisms leading to death, we still lack robust indicators of mortality risk that could be applied at the individual tree scale. Here, we build on a previous contribution exploring the differences in growth level between trees that died and survived a given mortality event to assess whether changes in temporal autocorrelation, variance, and synchrony in time-series of annual radial growth data can be used as early warning signals of mortality risk. Taking advantage of a unique global ring-width database of 3065 dead trees and 4389 living trees growing together at 198 sites (belonging to 36 gymnosperm and angiosperm species), we analyzed temporal changes in autocorrelation, variance, and synchrony before tree death (diachronic analysis), and also compared these metrics between trees that died and trees that survived a given mortality event (synchronic analysis). Changes in autocorrelation were a poor indicator of mortality risk. However, we found a gradual increase in inter-annual growth variability and a decrease in growth synchrony in the last ∼20 years before mortality of gymnosperms, irrespective of the cause of mortality. These changes could be associated with drought-induced alterations in carbon economy and allocation patterns. In angiosperms, we did not find any consistent changes in any metric. Such lack of any signal might be explained by the relatively high capacity of angiosperms to recover after a stress-induced growth decline. Our analysis provides a robust method for estimating early-warning signals of tree mortality based on annual growth data. In addition to the frequently reported decrease in growth rates, an increase in inter-annual growth variability and a decrease in growth synchrony may be powerful predictors of gymnosperm mortality risk, but not necessarily so for angiosperms.

High biodiversity of forests is not predicted by traditional models, and evidence for trade-offs those models require is limited. High-dimensional regulation (e.g., N factors to regulate N species) has long been recognized as a possible alternative explanation, but it has not be been seriously pursued, because only a few limiting resources are evident for trees, and analysis of multiple interactions is challenging. We develop a hierarchical model that allows us to synthesize data from long-term, experimental, data sets with processes that control growth, maturation, fecundity, and survival. We allow for uncertainty at all stages and variation among 26 000 individuals and over time, including 268 000 tree years, for dozens of tree species. We estimate population-level parameters that apply at the species level and the interactions among latent states, i.e., the demographic rates for each individual, every year. The former show that the traditional trade-offs used to explain diversity are not present. Demographic rates overlap among species, and they do not show trends consistent with maintenance of diversity by simple mechanisms (negative correlations and limiting similarity). However, estimates of latent states at the level of individuals and years demonstrate that species partition environmental variation. Correlations between responses to variation in time are high for individuals of the same species, but not for individuals of different species. We demonstrate that these relationships are pervasive, providing strong evidence that high-dimensional regulation is critical for biodiversity regulation.

1. Quercus macrocarpa (bur oak) is the dominant tree species along much of the prairie–forest border in the northern-central United States, and movement of Q. macrocarpa in response to climate change may determine the rate at which the prairie–forest ecotone shifts. To investigate likely controls over Q. macrocarpa performance at the edge of its range, we used tree rings to establish the links between drought, growth-rate and mortality for three sites spanning the prairie–forest border in Minnesota. 2. Quercus macrocarpa growth during the 20th century correlates strongly with the Palmer Drought Severity Index (PDSI) and more weakly with raw temperature and precipitation values for all three sites. However, the sensitivity of annual growth rates to drought has steadily declined over time as evidenced by increasing growth residuals and higher growth rates for a given PDSI value after 1950 compared with the first half of the century. We hypothesize that increased atmospheric carbon dioxide concentration may lead to increased water-use efficiency, although we cannot rule out other environmental factors. 3. Because growth is an excellent predictor of Q. macrocarpa mortality, growth–climate relationships provide information on whether oak forests will contract, because of individual tree death, when climate changes. For Q. macrocarpa, declining sensitivity of growth to drought translates into lower predicted mortality rates at all sites. At one site, declining moisture sensitivity yields a 49% lower predicted mortality from a severe drought (PDSI = −8, on par with the worst 1930s 'American Dust Bowl' droughts in our study region). 4. Unless the changing relationship between growth and climate is incorporated into forest simulation models, the predicted rate of established tree dieback in a warmer, drier climate may be exaggerated. 5. Synthesis. Adult Quercus macrocarpa trees appear to be increasingly insensitive to drought-induced mortality. Because the species is dominant at the prairie–forest ecotone in the northern-central United States, movement of the ecotone in response to climate change may be delayed for decades.

