Abstract Management of white‐tailed deer ( Odocoileus virginianus ) to control their consumptive effects on understory forest vegetation has been a long‐standing challenge in Pennsylvania, USA. In 2003, the Pennsylvania Game Commission implemented the Deer Management Assistance Program (DMAP) to allow landowners to increase antlerless harvest in localized areas, which has been used by the Pennsylvania Department of Conservation and Natural Resources (DCNR) on state forest lands. We evaluated survey data describing hunter participation and satisfaction over 2 periods (2013–2015 and 2019–2021) and across 4 DMAP areas on state forest lands managed by DCNR. Two study sites had greater DMAP permit allocations (1 permit per 6 ha) to attempt to reduce deer density compared to 2 other study sites (1 permit per 20 ha). Prior to 2020, only DMAP permits could be used to harvest antlerless deer during the first week of the firearm hunting season. In 2020, regulation changes allowed both DMAP and wildlife management unit antlerless licenses to be used throughout the firearm hunting season and DMAP permit allocations continued to be sold out only in areas where most hunters lived >80 km from the DMAP area. Satisfaction increased between periods, with hunters twice as likely to be satisfied during 2019–2021; however, increased satisfaction may be partly explained by dissatisfied hunters dropping out, as >50% of hunters purchased a single DMAP permit in 6 years, and only 20% of hunters purchased ≥1 permit in both periods. The strongest positive predictors of satisfaction were seeing an antlerless deer, harvesting an antlerless deer, and repeated participation through purchasing multiple DMAP permits. Consequently, understanding why few hunters are consistent purchasers of DMAP permits may provide insights into how landowner permit allocation or other currently unknown factors influence participation in the DMAP or similar programs encouraging harvest of antlerless deer.

In eastern North America, cucumber-root (Medeola virginiana) is a widely distributed perennial forest herb that has been used as an ecological indicator of white-tailed deer (Odocoileus virginiana) browsing due to its predictable responses to deer exclusion (i.e., increased height, abundance). However, cucumber-root is less likely to occupy sites with high concentrations of soil manganese (Mn), which may limit its utility as an indicator under limiting soil conditions. We examined responses of cucumber-root total counts and flowering abundance to deer exclusion, competitive release from surrounding vegetation, and soil application of dolomitic limestone to determine the relative effects of these treatments over 7 years (2014–2021). Prior to treatment, initial total and flowering abundance were best explained by soil extractable Mn concentration. Post-treatment, fencing best explained increases in total counts, but flowering abundance was most affected by soil extractable Mn and pH. Initial soil Mn concentrations determined the effectiveness of dolomitic limestone application; microplots with moderate to high soil Mn (> 6 cmolc kg–1) had increased flowering with increased pH, while flowering decreased on microplots with initially low soil Mn concentrations (< 6 cmolc kg–1). We suspect changes to soil chemistry from liming affected plant stress, but that stress was either alleviated or intensified depending on initial soil Mn concentrations. Herbivory is an important driver of plant abundance across our study area but flowering response, a critical component of plant demography, seems to be driven by soil Mn. Cucumber-root may have limited utility as an indicator because soil chemistry mediates flowering responses to deer exclusion.

Since the 1960s, forest planners have used linear programming models to develop management plans for large, forested areas. Hundreds of academic papers have presented such models, incorporating multiple objectives, a growing diversity of management interventions, and uncertainty, among other things. Three basic ways to formulate these models have been used: Model I, III, and III. We define these models based on the sequence of management unit states represented by the variables. In Model I, variables represent a sequence of states from the beginning of the planning horizon to the end. In Model II, variables represent a sequence of states from one intervention to the next. Finally, in Model III, variables represent a single arc in a management unit’s decision tree, including only a beginning and an ending state. We formulate each type of model for a case study with three increasingly complex scenarios incorporating additional ecosystem services. Our results indicate that, despite requiring more variables and constraints, Model III requires the least time to formulate, largely because it has the least dense parameter matrix. Model II has the shortest solution times, with Model III close behind. Model I requires both the longest formulation and solution times.

