Danny L. Fry

Historical and current landscape‐scale ponderosa pine and mixed conifer forest structure in the Southern Sierra Nevada

Many managers today are tasked with restoring forests to mitigate the potential for uncharacteristically severe fire. One challenge to this mandate is the lack of large-scale reference information on forest structure prior to impacts from Euro-American settlement. We used a robust 1911 historical dataset that covers a large geographic extent (>10,000 ha) and has unbiased sampling locations to compare past and current forest conditions for ponderosa pine and mixed conifer forests in the southern Sierra Nevada. The 1911 dataset contained records from 18,052 trees in 378 sampled transects, totaling just over 300 ha in transect area. Forest structure was highly variable in 1911 and shrubs were found in 54% of transects. Total tree basal area ranged from 1 to 60 m2 ha−1 and tree density from 2 to 170 ha−1 (based on trees >30 cm dbh). K-means cluster analysis divided transects into four groups: mixed conifer-high basal area (MC High BA), mixed conifer-average basal area (MC Ave BA), mixed conifer-average basal ...

Wildfire and Spatial Patterns in Forests in Northwestern Mexico: The United States Wishes It Had Similar Fire Problems

Knowledge of the ecological effect of wildfire is important to resource managers, especially from forests in which past anthropogenic influences, e.g., fire suppression and timber harvesting, have been limited. Changes to forest structure and regeneration patterns were documented in a relatively unique old-growth Jeffrey pine-mixed conifer forest in northwestern Mexico after a July 2003 wildfire. This forested area has never been harvested and fire suppression did not begin until the 1970s. Fire effects were moderate especially considering that the wildfire occurred at the end of a severe, multi-year (1999-2003) drought. Shrub consumption was an important factor in tree mortality and the dominance of Jeffrey pine increased after fire. The Baja California wildfire enhanced or maintained a patchy forest structure; similar spatial heterogeneity should be included in US forest restoration plans. Most US forest restoration plans include thinning from below to separate tree crowns and attain a narrow range for residual basal area/ha. This essentially produces uniform forest conditions over broad areas that are in strong contrast to the resilient forests in northern Baja California. In addition to producing more spatial heterogeneity in restoration plans of forests that once experienced frequent, low-moderate intensity fire regimes, increased use of US wildfire management options such as wildland fire use as well as appropriate management responses to non-natural ignitions could also be implemented at broader spatial scales to increase the amount of burning in western US forests.

Novel characterization of landscape‐level variability in historical vegetation structure

We analyzed historical timber inventory data collected systematically across a large mixed-conifer-dominated landscape to gain insight into the interaction between disturbances and vegetation structure and composition prior to 20th century land management practices. Using records from over 20 000 trees, we quantified historical vegetation structure and composition for nine distinct vegetation groups. Our findings highlight some key aspects of forest structure under an intact disturbance regime: (1) forests were low density, with mean live basal area and tree density ranging from 8-30 m2 /ha and 25-79 trees/ha, respectively; (2) understory and overstory structure and composition varied considerably across the landscape; and (3) elevational gradients largely explained variability in forest structure over the landscape. Furthermore, the presence of large trees across most of the surveyed area suggests that extensive stand-replacing disturbances were rare in these forests. The vegetation structure and composition characteristics we quantified, along with evidence of largely elevational control on these characteristics, can provide guidance for restoration efforts in similar forests.

Evaluating short- and long-term impacts of fuels treatments and simulated wildfire on an old-forest species

Fuels-reduction treatments are commonly implemented in the western U.S. to reduce the risk of high-severity fire, but they may have negative short-term impacts on species associated with older forests. Therefore, we modeled the effects of a completed fuels-reduction project on fire behavior and California Spotted Owl (Strix occidentalis occidentalis) habitat and demography in the Sierra Nevada to assess the potential short- and long-term trade-offs. We combined field-collected vegetation data and LiDAR data to develop detailed maps of forest structure needed to parameterize our fire and forest-growth models. We simulated wildfires under extreme weather conditions (both with and without fuels treatments), then simulated forest growth 30 years into the future under four combinations of treatment and fire: treated with fire, untreated with fire, treated without fire, and untreated without fire. We compared spotted owl habitat and population parameters under the four scenarios using a habitat suitability index developed from canopy cover and large-tree measurements at nest sites and from previously derived statistical relationships between forest structure and fitness (k) and equilibrium occupancy at the territory scale. Treatments had a positive effect on owl nesting habitat and demographic rates up to 30 years after simulated fire, but they had a persistently negative effect throughout the 30-year period in the absence of fire. We conclude that fuels-reduction treatments in the Sierra Nevada may provide long-term benefits to spotted owls if fire occurs under extreme weather conditions, but can have long-term negative effects on owls if fire does not occur. However, we only simulated one fire under the treated and untreated scenarios and therefore had no measures of variation and uncertainty. In addition, the net benefits of fuels treatments on spotted owl habitat and demography depends on the future probability that fire will occur under similar weather and ignition conditions, and such probabilities remain difficult to quantify. Therefore, we recommend a landscape approach that restricts timber harvest within territory core areas of use (;125 ha in size) that contain critical owl nesting and roosting habitat and locates fuels treatments in the surrounding areas to reduce the potential for high-severity fire in territory core areas.

