Design and validation of a spatially explicit simulation model for bottomland hardwood forests

Species composition in forests depends on the interaction of species traits and species availability. Yet many forest simulation models focus only on interactions of adult trees and saplings, ignoring how species become members of the community. We modify a published forest model for bottomland hardwood forests (program SWAMP [Phipps, R.L., 1979. Simulation of wetlands forest vegetation dynamics. Ecol. Modell. 7, 257–288]) to make it spatially explicit and incorporate explicit seed production and dispersal algorithms. The resulting individual-based, spatially explicit forest simulator (YAFSIM) combines mechanistic seed dispersal with growth and mortality of trees to track forest dynamics over time. We describe the structure of the model and test its validity for dynamics in small bottomland hardwood patches in the Mississippi Alluvial Valley. Dynamics of species composition and basal areas of trees predicted by Yazoo Forest Simulator (YAFSIM) were similar to those of natural second- and old-growth bottomland forests. However, diversity of simulated forest patches declined over time largely because of random dynamics acting on small, isolated populations.     

Analysis of neighborhood dynamics of forest ecosystems using likelihood methods and modeling.

Advances in computing power in the past 20 years have led to a proliferation of spatially explicit, individual-based models of population and ecosystem dynamics. In forest ecosystems, the individual-based models encapsulate an emerging theory of "neighborhood" dynamics, in which fine-scale spatial interactions regulate the demography of component tree species. The spatial distribution of component species, in turn, regulates spatial variation in a whole host of community and ecosystem properties, with subsequent feedbacks on component species. The development of these models has been facilitated by development of new methods of analysis of field data, in which critical demographic rates and ecosystem processes are analyzed in terms of the spatial distributions of neighboring trees and physical environmental factors. The analyses are based on likelihood methods and information theory, and they allow a tight linkage between the models and explicit parameterization of the models from field data. Maximum likelihood methods have a long history of use for point and interval estimation in statistics. In contrast, likelihood principles have only more gradually emerged in ecology as the foundation for an alternative to traditional hypothesis testing. The alternative framework stresses the process of identifying and selecting among competing models, or in the simplest case, among competing point estimates of a parameter of a model. There are four general steps involved in a likelihood analysis: (1) model specification, (2) parameter estimation using maximum likelihood methods, (3) model comparison, and (4) model evaluation. Our goal in this paper is to review recent developments in the use of likelihood methods and modeling for the analysis of neighborhood processes in forest ecosystems. We will focus on a single class of processes, seed dispersal and seedling dispersion, because recent papers provide compelling evidence of the potential power of the approach, and illustrate some of the statistical challenges in applying the methods.     

A phenomenological model without dispersal kernel to model species migration

Phenomenological approaches to model species migration are usually based on kernel-based methods. These methods require a good knowledge of the dispersal agent behaviour for a given species. They also calculate the location of individuals independently to each other (except the mother plant) and then suppress some of them according to additional interactions such as competition, facilitation and recruitment. In this paper, we propose to use a new phenomenological method, the Gibbs method, to model tree species migration at large scale. The Gibbs method handles the location of adult individuals in terms of pairwise interactions described by a potential function. This function summarizes the set of known and unknown factors determining the spatial distribution of the individuals (or cohorts). The principle of the Gibbs method is to minimize the sum of all pairwise interactions, also called the cost function, in order to optimize the spatial point pattern according to the chosen potential function.     