The root causes of forest tree regeneration failure are difficult to resolve, although numerous studies show ungulate herbivory, soil conditions, and competition from undesirable vegetation as likely contributors. To better understand the relative importance of each issue, we conducted a 7-year manipulative experiment to assess the interactive effects of white-tailed deer (Odocoileus virginianus) herbivory, soil acidity, and competing vegetation on tree regeneration in oak-hickory forests of central Pennsylvania, USA. Outcomes depended on initial tree seedling abundance, and all three factors had significant interactions. At low initial seedling abundance, fencing resulted in the greatest increase, but all treatments had a positive effect on seedling growth and abundance. At higher initial seedling abundance, abundance failed to recover 7 years after herbicide treatment and soil pH was an important predictor. When soil pH was >4.6 from lime application, seedling growth and abundance in unfenced controls with high initial abundance was comparable to the fenced-only treatment. Competing vegetation, assumed to be a symptom of excessive, long-term deer herbivory, does not seem to be the primary factor limiting tree regeneration in our study area. Ameliorating acid deposition warrants greater consideration as a management action because it could provide long-lasting benefits compared to short-term fence installations.

Linear programming models have been used in forest management planning since the 1960s. These models have been formulated in three basic ways: Models I, II, and III, which are defined by the sequences of management unit states represented by the variables. In Model I, variables represent sequences of states from the beginning of the planning horizon to the end. In Model II, variables represent sequences of states from one intervention to the next. Finally, in Model III, variables represent a single arc in a management unit’s decision tree, i.e., two states. The objectives of this paper are to clarify the definitions of these model variations and evaluate the advantages and disadvantages of each model. This second objective is to test the hypothesis that the relative performance of these models varies with the increasing number of ecosystem services (ES) incorporated into the models. This objective was achieved by formulating a case study problem using each model type. The case study includes three increasingly complex scenarios, each incorporating additional ecosystem services. Results show that despite having more variables and constraints, Model III requires the least time to formulate due to its less dense parameter matrix. Model II has the shortest solution times, followed closely by Model III, while Model I requires the longest times for both formulation and solution. These results are increasingly apparent in more complex scenarios.

Nutrition is fundamental to white-tailed deer (Odocoileus virginianus) management given its relationship to habitat carrying capacity and population productivity. Ecological Sites (ESs) are a United States federal landscape management unit of specific land potential due to unique soils, topography, climate, parent material, and perhaps deer forage nutritional value. We present results of a study that extends the use of ESs to inform white-tailed deer management by evaluating indicator plant chemistry in two spring forb species, Indian cucumber root (Medeola virginiana) and Canada mayflower (Maianthemum canadense), across the northcentral Appalachians. We sampled spring forbs and underlying soils across two ESs: Dry, upland, oak-maple-hemlock hardwood forest (OMH) and Deep soil, high slope, northern hardwood forests (NHF). Plant elemental content, soil pH, and site aspect, slope and elevation were measured. Our results show that forb chemistry differs between species and within a species geographically. Indian cucumber root, as compared to Canada mayflower, has significantly higher Mg, Na, Cu, Fe, and Zn, and lower Mn. Canada mayflower in the NHF ES, versus OMH ES, was found to have significantly higher K, Mn, and B. Indian cucumber root in the NHF ES, versus the OMH ES, was found to have significantly higher Mg, Al, Fe, and Ca:P ratio but lower K. Linear discriminant analysis shows that plant tissue Mn was the best discriminator between species, and between ESs, Canada mayflower plant tissue Mn and Indian cucumber plant tissue P, K, Ca, Mg and Mn were best discriminators. Given that nutrition determines habitat carrying capacity, differences in forage nutrition between ESs may have different potentials to support deer. Forage nutrition is an important aspect of deer habitat conditions and carrying capacity, thus ESs are likely to support deer populations with different growth potential, which means that even if the same plant species occur in different ESs their nutritional value to deer may differ.