Fuel treatment impacts on estimated wildfire carbon loss from forests in Montana, Oregon, California, and Arizona

Using forests to sequester carbon in response to anthropogenically induced climate change is being considered across the globe. A recent U.S. executive order mandated that all federal agencies account for sequestration and emissions of greenhouse gases, highlighting the importance of understanding how forest carbon stocks are influenced by wildfire. This paper reports the effects of the most common forest fuel reduction treatments on carbon pools composed of live and dead biomass as well as potential wildfire emissions from six different sites in four western U.S. states. Additionally, we predict the median forest product life spans and uses of materials removed during mechanical treatments. Carbon loss from modeled wildfire-induced tree mortality was lowest in the mechanical plus prescribed fire treatments, followed by the prescribed fire-only treatments. Wildfire emissions varied from 10–80 Mg/ha and were lowest in the prescribed fire and mechanical followed by prescribed fire treatments at most sites. Mean biomass removals per site ranged from approximately 30–60 dry Mg/ha; the median lives of products in first use varied considerably (from 50 years). Our research suggests most of the benefits of increased fire resistance can be achieved with relatively small reductions in current carbon stocks. Retaining or growing larger trees also reduced the vulnerability of carbon loss from wildfire. In addition, modeled vulnerabilities to carbon losses and median forest product life spans varied considerably across our study sites, which could be used to help prioritize treatment implementation.

Contrasting Spatial Patterns in Active-Fire and Fire- Suppressed Mediterranean Climate Old-Growth Mixed Conifer Forests

In Mediterranean environments in western North America, historic fire regimes in frequent-fire conifer forests are highly variable both temporally and spatially. This complexity influenced forest structure and spatial patterns, but some of this diversity has been lost due to anthropogenic disruption of ecosystem processes, including fire. Information from reference forest sites can help management efforts to restore forests conditions that may be more resilient to future changes in disturbance regimes and climate. In this study, we characterize tree spatial patterns using four-ha stem maps from four old-growth, Jeffrey pine-mixed conifer forests, two with active-fire regimes in northwestern Mexico and two that experienced fire exclusion in the southern Sierra Nevada. Most of the trees were in patches, averaging six to 11 trees per patch at 0.007 to 0.014 ha−1, and occupied 27–46% of the study areas. Average canopy gap sizes (0.04 ha) covering 11–20% of the area were not significantly different among sites. The putative main effects of fire exclusion were higher densities of single trees in smaller size classes, larger proportion of trees (≥56%) in large patches (≥10 trees), and decreases in spatial complexity. While a homogenization of forest structure has been a typical result from fire exclusion, some similarities in patch, single tree, and gap attributes were maintained at these sites. These within-stand descriptions provide spatially relevant benchmarks from which to manage for structural heterogeneity in frequent-fire forest types.

Beyond reducing fire hazard: fuel treatment impacts on overstory tree survival

Fuel treatment implementation in dry forest types throughout the western United States is likely to increase in pace and scale in response to increasing incidence of large wildfires. While it is clear that properly implemented fuel treatments are effective at reducing hazardous fire potential, there are ancillary ecological effects that can impact forest resilience either positively or negatively depending on the specific elements examined, as well as treatment type, timing, and intensity. In this study, we use overstory tree growth responses, measured seven years after the most common fuel treatments, to estimate forest health. Across the five species analyzed, observed mortality and future vulnerability were consistently low in the mechanical- only treatment. Fire-only was similar to the control for all species except Douglas-fir, while mechanical-plus-fire had high observed mortality and future vulnerability for white fir and sugar pine. Given that overstory trees largely dictate the function of forests and services they provide (e.g., wildlife habitat, carbon sequestration, soil stability) these results have implications for understanding longer-term impacts of common fuel treatments on forest resilience.

A Vegetation Mapping Strategy for Conifer Forests by Combining Airborne LiDAR Data and Aerial Imagery