A Landscape Approach to Biodiversity Conservation of Sacred Groves in the Western Ghats of India

Abstract:  Although sacred groves are important for conservation in India, the landscape that surrounds them has a vital influence on biodiversity within them. Research has focused on tree diversity inside these forest patches. In a coffee-growing region of the Western Ghats, however, landscape outside sacred groves is also tree covered because planters have retained native trees to provide shade for coffee plants. We examined the diversity of trees, birds, and macrofungi at 58 sites—10 forest-reserve sites, 25 sacred groves, and 23 coffee plantations— in Kodagu district. We measured landscape composition and configuration around each site with a geographic information system. To identify factors associated with diversity we constructed multivariate models by using a decision-tree technique. The conventional measures of landscape fragmentation such as patch size did not influence species richness. Distance of sacred groves from the forest reserve had a weak influence. The measures of landscape structure (e.g., tree cover in the surroundings) and stand structure (e.g., variability in canopy height) contributed to the variation in species richness explained by multivariate models. We suggest that biodiversity present within sacred groves has been influenced by native tree cover in the surrounding landscape. To conserve this biodiversity the integrity of the tree-covered landscape matrix will need to be conserved.     

Palatability mapping: a koala's eye view of spatial variation in habitat quality

Ecologists trying to understand the value of habitat to animals must first describe the value of resources contained in the habitat to animals and, second, they must describe spatial variation in resource quality at a resolution relevant to individual animal foraging. We addressed these issues in a study of koalas (Phascolarctos cinereus) in a Eucalyptus woodland. We measured beneficial and deterrent chemical characteristics as well as the palatability of trees using a near-infrared spectroscopic model based on direct feeding experiments. Tree use by koalas was influenced by tree size and foliar quality but was also context-dependent: trees were more likely to be visited if they were surrounded by small, unpalatable trees or by large, palatable trees. Spatial autocorrelation analysis and several mapping approaches demonstrated that foliar quality is spatially structured in the woodland at a scale relevant to foraging decisions by koalas and that the spatial structure is an important component of habitat quality.     

Tree cover in sub-Saharan Africa: rainfall and fire constrain forest and savanna as alternative stable states

Savannas are known as ecosystems with tree cover below climate-defined equilibrium values. However, a predictive framework for understanding constraints on tree cover is lacking. We present (a) a spatially extensive analysis of tree cover and fire distribution in sub-Saharan Africa, and (b) a model, based on empirical results, demonstrating that savanna and forest may be alternative stable states in parts of Africa, with implications for understanding savanna distributions. Tree cover does not increase continuously with rainfall, but rather is constrained to low (<50%, "savanna") or high tree cover (>75%, "forest"). Intermediate tree cover rarely occurs. Fire, which prevents trees from establishing, differentiates high and low tree cover, especially in areas with rainfall between 1000 mm and 2000 mm. Fire is less important at low rainfall (<1000 mm), where rainfall limits tree cover, and at high rainfall (>2000 mm), where fire is rare. This pattern suggests that complex interactions between climate and disturbance produce emergent alternative states in tree cover. The relationship between tree cover and fire was incorporated into a dynamic model including grass, savanna tree saplings, and savanna trees. Only recruitment from sapling to adult tree varied depending on the amount of grass in the system. Based on our empirical analysis and previous work, fires spread only at tree cover of 40% or less, producing a sigmoidal fire probability distribution as a function of grass cover and therefore a sigmoidal sapling to tree recruitment function. This model demonstrates that, given relatively conservative and empirically supported assumptions about the establishment of trees in savannas, alternative stable states for the same set of environmental conditions (i.e., model parameters) are possible via a fire feedback mechanism. Integrating alternative stable state dynamics into models of biome distributions could improve our ability to predict changes in biome distributions and in carbon storage under climate and global change scenarios.     

A model of surface fire,climate and forest pattern in the Sierra Nevada,California