Linear programming formulations of forest ecosystem management (FEM) problems proposed in the 1960s have been adapted and improved upon over the years. Generating management alternatives for forest planning is a key step in building these models. Global forests are diverse, and a variety of models have been developed to simulate management alternatives. This paper describes iGen, a forest prescription generator that employs a rule-based system (AI-RBS), an AI technique that is often used for expert systems. iGen was designed with the goal of being able to generate management alternatives for virtually any FEM problem. The prescription generator is not designed for, adapted to, focused on—and ideally not limited to—any specific region, landscape, forest condition, projection method, or yield function. Instead, it aims to maximize generality, enabling it to address a broad range of FEM problems. The goal is that practitioners and researchers who do not have and do not want to develop their own alternative generator can use iGen as a prescription generator for their problem instances. For those who choose to develop their own alternative generators, we hope that the concepts and algorithms we propose in this paper will be useful in designing their own systems. iGen’s flexibility can be attributed to three key features. First, users can define the state variable vector for management units according to the available data, models (production functions), and objectives of their problem instance. Second, users also define the types of interventions that can be applied to each type of management unit and create a rule base describing the conditions under which each intervention can be applied. Finally, users specify the equations of motion that determine how the state vector for each management unit will be updated over time, depending on which, if any, interventions are applied. Other than this basic structure, virtually everything in an iGen problem instance is user-defined. iGen uses these key elements to simulate all possible management prescriptions for each management unit and stores the resulting information in a database that is structured to efficiently store the output data from these simulations and to facilitate the generation of optimization models for ultimately determining the Pareto frontier for a given FEM problem. This article introduces iGen, illustrating its concepts, structure, and algorithms through two FEM example problems with contrasting forest management practices: natural regeneration with shelterwood harvests and plantation/coppice. For data and iGen source programs, visit github.com/SilvanaNobre/iGenPaper.

Deer herbivory has a reputation for suppressing tree seedling development in Northern hardwood forests. We examined survival and growth of sugar maple (Acer saccharum) and ash (Fraxinus spp.) seedlings in a controlled factorial experiment with differing light conditions and levels of deer access in a Northern hardwoods forest in Wisconsin, USA. Measurements were made in similar to 380 m(3) harvest gaps, in transition zones adjacent to gaps, and under closed canopy conditions, both inside and outside of deer exclosures. Browse incidence was initially greater in unfenced treatments, but a general decline through time eliminated this difference. Seven-year sur-vival of both species groups was correlated positively with initial root collar diameter (RCD) and was greater in transition zones. Ash seedling survival was greater in plots with greater overall seedling aggregate height. Soils were primarily differentiated by available nitrogen, which positively influenced height growth of sugar maple in transition zones but did not influence ash growth. Although sugar maple height growth was correlated positively with initial RCD, greater initial height reduced growth rates, both as a simple effect (sugar maple) and in combination with initial RCD (ash). Ash growth correlated negatively with seedling aggregate height in gaps but was unaffected in transition or canopy zones. Allometric coefficients of RCD:height indicated some influence of deer herbivory which was not detected in other analyses. Coefficient values trended downward from year 2 to year 9, but wide confidence intervals limit the value of this metric as an indicator of seedling community resilience with regard to deer.

Throughout the northeastern United States (U.S.) and Europe, relict charcoal hearths (RCHs) are regularly being discovered in proximity to furnaces once used for the extraction of metal from ore or quick-lime production; charcoal produced in hearths was used as a furnace fuel. Given previous research has shown that topographic and subsurface disturbance can be great when a hearth is constructed, we hypothesize that hearth construction alters surface hydrology and soil chemistry in en-vironments in and near hearths. We used a landscape classification process to identify 6758 hearths near furnaces at Greenwood and Pine Grove Furnace State Park, central and southcentral Pennsylvania, U.S. Two types of digital elevation model wetness indexes were used to quantify surface hydrology effects in and around hearths. Modeled wetness conditions were compared to field soil volumetric water content in RCHs near Greenwood Furnace State Park. Modeled wetness indexes indicate that RCH interiors are significantly wetter than RCH rim areas; RCHs are acting as a landscape moisture sink. Results also indicate that RCHs on slopes result in downslope drier conditions below RCHs. Field measured volumetric water content indicates that as distance from the center of the hearth increases, soil moisture significantly decreases. Geomorphic position was found to not be related to RCH wetness. Soil from RCHs, compared to nearby native soils, has significantly higher total C, a lower Mehlich 3 extractable acidity, higher Ca and P. No trend was evident with RCH soil chemistry and geomorphic position. The high frequency of RCH occurrence, in proximity to the furnace's RCHs supported, suggests that RCHs today could locally be an important niche for understory flora and fauna. Further research could explore how RCHs might be affecting surrounding plant populations and how within RCH patterns, especially on hillslopes, might represent a distinctly different scale of physical and chemical variability.

