Brice B. Hanberry

Regime Shifts and Weakened Environmental Gradients in Open Oak and Pine Ecosystems

Fire suppression allows tree species that are intolerant of fire stress to increase their distribution, potentially resulting in disruption of historical species-environmental relationships. To measure changes between historical General Land Office surveys (1815 to 1850) and current USDA Forest Inventory and Assessment surveys (2004 to 2008), we compared composition, distribution, and site factors of 21 tree species or species groups in the Missouri Ozarks. We used 24 environmental variables and random forests as a classification method to model distributions. Eastern redcedar, elms, maples, and other fire-sensitive species have increased in dominance in oak forests, with concurrent reductions by oak species; specific changes varied by ecological subsection. Ordinations displayed loss of separation between formerly distinctive oak and fire-sensitive tree species groups. Distribution maps showed decreased presence of disturbance-dependent oak and pine species and increased presence of fire-sensitive species that generally expanded from subsections protected from fire along rivers to upland areas, except for eastern redcedar, which expanded into these subsections. Large scale differences in spatial gradients between past and present communities paralleled reduced influence of local topographic gradients in the varied relief of the Missouri Ozarks, as fire-sensitive species have moved to higher, drier, and sunnier sites away from riverine corridors. Due to changes in land use, landscapes in the Missouri Ozarks, eastern United States, and world-wide are changing from open oak and pine-dominated ecosystems to novel oak-mixed species forests, although at fine scales, forests are becoming more diverse in tree species today. Fire suppression weakened the influence by environmental gradients over species dominance, allowing succession from disturbance-dependent oaks to an alternative state of fire-sensitive species. Current and future research and conservation that rely on historical relationships and ecological principles based on disturbance across the landscape will need to incorporate modern interactions among species for resources into management plans and projections.

Comparison of historical and current forest surveys for detection of homogenization and mesophication of Minnesota forests

Intense harvesting and slash fires during the late 1800s and early 1900s led to homogenization throughout the Great Lakes region via the conversion from tamarack, pine, and spruce forests to aspen forests, which are supported by the forest products industry. Subsequently, mesophication occurred in the eastern United States due to fire suppression, transforming oak woodlands to mixed mesophytic forests. We explored both homogenization and mesophication at a regional scale by quantifying changes in community composition and density between historical General Land Office survey points and current USDA Forest Analysis and Inventory plots for Minnesota’s Laurentian Mixed and Eastern Broadleaf Forest provinces. We used the Morisita plotless density estimator and applied corrections for surveyor bias to estimate density for historical forests and we used known densities of FIA plots to predict current densities with random forests, an ensemble regression tree method, and terrain and soil predictor variables. Of the 43 ecological units used in the analysis, only one current community was similar to its historical counterpart. Within the Laurentian Mixed Forest province, forest density of primarily mature aspen stands is reduced slightly today compared to the tamarack-dominated forests of the past. Conversely, in the Eastern Broadleaf Forest province, forest densities have increased compared to historical pine and oak woodlands, due to increases of densely growing, fire-sensitive species. Ordinations of functional traits and structure showed substantial changes between current and historical communities as well as reduced differentiation among current communities compared to their historical counterparts. Homogenization in the Laurentian Mixed Forest is occurring by transition from early-successional to late-successional species, with associated changes in forest ecosystems, and homogenization and mesophication in the Eastern Broadleaf Forest are occurring by transition from disturbance-stabilized genera of open forest ecosystems to non-disturbance-dependent genera of dense forests. Despite different starting points of historical forest ecosystems in the Laurentian Mixed Forest and Eastern Broadleaf Forest, we found homogenization and mesophication to be interrelated in the convergence of composition and densities along a common trajectory to dense forests composed of late-successional species in Minnesota.

Importance of succession, harvest, and climate change in determining future composition in U.S. Central Hardwood Forests

Most temperate forests in U.S. are recovering from heavy exploitation and are in intermediate successional stages where partial tree harvest is the primary disturbance. Changes in regional forest composition in response to climate change are often predicted for plant functional types using biophysical process models. These models usually simplify the simulation of succession and harvest and may not consider important species-specific demographic processes driving forests changes. We determined the relative importance of succession, harvest, and climate change to forest composition changes in a 125-million ha area of the Central Hardwood Forest Region of U.S. We used a forest landscape modeling approach to project changes in density and basal area of 23 tree species due to succession, harvest, and four climate scenarios from 2000 to 2300. On average, succession, harvest, and climate change explained 78, 17, and 1% of the variation in species importance values (IV) at 2050, respectively, but their contribution changed to 46, 26, and 20% by 2300. Climate change led to substantial increases in the importance of red maple and southern species (e.g., yellow-poplar) and decreases in northern species (e.g., sugar maple) and most of widely distributed species (e.g., white oak). Harvest interacted with climate change and accelerated changes in some species (e.g., increasing southern red oak and decreasing American beech) while ameliorated the changes for others (e.g., increasing red maple and decreasing white ash). Succession was the primary driver of forest composition change over the next 300 years. The effects of harvest on composition were more important than climate change in the short term but climate change became more important than harvest in the long term. Our results show that it is important to model species-specific responses when predicting changes in forest composition and structure in response to succession, harvest, and climate change.