A spatially explicit forest gap model was developed for the Sierra Nevada, California, and is the first of its kind because it integrates climate, fire and forest pattern. The model simulates a forest stand as a grid of 15×15 m forest plots and simulates the growth of individual trees within each plot. Fuel inputs are generated from each individual tree according to tree size and species. Fuel moisture varies both temporally and spatially with the local site water balance and forest condition, thus linking climate with the fire regime. Fires occur as a function of the simulated fuel loads and fuel moisture, and the burnable area is simulated as a result of the spatially heterogeneous fuel bed conditions. We demonstrate the model’s ability to couple the fire regime to both climate and forest pattern. In addition, we use the model to investigate the importance of climate and forest pattern as controls on the fire regime. Comparison of model results with independent data indicate that the model performs well in several areas. Patterns of fuel accumulation, climatic control of fire frequency and the influence of fuel loads on the spatial extent of fires in the model are particularly well-supported by data. This model can be used to examine the complex interactions among climate, fire and forest pattern across a wide range of environmental conditions and vegetation types. Our results suggest that, in the Sierra Nevada, fuel moisture can exert an important control on fire frequency and this control is especially pronounced at sites where most of the annual precipitation is in the form of snow. Fuel loads, on the other hand, may limit the spatial extent of fire, especially at elevations below 1500 m. Above this elevation, fuel moisture may play an increasingly important role in limiting the area burned.     

Competition among eucalyptus trees depends on genetic variation and resource supply

Genetic variation and environmental heterogeneity fundamentally shape the interactions between plants of the same species. According to the resource partitioning hypothesis, competition between neighbors intensifies as their similarity increases. Such competition may change in response to increasing supplies of limiting resources. We tested the resource partitioning hypothesis in stands of genetically identical (clone-origin) and genetically diverse (seed-origin) Eucalyptus trees with different water and nutrient supplies, using individual-based tree growth models. We found that genetic variation greatly reduced competitive interactions between neighboring trees, supporting the resource partitioning hypothesis. The importance of genetic variation for Eucalyptus growth patterns depended strongly on local stand structure and focal tree size. This suggests that spatial and temporal variation in the strength of species interactions leads to reversals in the growth rank of seed-origin and clone-origin trees. This study is one of the first to experimentally test the resource partitioning hypothesis for intergenotypic vs. intragenotypic interactions in trees. We provide evidence that variation at the level of genes, and not just species, is functionally important for driving individual and community-level processes in forested ecosystems.     

抚育间伐对栓皮栎种群空间分布格局的影响

抚育间伐是一种重要的改善林木生长条件的经营措施,对林分结构和动态具有重要影响。为研究抚育间伐对林木种群空间结构与格局影响的内在机制,以间伐和未间伐的栓皮栎人工林为研究对象,通过设置2个100 m×100 m样地并进行每木定位和调查,在采用径级结构代替年龄结构方法将栓皮栎种群划分为幼树(2 cm≤DBH<5 cm)、小树(5 cm≤DBH<13 cm)和大树(DBH≥13 cm)3个生长阶段的基础上,分别采用Ripley’s K函数衍生的g(r)函数和双变量g12(r)函数,对栓皮栎种群空间分布点格局及不同生长阶段栓皮栎种群之间的关联性进行了研究。结果表明,间伐和未间伐样地栓皮栎种群空间分布点格局分别在0-16 m和0-33 m距离尺度内呈聚集分布,而分别在大于16 m和33 m距离尺度内呈随机分布;间伐和未间伐样地栓皮栎幼树、小树和大树的株数比分别为8?741?699和261?1134?683,且间伐样地栓皮栎幼树、小树和大树种群分别在0-14、1-16、0-6 m距离尺度内呈现均匀或聚集分布,而在其他距离尺度上表现为随机分布;栓皮栎幼树、小树和大树之间仅在间伐样地0-6 m距离尺度内呈现一定的相关性,而在未间伐样地更大的距离尺度内有显著的关联性,如栓皮栎幼树和大树之间在6-38 m距离尺度上呈显著正相关。因此,抚育间伐一定程度上使得栓皮栎种群在更大距离尺度上呈现出随机分布状态,并弱化了不同生长阶段的林木栓皮栎种群的关联性,这调整了栓皮栎种群空间竞争关系,有利于大径级林木个体的培育。该研究可以为开展抚育间伐对林木种群的影响的研究提供理论依据,也可以为制定科学合理的抚育技术措施提供参考。     

Untangling positive and negative biotic interactions: views from above and below ground in a forest ecosystem