Stump sprouting is a widespread phenomenon in North American hardwood tree species following logging or severe crown damage from natural disturbances such as fire, wind, or insect attack. However, other than the effects of species and tree size, factors that influence the probability of sprouting are not well understood. Data from harvested stands in Pennsylvania and Connecticut, USA, were used to evaluate the effects of several variables on stump sprouting frequencies measured within the first year after cutting for several oak and other hardwood species. After adjusting for species and diameter of the “parent” tree (ortet), clearcut harvests were found to result in a higher frequency of sprouted stumps than shelterwood harvests or crop tree releases. In addition, the probability of sprouting was higher for trees in the Ridge and Valley province of Pennsylvania vs. the Appalachian Plateaus, and in general it was higher on dry vs. moist sites. After accounting for all measured variables, there remained statistically significant stand-to-stand differences in sprouting frequency that arose from unknown causes. Results should temper expectations of stump sprout contributions to regeneration stocking that are based on simple models derived from a small number of stands or a limited geographic area. On the stand-level basis at which most managers work, the actual contribution of sprouts to future stand development may vary widely from modeled expectations.

Understanding how present-day abrupt change may alter forest ecosystem services is becoming more important due to ever-growing anthropogenic stresses. Forest managers trying the adapt to anthropogenic stress can benefit from the study and quantification of past abrupt changes in forests, especially when the legacy of past disturbance is still evident. Across the United Kingdom, Europe, and recently the northeastern United States, the examination of historic forest change due to charcoal manufacturing for the firing of iron or lime furnaces is yielding new insights relative to landscape stability, anthropogenic vs natural soil genesis, and forest evolution. A landscape classification process was used in the Central Appalachians (Pennsylvania) to identify 6,758 RCHs near Greenwood Furnace (Greenwood Furnace State Park) and Pine Grove Furnace (Pine Grove Furnace State Park). Topographic wetness index (TWI), and SAGA wetness index (SWI) were created using ~1m LiDAR data for two study areas to quantify surface hydrology effects and were compared to field soil volumetric water content (VWC) measurements. Modeled TWI and SWI values were different for RCH areas when compared to surrounding non-hearth areas indicating that RCHs were acting as a moisture sink. We also found that RCH platforms have different TWI and SWI values than rim areas. Using field measured volumetric water content, we found that as distance from the center of the RCH increases, the drier the soil becomes. Geomorphic position did not affect wetness. Surface soil samples were collected at 51 RCHs in the Greenwood Furnace study area. Laboratory analyses revealed that RCH soils have higher C content than surrounding native soils. Furthermore, while the pH of RCH soils is like native soils, the acidity is greater in RCHs. RCH soils at Greenwood Furnace were found to have lower Mehlich 3 P concentrations and lower K potentially effecting plant growth. RCH soils were found to have higher Ca concentration when compared to native soils. To examine within RCH differences in soil chemistry and morphology more closely, 8 of the 51 RCHs were sampled intensely along a topographic gradient. Control pits were excavated directly upslope from the RCHs. The RCHs were sampled in 5 positions across the hearth from the upslope to down slope position (A upslope rim of the RCH; B halfway point between A and C; C RCH center; D halfway C and E; E downslope rim of the RCH). Soil profiles were described and sampled at each position. The soil samples were analyzed for trace and rare earth element content (Aqua Regia digestion), soil pH (water) and fertility (Mehlich 3 extraction). Results indicated that RCHs are potentially a unique location of refugia for forest flora and perhaps fauna due to the unique geochemistry with higher bases and C and some concentrated metals and a higher soil water content hypothesized to be due to an observed restrictive morphology. Future research should more closely investigate whether RCHs support unique species assemblages and how they may play a role in enhancing today’s forest biodiversity.