Adjusting Forest Density Estimates for Surveyor Bias in Historical Tree Surveys

Abstract The U.S. General Land Office surveys, conducted between the late 1700s to early 1900s, provide records of trees prior to widespread European and American colonial settlement. However, potential and documented surveyor bias raises questions about the reliability of historical tree density estimates and other metrics based on density estimated from these records. In this study, we present two complementary approaches to adjust density estimates for possible surveyor bias. We addressed the problem of surveyor bias of density estimates by simulating the effects of (1) rank of selected trees (compared to assuming the nearest trees were selected) and (2) specific surveyor bias in selection of (a) quadrant location, (b) quadrant configuration, (c) azimuth, and (d) combined species and diameter. We then developed regression equations to calculate adjustment quotients for these biases, making the adjustment quotients transferable to any similar datasets. For the rank-based approach, an unvarying rank of 2 (selection of the second nearest tree instead of always the nearest tree) decreased density estimates to about 25 to 45% of the actual density, depending on number of trees per survey point, resulting in corrected density estimates that are 2.2 to 4 times greater than uncorrected density estimates. However, constant selection of the second nearest tree did not occur; varying ranks decreased density estimates to around 55 to 65% of the density, resulting in corrected density estimates about 1.5 to 1.8 times greater than uncorrected values. For the bias-based approach, depending on the specific General Land Office dataset, bias for tree species and diameter alone may decrease density estimates by about 35%. Quadrant configuration and azimuth preference may decrease density estimates by about 15% each. The quadrant location bias has negligible effects on the density estimates. The overall density estimates may be about 35 to 55% of the actual density and correction of the density estimate will approximately double the value. These methods can provide a range of estimates, from low values of uncorrected density to high values of corrected density, about the amount that varying surveyor bias may have decreased density estimates for any areas where bias is detected (i.e., non-random frequencies) in point-centered quarter surveys. Adjustments will increase reliability of historical forest density estimates and their applications for restoration.

Spatial pattern corrections and sample sizes for forest density estimates of historical tree surveys

The U.S. General Land Office land surveys document trees present during European settlement. However, use of these surveys for calculating historical forest density and other derived metrics is limited by uncertainty about the performance of plotless density estimators under a range of conditions. Therefore, we tested two plotless density estimators, developed by Morisita and Pollard, for two, three, and four trees per survey point under simulated ranges of tree densities, non-uniform densities, and different tree spatial distributions. Based on these results, we developed estimator corrections and determined number of survey points needed for reliable density estimates. The Morisita estimator was accurate for densities ranging from 5 to 1,000 trees per unit area, non-uniform densities, random and regular spatial distribution, and outperformed the Pollard estimator. Estimators using points with two or three trees did need a simple correction to account for overestimation. Likewise, for clustered distributions, depending on the number of trees per survey point and the amount of clustering, there should be adjustment for a range of under and overestimation. Sample sizes for survey points with three or four trees should be at least 200 survey points, and 1,000 survey points will have density estimates within ±10% tolerance range of actual density. For survey points with two trees, the minimum sample size should be 600 survey points, and 2,000 survey points should be the target value. These results provide guidelines for researchers to improve density estimates of historical forests.

Multi-model comparison on the effects of climate change on tree species in the eastern U.S.: results from an enhanced niche model and process-based ecosystem and landscape models

ContextSpecies distribution models (SDM) establish statistical relationships between the current distribution of species and key attributes whereas process-based models simulate ecosystem and tree species dynamics based on representations of physical and biological processes. TreeAtlas, which uses DISTRIB SDM, and Linkages and LANDIS PRO, process-based ecosystem and landscape models, respectively, were used concurrently on four regional climate change assessments in the eastern Unites States.ObjectivesWe compared predictions for 30 species from TreeAtlas, Linkages, and LANDIS PRO, using two climate change scenarios on four regions, to derive a more robust assessment of species change in response to climate change.MethodsWe calculated the ratio of future importance or biomass to current for each species, then compared agreement among models by species, region, and climate scenario using change classes, an ordinal agreement score, spearman rank correlations, and model averaged change ratios.ResultsComparisons indicated high agreement for many species, especially northern species modeled to lose habitat. TreeAtlas and Linkages agreed the most but each also agreed with many species outputs from LANDIS PRO, particularly when succession within LANDIS PRO was simulated to 2300. A geographic analysis showed that a simple difference (in latitude degrees) of the weighted mean center of a species distribution versus the geographic center of the region of interest provides an initial estimate for the species’ potential to gain, lose, or remain stable under climate change.ConclusionsThis analysis of multiple models provides a useful approach to compare among disparate models and a more consistent interpretation of the future for use in vulnerability assessments and adaptation planning.