In ecological communities, the outcome of plant-plant interactions represents the net effect of positive and negative interactions occurring above and below ground. Untangling these complex relationships can provide a better understanding of mechanisms that underlie plant-plant interactions and enhance our ability to predict population, community, and ecosystem effects of biotic interactions. In forested ecosystems, tree seedlings interact with established vegetation, but the mechanisms and outcomes of these interactions are not well understood. To explore such mechanisms, we manipulated above- and belowground interactions among tree seedlings, shrubs, and trees and monitored seedling survival and growth of six species (Pinus banksiana, Betula papyrifera, P. resinosa, Quercus rubra, P. strobus, and Acer rubrum) in mature pine-dominated forest in northern Minnesota, USA. The forest had a moderately open canopy and sandy soils. Understory manipulations were implemented in the forest interior and in large gaps and included removal of shrubs (no interactions), tieback of shrubs (belowground), removal of shrubs with addition of shade (aboveground), and unmanipulated shrubs (both below- and aboveground). We found that shrubs either suppressed or facilitated seedling survival and growth depending on the seedling species, source of interaction (e.g., above- or belowground), and ecological context (e.g., gap or forest interior). In general, shrubs strongly influenced survival and growth in gaps, with more modest effects in the forest interior. In gaps, the presence of shrub roots markedly decreased seedling growth and survival, supporting the idea that belowground competition may be more important in dry, nutrient-poor sites. Shrub shade effects were neutral for three species and facilitative for the other three. Facilitation was more likely for shade-tolerant species. In the forest interior, shrub shade negatively affected seedling survival for the most shade-intolerant species. For several species the net effect of shrubs masked the existence of both positive and negative interactions above and below ground. Our results highlight the complexity of plant-plant interactions, demonstrate that outcomes of these interactions vary with the nature of resource limitation and the ecophysiology of the species involved, and suggest that ecological theory that rests on particular notions of plant-plant interactions (e.g., competition) should consider simultaneous positive and negative interactions occurring above and below ground.     

不同演替阶段中黧蒴栲种群的大小结构与分布格局

在中亚热带常绿阔叶林,有代表性地选择三个黧蒴栲群落类型,即黧蒴栲纯林（常绿阔叶林皆伐地自然演替而成的黧蒴栲纯林,用生长锥对优势木进行随机抽查得其最大年龄为１３ａ）、以黧蒴栲为优势种的混交林（经优势木随机抽测其最大年龄为２４ａ）和黧蒴栲已不成为优势种的混交林（实为天然次生林,优势木随机抽测最大年龄为５３ａ）。测定分析结果表明,黧蒴栲群落在自然演替的前期即幼林阶段的种群大小级结构呈典型的三角状增长型;     

A universal approach to estimate biomass and carbon stock in tropical forests using generic allometric models

Allometric equations allow aboveground tree biomass and carbon stock to be estimated from tree size. The allometric scaling theory suggests the existence of a universal power-law relationship between tree biomass and tree diameter with a fixed scaling exponent close to 8/3. In addition, generic empirical models, like Chave's or Brown's models, have been proposed for tropical forests in America and Asia. These generic models have been used to estimate forest biomass and carbon worldwide. However, tree allometry depends on environmental and genetic factors that vary from region to region. Consequently, theoretical models that include too few ecological explicative variables or empirical generic models that have been calibrated at particular sites are unlikely to yield accurate tree biomass estimates at other sites. In this study, we based our analysis on a destructive sample of 481 trees in Madagascar spiny dry and moist forests characterized by a high rate of endemism (> 95%). We show that, among the available generic allometric models, Chave's model including diameter, height, and wood specific gravity as explicative variables for a particular forest type (dry, moist, or wet tropical forest) was the only one that gave accurate tree biomass estimates for Madagascar (R2 > 83%, bias < 6%), with estimates comparable to those obtained with regional allometric models. When biomass allometric models are not available for a given forest site, this result shows that a simple height-diameter allometry is needed to accurately estimate biomass and carbon stock from plot inventories.     