Hearths used for 19th and 20th century charcoal manufacturing have been found to have unique plant com-munities or to produce unique growth characteristics for some species but not others. Given known differences in hearth morphology, within hearth physical and chemical differences may exist and result in unique ecologic niches. We examined soil stratigraphy across 8 relict charcoal hearths (RCH) and control soils on different landforms near a 19th century furnace complex (Greenwood Furnace, northcentral Appalachians USA). Soils were analyzed for particle size, total and trace elements, and fertility. Platform creation resulted in soils from upslope RCH positions mixed with subsurface materials on the downslope side to create a stabilized platform. The thin, uniform thickness of charcoal surface horizons (Ac) indicate that RCHs were not used more than once for charcoal manufacturing or that charcoal was always removed very efficiently. While rubification of soil or rock from high heat was seen in 6 of 8 sites sampled, it was not extensive across sampled areas of any one hearth, which indicate hearth use may not be frequent, hot enough, or spatially disparate. Soil fertility characteristics change within RCHs but also by landscape position. Downslope RCH positions are enriched in some parameters compared to control soils (total C, Mehlich 3 Mg, Ca, and Aquia Regia digestion Mn) and that enrichment often is from the surface downward. Downslope enrichment within RCH soils may have occurred from charcoal and released ions, slope erosion and accumulation, or transportation of constructed materials during RCH creation. Landscape position may accentuate or mute soil chemistry differences. Greenwood Furnace RCHs have unique patterns of chemistry, which could result in unique niches for flora and maybe fauna within RCH. Future research could more closely investigate whether hearths support unique species assemblages and how they may play a role in enhancing today's forest biodiversity.

We estimate the carbon sequestration supply curve at the stand level based on the optimal rotation decision and conduct a marginal analysis for payments necessary for postponing harvest for additional 1-year increments of two commercially important species in the United States, loblolly pine and Douglas-fir. Under certain costs, production and timber prices assumptions, payments ranged from 62.23 (26.97–105.87) ac/yr. for loblolly pine plantations and399.17 (189.80–628.72) ac/yr. for Douglas-fir plantations. Our results indicate that higher carbon sequestration occurs with higher site index, higher trees per acre, and in unthinned stands. Significant variability within and between species was heavily dependent on the number of years that final harvest was postponed. In addition, we show the effect of prices on the quantity supplied under multiple silvicultural treatments. The study should assist willing forest landowners and potential partners to determine initial reservation prices for carbon sequestration and temporary provision for a 1-year period in line with programs offering this contracting mechanism. One approach to sequestering carbon in forests above ground is to postpone timber-harvesting operations, therefore accumulating standing carbon for an additional period. Remuneration above the financial minimum necessary for postponement alters forest management decision-making at the stand level, and therefore potentially economic and ecological patterns if adopted at large scales. One new carbon offset program is currently available that provides an annual payment to forest landowners enrolled in the program. The methodology used in this study will allow landowners and forest stakeholders to value the necessary payment for postponing harvest for multiple 1-year periods past the financially optimal age for final harvest. These results are sensitive to site index, trees per acre, and whether the stand had an intermediate thinning.

