Predicting Douglas‐fir Sapling Mortality Following Prescribed Fire in an Encroached Grassland

Tree encroachment in fire‐maintained woodlands and grasslands is a major management concern, yet little information exists regarding the mechanisms of small tree mortality following prescribed burns. We sought to clarify the relative importance of tree size and fire‐induced injury in the post‐fire mortality of encroaching Douglas‐fir trees and to compare results with an existing mortality model for larger Douglas‐fir trees. Crown injury to small Douglas‐fir trees was a significant explanatory variable in post‐fire mortality models, with results suggesting a 20% threshold in crown scorch. Crown injury was strongly related to bole injury, and delayed mortality was important as we documented new mortality 20 months post‐burn. Mortality models for large Douglas‐fir tend to over‐predict small tree mortality, underscoring the need to better understand the mechanisms of fire‐caused mortality for small, encroaching trees.     

Deadly combination of genes and drought: increased mortality of herbivore-resistant trees in a foundation species

Current climate models predict a shift to warmer, drier conditions in the southwestern US. While major shifts in plant distribution are expected to follow these climate changes, interactions among species and intraspecific genetic variation rarely have been incorporated into models of future plant distributions. We examined the drought‐related mortality of pinyon pine (Pinus edulis) in northern Arizona focusing on trees that showed genetically‐based resistance or susceptibility to a nonlethal herbivore, the shoot‐boring moth, Dioryctria albovittella. Because moth resistant trees have outperformed susceptible trees during 20 years of study, and herbivory has been shown to increase drought related mortality, we expected higher mortality rates in susceptible trees. However, our field observations and greenhouse experiments showed several unexpected patterns relevant to understanding the consequences of climate change: (1) The mortality of adult P. edulis resistant to the moth was three times higher than the mortality of trees susceptible to the moth. (2) Over a few years, differential mortality caused a shift in stand structure from resistant dominated to equality (3 : 1 resistant : susceptible to 1 : 1). (3) Adult moth resistant trees suffered significantly greater water stress than adult moth susceptible trees, suggesting that variation among the two groups in drought tolerance may be a mechanism for differential mortality. (4) When grown under drought conditions in the greenhouse, seedlings from resistant mothers died sooner than seedlings from susceptible mothers. These data support the hypothesis that drought can act as an agent of balancing selection and that drought resistance is a heritable trait. Taken together, our findings suggest that genetic variation in a population can be an important factor in determining its response to future climate change, and argue for the inclusion of genetics into models developed to understand the consequences of climate change.     

A holistic approach to determine tree structural complexity based on laser scanning data and fractal analysis

The three‐dimensional forest structure affects many ecosystem functions and services provided by forests. As forests are made of trees it seems reasonable to approach their structure by investigating individual tree structure. Based on three‐dimensional point clouds from laser scanning, a newly developed holistic approach is presented that enables to calculate the box dimension as a measure of structural complexity of individual trees using fractal analysis. It was found that the box dimension of trees was significantly different among the tested species, among trees belonging to the same species but exposed to different growing conditions (at gap vs. forest interior) or to different kinds of competition (intraspecific vs. interspecific). Furthermore, it was shown that the box dimension is positively related to the trees’ growth rate. The box dimension was identified as an easy to calculate measure that integrates the effect of several external drivers of tree structure, such as competition strength and type, while simultaneously providing information on structure‐related properties, like tree growth.     

Allometric Models for Predicting Aboveground Biomass in Two Widespread Woody Plants in Hawaii

Allometric models are important for quantifying biomass and carbon storage in terrestrial ecosystems. Generalized allometry exists for tropical trees, but species‐ and site‐specific models are more accurate. We developed species‐specific models to predict aboveground biomass in two of the most ubiquitous natives in Hawaiian forests and shrublands, Metrosideros polymorpha and Dodonaea viscosa. The utility of the M. polymorpha allometry for predicting biomass across a range of sites was explored by comparing size structure (diameter at breast height vs. tree height) of the trees used to develop the models against trees from four M. polymorpha‐dominated forests along a precipitation gradient (1630–2380 mm). We also compared individual tree biomass estimated with the M. polymorpha model against existing generalized equations, and the D. viscosa model with an existing species‐specific model. Our models were highly significant and displayed minimal bias. Metrosideros polymorpha size structures from the three highest precipitation sites fell well within the 95% confidence intervals for the harvested trees, indicating that the models are applicable at these sites. However, size structure in the area with the lowest precipitation differed from those in the higher rainfall sites, emphasizing that care should be taken in applying the models too widely. Existing generalized allometry differed from the M. polymorpha model by up to 88 percent, particularly at the extremes of the data range examined, underestimating biomass in small trees and overestimating in large trees. The existing D. viscosa model underestimated biomass across all sizes by a mean of 43 percent compared to our model. The species‐specific models presented here should enable more accurate estimates of biomass and carbon sequestration in Hawaiian forests and shrublands.     