Partitioning the factors of spatial variation in regeneration density of shade-tolerant tree species

Understanding coexistence of highly shade-tolerant tree species is a longstanding challenge for forest ecologists. A conceptual model for the coexistence of sugar maple (Acer saccharum) and American beech (Fagus grandibfolia) has been proposed, based on a low-light survival/high-light growth trade-off, which interacts with soil fertility and small-scale spatiotemporal variation in the environment. In this study, we first tested whether the spatial distribution of seedlings and saplings can be predicted by the spatiotemporal variability of light availability and soil fertility, and second, the manner in which the process of environmental filtering changes with regeneration size. We evaluate the support for this hypothesis relative to the one for a neutral model, i.e., for seed rain density predicted from the distribution of adult trees. To do so, we performed intensive sampling over 86 quadrats (5 x 5 m) in a 0.24-ha plot in a mature maple-beech community in Quebec, Canada. Maple and beech abundance, soil characteristics, light availability, and growth history (used as a proxy for spatiotemporal variation in light availability) were finely measured to model variation in sapling composition across different size classes. Results indicate that the variables selected to model species distribution do effectively change with size, but not as predicted by the conceptual model. Our results show that variability in the environment is not sufficient to differentiate these species' distributions in space. Although species differ in their spatial distribution in the small size classes, they tend to correlate at the larger size class in which recruitment occurs. Overall, the results are not supportive of a model of coexistence based on small-scale variations in the environment. We propose that, at the scale of a local stand, the lack of fit of the model could result from the high similarity of species in the range of environmental conditions encountered, and we suggest that coexistence would be stable only at larger spatial scales at which variability in the environment is greater.     

Evaluation of sampling methods for the estimation of structural indices in forest stands

The paper is about the accurate (i.e. unbiased and precise) and efficient estimation of structural indices in forest stands. We present SIAFOR, a computer programme for the calculation of four nearest-neighbour indices, which describe the spatial arrangement of tree positions, the distribution pattern of species, and the size differentiation between trees. The study uses SIAFOR as a sampling simulator in eight completely stem-mapped forest stands of varying area and structural complexity. We statistically evaluate two sample types (distance and plot sampling), comparing sampling error, bias and minimum sample size for index estimation. We introduce the concepts of measurement expansion factor (MEF) and design expansion factor (DEF) for the technical evaluation of sample type efficiency (optimal sample type). Results indicate that sampling error can reach high levels and that minimum sample sizes for index estimation often amply exceed the limit of 20% of tree density or 20 trees per species per hectare, that we set as the highest feasible sample size in normal situations. We found clear feasibility limits (in terms of minimal tree densities and reachable accuracy levels) for the estimation of all investigated indices. Generally, equal or higher sample sizes are needed for plot sampling than for distance sampling to reach equal accuracy levels. Nevertheless, plot sampling resulted more efficient for the estimation of tree size differentiation at low to medium accuracy levels. For all other investigated indices distance sampling resulted more efficient than plot sampling. Minimum sample size increases with accuracy and is negatively correlated with tree density. At a given accuracy level minimum sample size is highest for the estimation of relative mingling and lowest for tree size differentiation; furthermore it is generally lower in large stands than in small ones. Because of the consistency of our conclusions in all of the investigated stands, we think they apply in most stands of similar area (between 1 and 10 ha) and species diversity (not more than four species).     