Forest management can be seen as a sequential decision-making problem to determine an optimal scheduling policy, e.g., harvest, thinning, or do-nothing, that can mitigate the risks of wildfire. Markov Decision Processes (MDPs) offer an efficient mathematical framework for optimizing forest management policies. However, computing optimal MDP solutions is computationally challenging for large-scale forests due to the curse of dimensionality, as the total number of forest states grows exponentially with the numbers of stands into which it is discretized. In this work, we propose a Deep Reinforcement Learning (DRL) approach to improve forest management plans that track the forest dynamics in a large area. The approach emphasizes on prevention and mitigation of wildfire risks by determining highly efficient management policies. A large-scale forest model is designed using a spatial MDP that divides the square-matrix forest into equal stands. The model considers the probability of wildfire dependent on the forest timber volume, the flammability, and the directional distribution of the wind using data that reflects the inventory of a typical eucalypt (Eucalyptus globulus Labill) plantation in Portugal. In this spatial MDP, the agent (decision-maker) takes an action at one stand at each step. We use an off-policy actor-critic with experience replay reinforcement learning approach to approximate the MDP optimal policy. In three different case studies, the approach shows good scalability for providing large-scale forest management plans. The results of the expected return value and the computed DRL policy are found identical to the exact optimum MDP solution, when this exact solution is available, i.e., for low dimensional models. DRL is also found to outperform a genetic algorithm (GA) solutions which were used as benchmarks for large-scale model policy.

This paper describes a new method for detecting individual tree stems that was designed to perform well in the challenging hardwood-dominated, mixed-species forests common to the northeastern U.S., where canopy height-based methods have proven unreliable. Most prior research in individual tree detection has been performed in homogenous coniferous or conifer-dominated forests with limited hardwood presence. The study area in central Pennsylvania, United States, includes 17+ tree species and contains over 90% hardwoods. Existing methods have shown reduced performance as the proportion of hardwood species increases, due in large part to the crown-focused approaches they have employed. Top-down approaches are not reliable in deciduous stands due to the inherent complexity of the canopy and tree crowns in such stands. This complexity makes it difficult to segment trees and accurately predict tree stem locations based on detected crown segments. The proposed voxel column-based approach has advantages over both traditional canopy height model-based methods and computationally demanding point-based solutions. The method was tested on 1125 reference trees, ≥10 cm diameter at breast height (DBH), and it detected 68% of all reference trees and 87% of medium and large (sawtimber-sized) trees ≥28 cm DBH. Significantly, the commission rate (false predictions) was negligible as most raw false positives were confirmed in follow-up field visits to be either small trees below the threshold for recording or trees that were otherwise missed during the initial ground survey. Minimizing false positives was a priority in tuning the method. Follow-up in-situ evaluation of individual omission and commission instances was facilitated by the high spatial accuracy of predicted tree locations generated by the method. The mean and maximum predicted-to-reference tree distances were 0.59 m and 2.99 m, respectively, with over 80% of matches within <1 m. A new tree-matching method utilizing linear integer programming is presented that enables rigorous, repeatable matching of predicted and reference trees and performance evaluation. Results indicate this new tree detection method has potential to be operationalized for both traditional forest management activities and in providing the more frequent and scalable inventories required by a growing forest carbon offsets industry.

Abrupt changes in a forest ecosystem, whether natural or anthropogenic, are changes that occur over short time periods; such disturbance has the potential to drive state changes and alter forest resilience. Understanding how present-day abrupt forest change may alter ecosystem services is becoming more important due to ever-growing anthropogenic stresses. Forest managers trying the adapt to anthropogenic stress can benefit from the study and quantification of past abrupt changes in forests, especially when the legacy of past disturbance is still evident. Across the United Kingdom, Europe, and recently the northeastern United States, the examination of historic forest change due to charcoal manufacturing for the firing of iron or lime furnaces is yielding new insights relative to landscape stability, anthropogenic vs natural soil genesis, and forest evolution. We present results of a study that strives to evaluate how historic land clearing for the charcoal industry (supporting iron furnaces) affected local soils and may drive surrounding present day forest composition. We incorporate field sampling of hearth soils and modeled hydrologic parameters (in hearth and non-hearth areas), to quantify the uniqueness of relict charcoal hearth (RCH) systems. We identified 1,239 hearths using a LiDAR terrain analysis; approximately 10% of these were visited to quantify hearth morphology and soil moisture differences on and off hearth. Nine hearths from this 10% were intensively sampled and were associated with a northern Appalachian, USA furnace that was in operation from 1867 to 1904. Three profiles were excavated across each hearth and compared to an adjacent soil profile on the same contour. Soil descriptions were made of hearths and soil samples analyzed for total, trace and rare earth element content (Aqua Regia digestion). Soil pH (water) and fertility (Mehlich III extraction) were also determined. Results indicate that hearths have a unique geochemistry with higher bases and some concentrated metals and higher organic carbon. Coupled with a higher hearth soil water content, hypothesized to be due to an observed restrictive subsurface morphology and higher organic carbon, hearths are potentially unique locations of refugia for forest flora and fauna. Future research should more closely investigate whether hearths support unique species assemblages and how they may play a role in enhancing today’s forest biodiversity.