Empirical phylogenies and species abundance distributions are consistent with preequilibrium dynamics of neutral community models with gene flow

Community characteristics reflect past ecological and evolutionary dynamics. Here, we investigate whether it is possible to obtain realistically shaped modeled communities–that is with phylogenetic trees and species abundance distributions shaped similarly to typical empirical bird and mammal communities–from neutral community models. To test the effect of gene flow, we contrasted two spatially explicit individual‐based neutral models: one with protracted speciation, delayed by gene flow, and one with point mutation speciation, unaffected by gene flow. The former produced more realistic communities (shape of phylogenetic tree and species‐abundance distribution), consistent with gene flow being a key process in macro‐evolutionary dynamics. Earlier models struggled to capture the empirically observed branching tempo in phylogenetic trees, as measured by the gamma statistic. We show that the low gamma values typical of empirical trees can be obtained in models with protracted speciation, in preequilibrium communities developing from an initially abundant and widespread species. This was even more so in communities sampled incompletely, particularly if the unknown species are the youngest. Overall, our results demonstrate that the characteristics of empirical communities that we have studied can, to a large extent, be explained through a purely neutral model under preequilibrium conditions.     

USING PHYLOGENETIC TREES TO STUDY SPECIATION AND EXTINCTION

One tool in the study of the forces that determine species diversity is the null, or simple, model. The fit of predictions to observations, good or bad, leads to a useful paradigm or to knowledge of forces not accounted for, respectively. It is shown how simple models of speciation and extinction lead directly to predictions of the structure of phylogenetic trees. These predictions include both essential attributes of phylogenetic trees: lengths, in the form of internode distances; and topology, in the form of internode links. These models also lead directly to statistical tests which can be used to compare predictions with phylogenetic trees that are estimated from data. Two different models and eight data sets are considered. A model without species extinction consistently yielded predictions closer to observations than did a model that included extinction. It is proposed that it may be useful to think of the diversification of recently formed monophyletic groups as a random speciation process without extinction.     

Influence of Post‐Clearing Treatment on the Recovery of Herbaceous Plant Communities in Amazonian Secondary Forests

Secondary forests are an increasingly common feature in tropical landscapes worldwide and understanding their regeneration is necessary to design effective restoration strategies. It has previously been shown that the woody species community in secondary forests can follow different successional pathways according to the nature of past human activities in the area, yet little is known about patterns of herbaceous species diversity in secondary forests with different histories of land use. We compared the diversity and abundance of herbaceous plant communities in two types of Central Amazonian secondary forests—those regenerating on pastures created by felling and burning trees and those where trees were felled only. We also tested if plant density and species richness in secondary forests are related to proximity to primary forest. In comparison with primary forest sites, forests regenerating on non‐burned habitats had lower herbaceous plant density and species richness than those on burned ones. However, species composition and abundance in non‐burned stands were more similar to those of primary forest, whereas several secondary forest specialist species were found in burned stands. In both non‐burned and burned forests, distance from the forest edge was not related to herbaceous density and species richness. Overall, our results suggest that the natural regeneration of herbaceous species in secondary tropical forests is dependent on a site's post‐clearing treatment. We recommend evaluating the land history of a site prior to developing and implementing a restoration strategy, as this will influence the biological template on which restoration efforts are overlaid.     

Growth allocation between height and stem diameter in nonsuppressed reproducing Abies mariesii trees

To understand the growth patterns with respect to competition and leaf‐mass increase in reproducing trees, growth allocation between height and stem diameter was examined for nonsuppressed reproducing Abies mariesii trees in a subalpine forest in northern Honshu, Japan. The growth allocation was analyzed by dividing the relative growth rate of the stem volume into the relative contributions of height and stem‐diameter growth. During a 9‐yr period, height growth and seed‐cone production showed obvious annual variation, while stem‐diameter growth recorded moderate variation. For two of three years of seed‐cone production during the 9‐yr period, trees with larger seed‐cone production were associated with less height growth in the following year of seed‐cone production; however, there was no trend of height growth in the year of seed‐cone production. In the following year of mast seeding, trees with larger stem‐volume growth were associated with less height growth. This trend was also shown for the relationship between the cumulative stem‐volume growth during the 9‐yr period and growth allocation to height, suggesting that trees with a larger biomass increase depress the allocation of photosynthate to competition with a large expenditure for reproduction. In contrast to this, trees with a smaller biomass increase might allocate photosynthate to competition with surrounding trees. The results of this study suggest that an increase in reproductive organs during life history and annual variation in reproduction are closely associated with the growth patterns of the stem in A. mariesii trees.     