Modeling the Persistence of Small Populations of Strongly Interdependent Species: Figs and Fig Wasps

Conservation problems are usually studied at the population or ecosystem levels. Formulating predictive theory for the domain in between has been difficult. Fig trees and their pollinating wasps, principally tropical groups of organisms, form pairs of obligate mutualists that provide unique opportunities for studying the influence of species interactions on the survival of small populations. Survival of each partner depends on that of the associated species. The pollinator population can be maintained only if figs are produced year-round. Because fig trees flower synchronously at the individual level, wasps have to locate a new individual host tree at each generation. We describe results of simulation models estimating the minimum number of trees required to maintain a wasp population using two levels of the criteria: (1) different probability of survival (50% and 99%) and (2) different time of survival (5 or 1000 years). We also examined how these different estimates are sensitive to differences in the seasonality of flowering period and in the length of the period of female receptivity in figs. Such estimates can be used to understand the potential effects of the reduction of fig population size via fragmentation. Unlike most studies on the effect of low population size on population viability, our paper focuses on maintenance of a biotic interaction, rather than on single-species dynamics. The biotic interaction on which we focus is important because figs in many tropical ecosystems may be keystone resources for frugivores that are in turn essential seed dispersal agents for other plants.     

Modelling the impact of flooding stress on the growth performance of woody species using fuzzy logic

Among the driving processes responsible for riparian forest dynamics the species-specific impact of flooding on the development of woody plants plays a key role—particularly for lowland rivers. Only a few of the forest succession models currently in use incorporate the flooding stress response of trees. This situation is mainly due to the incomplete investigation of the flooding tolerance processes and the related abiotic and biotic factors. In an attempt to use the wide-ranging but still rather vague knowledge available on flooding stress, the research presented in this paper proposes an approach to model tree response to flooding using the fuzzy set theory. The model is illustrated for the case of central European species. Flooding stress response to the abiotic factors of duration, depth and frequency of flooding differs according to five flooding tolerance classes and is expressed by means of a growth factor that limits optimal tree growth. We show that existing fuzzy set theory is able to generate and calibrate a flood stress response model which in turn can be incorporated into more complex forest succession models adapted to riparian areas.     

Multi-model analysis of tree competition along environmental gradients in southern New England forests.

Robust predictions of competitive interactions among canopy trees and variation in tree growth along environmental gradients represent key challenges for the management of mixed-species, uneven-aged forests. We analyzed the effects of competition on tree growth along environmental gradients for eight of the most common tree species in southern New England and southeastern New York using forest inventory and analysis (FIA) data, information theoretic decision criteria, and multi-model inference to evaluate models. The suite of models estimated growth of individual trees as a species-specific function of average potential diameter growth, tree diameter at breast height, local environmental conditions, and crowding by neighboring trees. We used ordination based on the relative basal area of species to generate a measure of site conditions in each plot. Two ordination axes were consistent with variation in species abundance along moisture and fertility gradients. Estimated potential growth varied along at least one of these axes for six of the eight species; peak relative abundance of less shade-tolerant species was in all cases displaced away from sites where they showed maximum potential growth. Our crowding functions estimate the strength of competitive effects of neighbors; only one species showed support for the hypothesis that all species of competitors have equivalent effects on growth. The relative weight of evidence (Akaike weights) for the best models varied from a low of 0.207 for Fraxinus americana to 0.747 for Quercus rubra. In such cases, model averaging provides a more robust platform for prediction than that based solely on the best model. We show that predictions based on the selected best models dramatically overestimated differences between species relative to predictions based on the averaged set of models.     

Importance of conserving large and old trees to continuity of tree-related microhabitats

Protecting structural features, such as tree-related microhabitats (TreMs), is a cost-effective tool crucial for biodiversity conservation applicable to large forested landscapes. Although the development of TreMs is influenced by tree diameter, species, and vitality, the relationships between tree age and TreM profile remain poorly understood. Using a tree-ring-based approach and a large data set of 8038 trees, we modeled the effects of tree age, diameter, and site characteristics on TreM richness and occurrence across some of the most intact primary temperate forests in Europe, including mixed beech and spruce forests. We observed an overall increase in TreM richness on old and large trees in both forest types. The occurrence of specific TreM groups was variably related to tree age and diameter, but some TreM groups (e.g., epiphytes) had a stronger positive relationship with tree species and elevation. Although many TreM groups were positively associated with tree age and diameter, only two TreM groups in spruce stands reacted exclusively to tree age (insect galleries and exposed sapwood) without responding to diameter. Thus, the retention of trees for conservation purposes based on tree diameter appears to be a generally feasible approach with a rather low risk of underrepresentation of TreMs. Because greater tree age and diameter positively affected TreM development, placing a greater emphasis on conserving large trees and allowing them to reach older ages, for example, through the establishment of conservation reserves, would better maintain the continuity of TreM resource and associated biodiversity. However, this approach may be difficult due to the widespread intensification of forest management and global climate change.     