Localized management of white-tailed deer (Odocoileus virginianus) involves the removal of matriarchal family units with the intent to create areas of reduced deer density. However, application of this approach has not always been successful, possibly because of female dispersal and high deer densities. We developed a spatially explicit, agent-based model to investigate the intensity of deer removal required to locally reduce deer density depending on the surrounding deer density, dispersal behavior, and size and shape of the area of localized reduction. Application of this model is illustrated using the example of abundant deer populations in Pennsylvania, USA. Most scenarios required at least 5 years before substantial deer density reductions occurred. Our model indicated that a localized reduction was successful for scenarios in which the surrounding deer density was lowest (30 deer/mi(2)), localized antlerless harvest rates were >= 30%, and the removal area was >= 5 mi(2). When the size of the removal area was < 5 mi(2), end population density was highly variable and, in some scenarios, exceeded the initial density. The shape of the area of localized reduction had less influence on the ability to reduce deer density than the size. There were no differences in mean deer density in the same size circle or square removal areas. Similarly, increasing the ratio of sides (length: width) in rectangular removal areas had little influence on the ability to locally reduce deer densities. Situations in which deer density was higher (40 or 50 deer/mi(2)) required antlerless removal rates to exceed 30% and took more than 5 years to considerably reduce density in the localized area regardless of its size. These results indicate that the size of the removal area, surrounding deer density, and antlerless harvest rate are the most influential factors in locally reducing deer density. Therefore, localized management likely can be an effective strategy for lower density herds, especially in larger removal areas. For high density herds, the success of this strategy would depend most on the ability of resource managers to achieve consistently high antlerless harvest rates.

Throughout the northeastern United States and Europe, relic charcoal hearths (RCHs) are more regularly being discovered in proximity to furnaces used for iron or quick-lime production; charcoal was used as a primary fuel source in the furnaces. RCHs have been found across parts of Europe and Connecticut, USA in different hillslope positions, on vary degrees of slope and aspect, all of which can be a factor affecting the shape of the RCH. Their usage for charcoal production varied with the time period, furnaces were in operation with some hearths being used once and older ones (such as in Europe) being used multiple times. RCHs across the northcentral Appalachians, USA have been minimally investigated, thus determining where they occur on the landscape, their shape, and their morphologic positions will be useful in discerning their effect on surface hydrology and soil development. Our study focuses on developing a repeatable process for: finding RCHs and quantifying how RCHs may alter surface hydrology.We used a combination of processed LiDAR data to create hillshades, and slope gradients to visualize RCHs. A total of 6,758 hearths have been digitized across three study areas that reflect different historical time periods of construction and environments. We hypothesize that the construction of RCHs can alter the surface hydrology of their surrounding environments. To fully quantify the landscape-level effects of RCHs, a subset of the total was created to fully digitize the RCHs’ area. The RCH was broken into their rim and platform components. A topographic wetness index (TWI), and SAGA wetness index (SWI) was created for two study areas in order to quantify surface hydrology effects. We found that RCH platforms have a significantly higher TWI and SWI than the rim counterparts indicating that the platform is wetter than the RCH outer rims. Geomorphic position was found to not effect wetness. Using field measured volumetric water content, we found that as distance from the center of the hearth increases, the drier the soil becomes. Using a combination of GIS flow path analysis, and RCH geometry, standardized ellipses using the axis of local RCHs and the mean area of the total RCHs were created to understand the upslope (control) and downslope (experiment) effects of hearths on the surface hydrology. Preliminary analysis indicates that downslope positions from RCHs are drier than upslope positions and that there is a significant difference in the relationship between slope position and distance from an RCH and the corresponding TWI and SWI values. Future research will address the effect of slope position and distance to quantify the effect of RHCs on surface hydrology. Furthermore, the soil chemical changes from RCH creation and the increase moisture may increase the habitat for rare species of both plants and animals that otherwise would not be present. Understanding the extent of the impact human activity can have on various ecosystems can help forest managers, conservationists, pedologists, and climatologists better adapt their management or research pursuits within a specific environment to prepare for future changes, natural or anthropogenic.