1 Slow growth is associated with high mortality risk for trees, but few data exist to assess interspecific differences in the relationship between growth and mortality. Here we compare low growth tolerance for seven co-occurring species in the southern Appalachian Mountains: Acer rubrum, Betula lenta, Cornus florida, Liriodendron tulipifera, Quercus prinus, Quercus rubra and Robinia pseudo-acacia. 2 For all species, mortality was greater for understorey individuals than for canopy trees. Species varied widely in the length of growth decline prior to death, ranging from 6 years for L. tulipifera to more than 12 years for Q. rubra. 3 Growth-mortality functions differ among species, but we found little evidence of a trade-off between tolerance of slow growth and an ability to show rapid growth in high light conditions. 4 A. rubrum stands out in its ability both to grow rapidly and to tolerate slow growth, suggesting that its density may increase at our study site as in other parts of the eastern United States. In contrast, C. florida shows high mortality (15% per annum) as a result of infection with dogwood anthracnose. 5 We modified a forest simulation model, LINKAGES (which assumes that all species have the same ability to tolerate slow growth), to include our functions relating growth and mortality. The modified model gives radically altered predictions, reinforcing the need to rethink and re-parameterize existing computer models with field data.

We address the relationships between tree growth rate and growing environment for 21 co-occurring species. Tree growth rates are obtained from mapped plots at the Coweeta Long-Term Ecological Research site in the southern Appalachian Mountains. We employ high-resolution aerial photography to assess the light environment for trees growing in these plots, using exposed crown area (ECA) as a surrogate for light interception. The relationship between growth and ECA is compared with two other growth predictors: tree size and shade-tolerance classification. We find that ECA is an excellent predictor of tree growth (average R 2  = 0.69 for nine species). When ECA is combined with tree size, growth rate prediction is improved (average R 2  = 0.76). Tree size alone is also a strong predictor of tree growth (average R 2  = 0.68). Shade-tolerance classification, by contrast, is a poor predictor of tree growth.

Gap models are perhaps the most widely used class of individual-based tree models used in ecology and climate change research. However, most gap model emphasize, in terms of process detail, computer code, and validation effort, tree growth with little attention to thesimulation of plant death or mortality.

Quercus macrocarpa Michx. (bur oak) is the key pioneer species as forests establish at the prairie-forest ecotone in western Minnesota, but invasive Rhamnus cathartica L. (European buckthorn) is an abundant and increasing secondary tree. Here we contrast microsite utilization and growth as a function of light and soil moisture for Q. macrocarpa and R. cathartica saplings at an ecotonal forest in an effort to establish the roles these two species are likely to play in near-term forest dynamics. Compared to Q. macrocarpa, R cathartica saplings are found, on average, in darker microsites (P < 0.001) with higher soil moisture (P < 0.001), though the range of light levels at which saplings were seen to occur is much larger for Q. macrocarpa than for R. cathartica. We fit a variety of models which predict sapling growth and compared fits using AICc. With our best fitting models, light, size, and soil moisture together explain approximately half of the variation in growth among R. cathartica saplings and two-thirds of the variation in Q. macrocarpa. Most similar studies utilize models that include an a priori assumption that growth will asymptote with increasing light availability, but we find no evidence to support the use of asymptotic models. All top ranked models include light and sapling size, but the calculated importance of both light and soil moisture is dependent on the choice of growth metric, a disturbing finding given the variety of metrics utilized in the sapling growth literature. For neither species does the addition of soil moisture significantly improve growth models if the growth metric used is absolute radial stem growth increment, but soil moisture becomes important when absolute basal area increment is the growth metric for Q. macrocarpa, and when relative growth increment is used for either species. Limited success of R. cathartica in light, dry microsites suggests that the invasive tree may be near its climatic limit at our ecotonal forest site. At the same time, the relative success of the species in the dark understory of our warm dry forest suggests that near-term warming, with an expected increase in continental-climate drought, is unlikely to limit R. cathartica across the bulk of forests it has invaded in North America.

Ecologists and foresters have long noted a link between tree growth rate and mortality, and recent work suggests that interspecific differences in low growth tolerance is a key force shaping forest structure. Little information is available, however, on the growth-mortality relationship for most species. We present three methods for estimating growth-mortality functions from readily obtainable field data. All use annual mortality rates and the recent growth rates of living and dead individuals. Annual mortality rates are estimated using both survival analysis and a Bayesian approach. Growth rates are obtained from increment cores. Growth-mortality functions are fitted using two parametric approaches and a nonparametric approach. The three methods are compared using bootstrapped confidence intervals and likelihood ratio tests. For two example species, Acer rubrum L. and Cornus florida L., growth-mortality functions indicate a substantial difference in the two species' abilities to withstand slow growth. Both survival analysis and Bayesian estimates of mortality rates lead to similar growth-mortality functions, with the Bayesian approach providing a means to overcome the absence of long-term census data. In fitting growth-mortality functions, the nonparametric approach reveals that inflexibility in parametric methods can lead to errors in estimating mortality risk at low growth. We thus suggest that nonparametric fits be used as a tool for assessing parametric models.