Tree–grass coexistence in savannas revisited – insights from an examination of assumptions and mechanisms invoked in existing models

Several explanations for the persistence of tree–grass mixtures in savannas have been advanced thus far. In general, these either concentrate on competition‐based mechanisms, where niche separation with respect to limiting resources such as water lead to tree–grass coexistence, or demographic mechanisms, where factors such as fire, herbivory and rainfall variability promote tree–grass persistence through their dissimilar effects on different life‐history stages of trees. Tests of these models have been largely site‐specific, and although different models find support in empirical data from some savanna sites, enough dissenting evidence exists from others to question their validity as general mechanisms of tree–grass coexistence. This lack of consensus on determinants of savanna structure and function arises because different models: (i) focus on different demographic stages of trees, (ii) focus on different limiting factors of tree establishment, and (iii) emphasize different subsets of the potential interactions between trees and grasses. Furthermore, models differ in terms of the most basic assumptions as to whether trees or grasses are the better competitors. We believe an integration of competition‐based and demographic approaches is required if a comprehensive model that explains both coexistence and the relative productivity of the tree and grass components across the diverse savannas of the world is to emerge. As a first step towards this end, we outline a conceptual framework that integrates existing approaches and applies them explicitly to different life‐history stage of trees.     

Individual-based modeling of the spread of pine wilt disease: vector beetle dispersal and the Allee effect

Pine wilt disease is caused by the pinewood nematode Bursaphelenchus xylophilus, which is vectored by the Japanese pine sawyer beetle Monochamus alternatus. Due to their mutualistic relationship, according to which the nematode weakens and makes trees available for beetle reproduction and the beetle in turn carries and transmits the nematode to healthy pine trees, this disease has resulted in severe damage to pine trees in Japan in recent decades. Previous studies have worked on modeling of population dynamics of the vector beetle and the pine tree to explore spatial expansion of the disease using an integro-difference equation with a dispersal kernel that describes beetle mobility over space. In this paper, I revisit these previous models but retaining individuality: by considering mechanistic interactions at the individual level it is shown that the Allee effect, an increasing per-capita growth rate as population abundance increases, can arise in the beetle dynamics because of the necessity for beetles to contact pine trees at least twice to reproduce successfully. The incubation period after which a tree contacted by a first beetle becomes ready for beetle oviposition by later beetles is crucial for the emergence of this Allee effect. It is also shown, however, that the strength of this Allee effect depends strongly on biological mechanistic properties, especially on beetle mobility. Realistic individual-based modeling highlights the importance of how spatial scales are dealt with in mathematical models. The link between mechanistic individual-based modeling and conventional analytical approaches is also discussed.     

Effect of detection heterogeneity in occupancy‐detection models: an experimental test of time‐to‐first‐detection methods

Imperfect detection can bias estimates of site occupancy in ecological surveys but can be corrected by estimating detection probability. Time‐to‐first‐detection (TTD) occupancy models have been proposed as a cost–effective survey method that allows detection probability to be estimated from single site visits. Nevertheless, few studies have validated the performance of occupancy‐detection models by creating a situation where occupancy is known, and model outputs can be compared with the truth. We tested the performance of TTD occupancy models in the face of detection heterogeneity using an experiment based on standard survey methods to monitor koala Phascolarctos cinereus populations in Australia. Known numbers of koala faecal pellets were placed under trees, and observers, uninformed as to which trees had pellets under them, carried out a TTD survey. We fitted five TTD occupancy models to the survey data, each making different assumptions about detectability, to evaluate how well each estimated the true occupancy status. Relative to the truth, all five models produced strongly biased estimates, overestimating detection probability and underestimating the number of occupied trees. Despite this, goodness‐of‐fit tests indicated that some models fitted the data well, with no evidence of model misfit. Hence, TTD occupancy models that appear to perform well with respect to the available data may be performing poorly. The reason for poor model performance was unaccounted for heterogeneity in detection probability, which is known to bias occupancy‐detection models. This poses a problem because unaccounted for heterogeneity could not be detected using goodness‐of‐fit tests and was only revealed because we knew the experimentally determined outcome. A challenge for occupancy‐detection models is to find ways to identify and mitigate the impacts of unobserved heterogeneity, which could unknowingly bias many models.     

Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble‐based methods?

In biomedical research, the logistic regression model is the most commonly used method for predicting the probability of a binary outcome. While many clinical researchers have expressed an enthusiasm for regression trees, this method may have limited accuracy for predicting health outcomes. We aimed to evaluate the improvement that is achieved by using ensemble‐based methods, including bootstrap aggregation (bagging) of regression trees, random forests, and boosted regression trees. We analyzed 30‐day mortality in two large cohorts of patients hospitalized with either acute myocardial infarction (N = 16,230) or congestive heart failure (N = 15,848) in two distinct eras (1999–2001 and 2004–2005). We found that both the in‐sample and out‐of‐sample prediction of ensemble methods offered substantial improvement in predicting cardiovascular mortality compared to conventional regression trees. However, conventional logistic regression models that incorporated restricted cubic smoothing splines had even better performance. We conclude that ensemble methods from the data mining and machine learning literature increase the predictive performance of regression trees, but may not lead to clear advantages over conventional logistic regression models for predicting short‐term mortality in population‐based samples of subjects with cardiovascular disease.     

A comparison between data requirements and availability for calibrating predictive ecological models for lowland UK woodlands: learning new tricks from old trees

Woodlands provide valuable ecosystem services, and it is important to understand their dynamics. To predict the way in which these might change, we need process‐based predictive ecological models, but these are necessarily very data intensive. We tested the ability of existing datasets to provide the parameters necessary to instantiate a well‐used forest model (SORTIE) for a well‐studied woodland (Wytham Woods). Only five of SORTIE's 16 equations describing different aspects of the life history and behavior of individual trees could be parameterized without additional data collection. One age class – seedlings – was completely missed as they are shorter than the height at which Diameter at Breast Height (DBH) is measured. The mensuration of trees has changed little in the last 400 years (focussing almost exclusively on DBH) despite major changes in the nature of the source of value obtained from trees over this time. This results in there being insufficient data to parameterize process‐based models in order to meet the societal demand for ecological prediction. We do not advocate ceasing the measurement of DBH, but we do recommend that those concerned with tree mensuration consider whether additional measures of trees could be added to their data collection protocols. We also see advantages in integrating techniques such as ground‐based LIDAR or remote sensing techniques with long‐term datasets to both preserve continuity with what has been performed in the past and to expand the range of measurements made.     

Feedbacks between plant N demand and rhizosphere priming depend on type of mycorrhizal association

Ecosystem carbon (C) balance is hypothesised to be sensitive to the mycorrhizal strategies that plants use to acquire nutrients. To test this idea, we coupled an optimality‐based plant nitrogen (N) acquisition model with a microbe‐focused soil organic matter (SOM) model. The model accurately predicted rhizosphere processes and C–N dynamics across a gradient of stands varying in their relative abundance of arbuscular mycorrhizal (AM) and ectomycorrhizal (ECM) trees. When mycorrhizal dominance was switched – ECM trees dominating plots previously occupied by AM trees, and vice versa – legacy effects were apparent, with consequences for both C and N stocks in soil. Under elevated productivity, ECM trees enhanced decomposition more than AM trees via microbial priming of unprotected SOM. Collectively, our results show that ecosystem responses to global change may hinge on the balance between rhizosphere priming and SOM protection, and highlight the importance of dynamically linking plants and microbes in terrestrial biosphere models.     

A Robust Test for Two‐Stage Design in Genome‐Wide Association Studies

Summary A two‐stage design is cost‐effective for genome‐wide association studies (GWAS) testing hundreds of thousands of single nucleotide polymorphisms (SNPs). In this design, each SNP is genotyped in stage 1 using a fraction of case–control samples. Top‐ranked SNPs are selected and genotyped in stage 2 using additional samples. A joint analysis, combining statistics from both stages, is applied in the second stage. Follow‐up studies can be regarded as a two‐stage design. Once some potential SNPs are identified, independent samples are further genotyped and analyzed separately or jointly with previous data to confirm the findings. When the underlying genetic model is known, an asymptotically optimal trend test (TT) can be used at each analysis. In practice, however, genetic models for SNPs with true associations are usually unknown. In this case, the existing methods for analysis of the two‐stage design and follow‐up studies are not robust across different genetic models. We propose a simple robust procedure with genetic model selection to the two‐stage GWAS. Our results show that, if the optimal TT has about 80% power when the genetic model is known, then the existing methods for analysis of the two‐stage design have minimum powers about 20% across the four common genetic models (when the true model is unknown), while our robust procedure has minimum powers about 70% across the same genetic models. The results can be also applied to follow‐up and replication studies with a joint analysis.     