Oaks (Quercus spp.) are becoming less abundant in most of the Central Hardwood Region of the eastern United States, and this is creating shifts in forest composition that will likely have important economic and ecological consequences. In large measure, these changes originate with deficiencies in the oak regeneration cohort preceding stand-replacement disturbances such as timber harvest. To sustain the oak resource, managers need better information on the connection between pre-harvest and early stand conditions and regeneration outcomes. In this study, we used direct observations of oak seedling dominance in the stem exclusion stage of stand development (mean age = 17.4 years) to model the probability of successful regeneration during stand initiation as a function of stand conditions before and after harvest (ages -1, 1, 4, and 7 years). For pre-harvest conditions, the most predictive model was based solely on the aggregate height of advance regeneration oak seedlings > 15 cm in sample plots. As expected, post-harvest models were more predictive, and increasingly more predictive with the passage of time, and they were optimized by contrasting the height of the plot-dominant oak seedling with the heights of competing tree species. The predictive power of post-harvest models increased most between ages 1 and 4 years and only slightly between ages 4 and 7, indicating that age 4 is an optimal time to evaluate opportunities to favor oak regeneration with early silvicultural interventions. Of the two most common competitors, black birch (Betula lenta) had the more inhibitory effect on the success of oak regeneration when it was present. However, red maple (Acer rubrum) was the more important competitor because of its very high frequency of occurrence in plots occupied by oak seedlings.

The loss of species diversity and plant community structure throughout the temperate deciduous forests of North America have often been attributed to overbrowsing by white-tailed deer (Odocoileus virginanus). Slow species recovery following removal from browsing, or reduction in deer density, has been termed a legacy effect of past deer herbivory. However, vegetation legacy effects have also coincided with changes to soil chemistry throughout the north-eastern USA. In this paper, we assess the viability of soil chemistry (i.e. pH, extractable nutrients and extractable metals) and other factors (topography, light, overstory basal area and location) as alternative explanations for a lack of vegetation recovery. We compared the relative effects of soil chemistry, site conditions and short-term (1-2 year) deer exclusion on single-species occupancy probabilities of 10 plant taxa common to oak-hickory forests in central Pennsylvania. We found detection for all modelled species was constant and high ((p) over cap > 0.65), and occupancy probability of most taxa was best explained by at least one soil chemistry parameter. Specifically, ericaceous competing vegetation was more likely to occupy acidic (pH < 3.5), base cation-poor (K < 0.20 cmol(c) kg(-1)) sites, while deer-preferred plants were less likely to occur when soil manganese exceeded 0.1 cmol(c) kg(-1). Short-term deer exclusion did not explain occupancy of any plant taxon, and site conditions were of nominal importance. This study demonstrates the importance of soil chemistry in shaping plant community composition in the north-central Appalachians, and suggests soil as an alternative, or additional, explanation for deer vegetation legacy effects. We suggest that the reliance on phyto-indicators of deer browsing effects may overestimate the effects of browsing if those species are also limited by unfavourable soil conditions. Future research should consider study designs that address the complexity of deer forest interactions, especially in areas with complex site-vegetation histories.