Clarifying the role of fire in the deciduous forests of eastern North America: reply to Matlack

Fire is an important disturbance in ecosystems across the eastern deciduous forests of North America (Brose et al. 2014). Matlack (2013) provided an interpretation of historical and contemporary fire in this region. Although we applaud Matlack for correcting simplistic assumptions that fire was ubiquitous and all plant communities need to burn regularly to maintain biodiversity, we believe his interpretation of the role of fire is erroneous on several counts. Most problematic is his statement “ . . . it seems prudent to limit the use of prescribed burning east of the prairie-woodland transition zone.” Adherence to this overgeneralized advice would inevitably result in losses of native diversity across the eastern deciduous forest.

Historical Open Forest Ecosystems in the Missouri Ozarks: Reconstruction and Restoration Targets

Current forests no longer resemble historical open forest ecosystems in the eastern United States. In the absence of representative forest ecosystems under a continuous surface fire regime at a large scale, reconstruction of historical landscapes can provide a reference for restoration efforts. For initial expert-assigned vegetation phases ranging from prairie to forest across the Missouri Ozarks landscape, we reconstructed historical (1815 to 1850) forest densities, basal area, percent stocking or growing space, and canopy cover. After examination of structural means and ranges by initial expected vegetation phases, we classified vegetation phases based on percent stocking boundaries of 30–55% for open woodlands and 55–75% for closed woodlands (diameters ≥ 12.7 cm). We suggest that a percent stocking boundary of 10% may separate prairie and savannas, but we did not identify any large scale prairies in Missouri. We provided structure of each vegetation phase for restoration targets; mean historical densities of vegetation phases ranged from 81 trees/ha in savannas to 285 trees/ha in non-oak/non-pine forests (diameters ≥ 12.7 cm). Due to greater densities than expected and larger diameter trees than current forests, historical forests may have been primarily (about 65%) woodlands with nearly closed canopies, unlike the open canopies presumed during settlement in the Missouri Ozarks. However, a closed yet single canopy layer can transmit enough light to sustain an herbaceous ground cover, given an open midstory due to frequent surface fires. Restoration of open woodlands across all public lands is not practical, but restoration of lower density forests composed of drought-tolerant tree species should translate to management for changing climate.

Winning and losing tree species of reassembly in Minnesota's mixed and broadleaf forests.

We examined reassembly of winning and losing tree species, species traits including shade and fire tolerance, and associated disturbance filters and forest ecosystem types due to rapid forest change in the Great Lakes region since 1850. We identified winning and losing species by changes in composition, distribution, and site factors between historical and current surveys in Minnesota’s mixed and broadleaf forests. In the Laurentian Mixed Forest, shade-intolerant aspen replaced shade-intolerant tamarack as the most dominant tree species. Fire-tolerant white pine and jack pine decreased, whereas shade-tolerant ashes, maples, and white cedar increased. In the Eastern Broadleaf Forest, fire-tolerant white oaks and red oaks decreased, while shade-tolerant ashes, American basswood, and maples increased. Tamarack, pines, and oaks have become restricted to sites with either wetter or sandier and drier soils due to increases in aspen and shade-tolerant, fire-sensitive species on mesic sites. The proportion of shade-tolerant species increased in both regions, but selective harvest reduced the applicability of functional groups alone to specify winners and losers. Harvest and existing forestry practices supported aspen dominance in mixed forests, although without aspen forestry and with fire suppression, mixed forests will transition to a greater composition of shade-tolerant species, converging to forests similar to broadleaf forests. A functional group framework provided a perspective of winning and losing species and traits, selective filters, and forest ecosystems that can be generalized to other regions, regardless of species identity.

Pseudoabsence Generation Strategies for Species Distribution Models

Background Species distribution models require selection of species, study extent and spatial unit, statistical methods, variables, and assessment metrics. If absence data are not available, another important consideration is pseudoabsence generation. Different strategies for pseudoabsence generation can produce varying spatial representation of species. Methodology We considered model outcomes from four different strategies for generating pseudoabsences. We generating pseudoabsences randomly by 1) selection from the entire study extent, 2) a two-step process of selection first from the entire study extent, followed by selection for pseudoabsences from areas with predicted probability <25%, 3) selection from plots surveyed without detection of species presence, 4) a two-step process of selection first for pseudoabsences from plots surveyed without detection of species presence, followed by selection for pseudoabsences from the areas with predicted probability <25%. We used Random Forests as our statistical method and sixteen predictor variables to model tree species with at least 150 records from Forest Inventory and Analysis surveys in the Laurentian Mixed Forest province of Minnesota. Conclusions Pseudoabsence generation strategy completely affected the area predicted as present for species distribution models and may be one of the most influential determinants of models. All the pseudoabsence strategies produced mean AUC values of at least 0.87. More importantly than accuracy metrics, the two-step strategies over-predicted species presence, due to too much environmental distance between the pseudoabsences and recorded presences, whereas models based on random pseudoabsences under-predicted species presence, due to too little environmental distance between the pseudoabsences and recorded presences. Models using pseudoabsences from surveyed plots produced a balance between areas with high and low predicted probabilities and the strongest relationship between density and area with predicted probabilities ≥75%. Because of imperfect accuracy assessment, the best assessment currently may be evaluation of whether the species has been sufficiently but not excessively predicted to occur.