Wyckoff, P. H., R. Greiman, A. Krueger, and L. Luce. (Biology Discipline, University of Minnesota, Morris, MN 56267). Forest dynamics at Minnesota's prairie-forest border driven by invasive buckthorn (Rhamnus cathartica) and native bur oak (Quercus macrocarpa). J. Torrey Bot. Soc. 139: 311–322. 2012.—Quercus macrocarpa Michx. (bur oak) is the key pioneer species as forests establish at the prairie-forest ecotone in western Minnesota, but invasive Rhamnus cathartica L. (European buckthorn) is an abundant and increasing secondary tree. Here we contrast microsite utilization and growth as a function of light and soil moisture for Q. macrocarpa and R. cathartica saplings at an ecotonal forest in an effort to establish the roles these two species are likely to play in near-term forest dynamics. Compared to Q. macrocarpa, R. cathartica saplings are found, on average, in darker microsites (P < 0.001) with higher soil moisture (P < 0.001), though the range of light levels at which saplings were seen to occur is much larger for Q. macrocarpa than for R. cathartica. We fit a variety of models which predict sapling growth and compared fits using AICc. With our best fitting models, light, size, and soil moisture together explain approximately half of the variation in growth among R. cathartica saplings and two-thirds of the variation in Q. macrocarpa. Most similar studies utilize models that include an a priori assumption that growth will asymptote with increasing light availability, but we find no evidence to support the use of asymptotic models. All top ranked models include light and sapling size, but the calculated importance of both light and soil moisture is dependent on the choice of growth metric, a disturbing finding given the variety of metrics utilized in the sapling growth literature. For neither species does the addition of soil moisture significantly improve growth models if the growth metric used is absolute radial stem growth increment, but soil moisture becomes important when absolute basal area increment is the growth metric for Q. macrocarpa, and when relative growth increment is used for either species. Limited success of R. cathartica in light, dry microsites suggests that the invasive tree may be near its climatic limit at our ecotonal forest site. At the same time, the relative success of the species in the dark understory of our warm dry forest suggests that near-term warming, with an expected increase in continental-climate drought, is unlikely to limit R. cathartica across the bulk of forests it has invaded in North America.

1.Quercus macrocarpa (bur oak) is the dominant tree species along much of the prairie-forest border in the northern-central United States, and movement of Q. macrocarpa in response to climate change may determine the rate at which the prairie-forest ecotone shifts. To investigate likely controls over Q. macrocarpa performance at the edge of its range, we used tree rings to establish the links between drought, growth-rate and mortality for three sites spanning the prairie-forest border in Minnesota. 2.Quercus macrocarpa growth during the 20th century correlates strongly with the Palmer Drought Severity Index (PDSI) and more weakly with raw temperature and precipitation values for all three sites. However, the sensitivity of annual growth rates to drought has steadily declined over time as evidenced by increasing growth residuals and higher growth rates for a given PDSI value after 1950 compared with the first half of the century. We hypothesize that increased atmospheric carbon dioxide concentration may lead to increased water-use efficiency, although we cannot rule out other environmental factors. 3. Because growth is an excellent predictor of Q. macrocarpa mortality, growth-climate relationships provide information on whether oak forests will contract, because of individual tree death, when climate changes. For Q. macrocarpa, declining sensitivity of growth to drought translates into lower predicted mortality rates at all sites. At one site, declining moisture sensitivity yields a 49% lower predicted mortality from a severe drought (PDSI = -8, on par with the worst 1930s 'American Dust Bowl' droughts in our study region). 4. Unless the changing relationship between growth and climate is incorporated into forest simulation models, the predicted rate of established tree dieback in a warmer, drier climate may be exaggerated. 5.Synthesis. Adult Quercus macrocarpa trees appear to be increasingly insensitive to drought-induced mortality. Because the species is dominant at the prairie-forest ecotone in the northern-central United States, movement of the ecotone in response to climate change may be delayed for decades.