Inverse modeling for effective dispersal: Do we need tree size to estimate fecundity?

The estimation of the dispersal kernel for the seedling and sapling stages of the recruitment process was made possible through the application of inverse modeling to dispersal data. This method uses the spatial coordinates of adult trees and the counts of seedlings (or saplings) in small quadrats to estimate the dispersal kernel. The unknown number of recruits produced by an adult tree (the fecundity) is estimated - simultaneously with the dispersal kernel - via an allometric linear model relating the unknown quantity with a (easily) measured characteristic of the adult tree (usually the basal area). However, the allometric relation between tree size and reproductive success in the sapling (or seedling) stage may not be strong enough when numerous, well-documented, post-dispersal processes (such as safe-site limitation for recruitment) cause large post-dispersal seedling mortality, which is usually unrelated to the size of the tree that dispersed them. In this paper we hypothesize that when tree size and reproductive success in the seedling/sapling stage are not well correlated then the use of allometry in inverse modeling is counter-productive and may lead to poor model fits. For these special cases we suggest using a new model for effective dispersal that we term the unrestricted fecundity (UF) model that, contrary to allometric models, makes no assumptions on the fecundities; instead they are allowed to vary freely from one tree to another and even to be zero for trees that are reproductively inactive. Based on this model, we examine the hypothesis that when tree size and reproductive success are weakly correlated and the fecundities are estimated independently of tree size the goodness-of-fit and the ecological meaning of dispersal models (in the seedling or sapling stage) may be enhanced. Parameters of the UF model are estimated through the EM algorithm and their standard errors are approximated via the observed information matrix. We fit the UF model to a dataset from an expanding European beech population of central Spain as well as to a set of simulated dispersal data were the correlation between reproductive success and tree size was moderate. In comparisons with a simple allometric model, the UF model fitted the data better and the parameter estimates were less biased. We suggest using this new approach for modeling dispersal in the seedling and sapling stages when tree size (or other adult-specific covariates) is not deemed to be in strong relation to the reproductive success of adults. Models that use covariates for modeling the fecundity of adults should be preferred when reproductive success and tree size guard a strong relationship.     

Modeling freshwater fish distributions using multiscale landscape data: A case study of six narrow range endemics

Species distribution models (SDMs) have become integral tools in scientific research and conservation planning. Despite progress in the assessment of various statistical models for use in SDMs, little has been done in way of evaluating appropriate ecological models. In this paper, we evaluate the multiscale filter framework as a suitable theoretical model for predicting freshwater fish distributions in the upper Green River system (Ohio River drainage), USA. The spatial distributions of six fishes with contrasting biogeographies were modeled using boosted regression trees and multiscale landscape data. Species biogeography did not appear to affect predictive performance and all models performed well statistically with receiver operating characteristic area under the curve (AUC) ranging from 0.87 to 0.98. Predictive maps show accurate estimations of ranges for five of six species based on historical collections. The relative influence of each type of environmental feature and spatial scale varied markedly with between species. A hierarchical effect was detected for narrowly distributed species. These species were highly influenced by soil composition at larger spatial scales and land use/land cover (LULC) patterns at more proximal scales. Conversely, LULC pattern was the most influential feature for widely distributed at all spatial scales. Using multiscale data capable of capturing hierarchical landscape influences allowed production of accurate predictive models and provided further insight into factors controlling freshwater fish distributions.