Parameter estimation in topological analysis of binary tree structures

Different types of random binary topological trees (like neuronal processes and rivers) occur with relative frequencies that can be explained in terms of growth models. It will be shown how the model parameter determining the mode of growth can be estimated with the maximum likelihood procedure from observed data. Monte Carlo simulations were used to study the distributional properties of this estimator which appeared to have a negligible bias. It is shown that the minimum chi-square procedure yields an estimate that is very close to the maximum likelihood estimate. Moreover, the goodness-of-fit of the growth model can be inferred directly from the chi-square statistic. To illustrate the procedures we examined axonal trees from the goldfish tectum. A notion of complete partition randomness is presented as an alternative to our growth hypotheses.     

Daylength helps temperate deciduous trees to leaf‐out at the optimal time

Global warming has led to substantially earlier spring leaf‐out in temperate‐zone deciduous trees. The interactive effects of temperature and daylength underlying this warming response remain unclear. However, they need to be accurately represented by earth system models to improve projections of the carbon and energy balances of temperate forests and the associated feedbacks to the Earth's climate system. We studied the control of leaf‐out by daylength and temperature using data from six tree species across 2,377 European phenological network ( www.pep725.eu ), each with at least 30 years of observations. We found that, in addition to and independent of the known effect of chilling, daylength correlates negatively with the heat requirement for leaf‐out in all studied species. In warm springs when leaf‐out is early, days are short and the heat requirement is higher than in an average spring, which mitigates the warming‐induced advancement of leaf‐out and protects the tree against precocious leaf‐out and the associated risks of late frosts. In contrast, longer‐than‐average daylength (in cold springs when leaf‐out is late) reduces the heat requirement for leaf‐out, ensuring that trees do not leaf‐out too late and miss out on large amounts of solar energy. These results provide the first large‐scale empirical evidence of a widespread daylength effect on the temperature sensitivity of leaf‐out phenology in temperate deciduous trees.     

Point Processes for Fine‐Scale Spatial Genetics and Molecular Ecology

This paper introduces point processes into fine‐scale spatial genetics and molecular ecology. Datasets given in the form of a complete map of individuals and their genotypes can be analyzed by means of the theory of marked or multivariate point processes. Beginning with reformulation of conventional spatial autocorrelation statistics in genetics by the language of point processes, this paper first shows an example of point process models that describe spatial patterns of both tree locations and their genotypes, on the assumption of limited seed dispersal and long pollen movement. The results show that isolation‐by‐distance slightly occurs from the assumption above, and more importantly, an increment of the degree of clustering of trees reduces the degree of genetic clustering. Next, the point process model is applied to field data of secondary forest regenerated after seed tree harvesting, and tests the hypothesis that the current population was formed only from a small number of seed trees. The hypothesis was not acceptable, instead, the alternative assuming advance reproduction conducted prior to the harvesting is supported. The results of this first trial of point process models suggest that point processes can provide a useful mathematical methodology in fine‐scale spatial genetics and molecular ecology.     

Climate‐mediated habitat selection in an arboreal folivore

The decisions that animals must make to achieve a balance between quantity and quality of resources become more difficult when their habitats are patchy and differ greatly in quality across space and time. Koalas are a prime subject to study this problem because they have a specialised diet of eucalypt leaves and need to balance nutrient and water intake against toxins in the leaves, all of which can change with soil type and climate. Koalas are nocturnal and spend most of the day resting and therefore choose trees for reasons other than feeding, particularly for thermoregulation. We GPS‐tracked 40 koalas over 3 yr to determine their shift in tree selection between day and night, and in relation to daily maximum temperature, in a patchy rural landscape in north‐western NSW, Australia. The species, degree of shelter, diameter, height and elevation of each visited tree were recorded. We used generalised linear mixed effects models to compare tree use between day and night and maximum daily temperature. Koalas used more feed‐trees during the night, and more shelter‐trees during the day. They also selected taller trees with more shelter in the day compared with night. As daytime temperatures rose, koalas increasingly selected taller trees at lower elevations. Our results demonstrate that koalas need taller trees, and non‐feed species with shadier/denser foliage, to provide shelter from heat. This highlights the need both for the retention of taller, mature trees, such as remnant paddock trees, and the planting of both food and shelter trees to increase habitat area and connectivity across the landscape for arboreal species. Retaining and planting trees that provide optimum habitat will help arboreal folivores cope with the more frequent droughts and heatwaves expected with climate change.