Abstract. Accurate vegetation mapping is critical for natural resources management, ecological analysis, and hydrological modeling, among other tasks. Remotely sensed multispectral and hyperspectral imageries have proved to be valuable inputs to the vegetation mapping process, but they can provide only limited vegetation structure characteristics, which are critical for differentiating vegetation communities in compositionally homogeneous forests. Light detection and ranging (LiDAR) can accurately measure the forest vertical and horizontal structures and provide a great opportunity for solving this problem. This study introduces a strategy using both multispectral aerial imagery and LiDAR data to map vegetation composition and structure over large spatial scales. Our approach included the use of a Bayesian information criterion algorithm to determine the optimized number of vegetation groups within mixed conifer forests in two study areas in the Sierra Nevada, California, and an unsupervised classification technique and post hoc analysis to map these vegetation groups across both study areas. The results show that the proposed strategy can recognize four and seven vegetation groups at the two study areas, respectively. Each vegetation group has its unique vegetation structure characteristics or vegetation species composition. The overall accuracy and kappa coefficient of the vegetation mapping results are over 78% and 0.64 for both study sites. Résumé. La cartographie précise de la végétation est essentielle entre autres pour la gestion des ressources naturelles, l’analyse écologique, et la modélisation hydrologique. Les approches d’imagerie multispectrale et hyperspectrale par télédétection se sont avérées de précieuses contributions au processus de la cartographie de la végétation, mais elles ne peuvent fournir qu’un nombre limité de caractéristiques sur la structure de la végétation, qui sont essentielles pour différencier les communautés végétales dans les forêts de composition homogènes. La télédétection par laser «light detection and ranging» (LiDAR) peut mesurer avec précision les structures verticales et horizontales de la forêt, et fournit une formidable opportunité de résoudre ce problème. Cette étude présente une stratégie qui utilise à la fois l’imagerie multispectrale aérienne et des données LiDAR pour cartographier la composition et la structure de la végétation à grandes échelles spatiales. Notre approche comprenait l’utilisation d’un algorithme du critère d’information Bayésien pour déterminer le nombre optimal de groupes de végétation dans les forêts mixtes de conifères sur deux zones d’étude dans les Sierra Nevada, en Californie, ainsi qu’une technique de classification non supervisée et une analyse post hoc pour cartographier ces groupes de végétation dans les deux zones d’étude. Les résultats montrent que la stratégie proposée peut reconnaitre quatre et sept groupes de végétation dans les deux zones d’étude respectivement. Chaque groupe de végétation a des caractéristiques uniques de structure de la végétation ou de composition des espèces de la végétation. La précision globale et le coefficient kappa des résultats de la cartographie de la végétation sont de plus de 78% et 0,64 pour les deux sites d’étude.

Forest fuel treatment detection using multi-temporal airborne lidar data and high-resolution aerial imagery: a case study in the Sierra Nevada Mountains, California

ABSTRACT Treatments to reduce forest fuels are often performed in forests to enhance forest health, regulate stand density, and reduce the risk of wildfires. Although commonly employed, there are concerns that these forest fuel treatments (FTs) may have negative impacts on certain wildlife species. Often FTs are planned across large landscapes, but the actual treatment extents can differ from the planned extents due to operational constraints and protection of resources (e.g. perennial streams, cultural resources, wildlife habitats). Identifying the actual extent of the treated areas is of primary importance to understand the environmental influence of FTs. Light detection and ranging (lidar) is a powerful remote-sensing tool that can provide accurate measurements of forest structures and has great potential for monitoring forest changes. This study used the canopy height model (CHM) and canopy cover (CC) products derived from multi-temporal airborne laser scanning (ALS) data to monitor forest changes following the implementation of landscape-scale FT projects. Our approach involved the combination of a pixel-wise thresholding method and an object-of-interest (OBI) segmentation method. We also investigated forest change using normalized difference vegetation index (NDVI) and standardized principal component analysis from multi-temporal high-resolution aerial imagery. The same FT detection routine was then applied to compare the capability of ALS data and aerial imagery for FT detection. Our results demonstrate that the FT detection using ALS-derived CC products produced both the highest total accuracy (93.5%) and kappa coefficient (κ) (0.70), and was more robust in identifying areas with light FTs. The accuracy using ALS-derived CHM products (the total accuracy was 91.6%, and the κ was 0.59) was significantly lower than that using ALS-derived CC, but was still higher than using aerial imagery. Moreover, we also developed and tested a method to recognize the intensity of FTs directly from pre- and post-treatment ALS point clouds.

Impacts of different land management histories on forest change

Many western North American forest types have experienced considerable changes in ecosystem structure, composition, and function as a result of both fire exclusion and timber harvesting. These two influences co-occurred over a large portion of dry forests, making it difficult to know the strength of either one on its own or the potential for an interaction between the two. In this study, we used contemporary remeasurements of a systematic historical forest inventory to investigate forest change in the Sierra Nevada. The historical data opportunistically spanned a significant land management agency boundary, which protected part of the inventory area from timber harvesting. This allowed for a robust comparison of forest change between logged and unlogged areas. In addition, we assessed the effects of recent management activities aimed at forest restoration relative to the same areas historically, and to other areas without recent management. Based on analyses of 22,007 trees (historical, 9,573; contemporary, 12,434), live basal area and tree density significantly increased from 1911 to the early 2000s in both logged and unlogged areas. Both shrub cover and the proportion of live basal area occupied by pine species declined from 1911 to the early 2000s in both areas, but statistical significance was inconsistent. The most notable difference between logged and unlogged areas was in the density of large trees, which declined significantly in logged areas, but was unchanged in unlogged areas. Recent management activities had a varied impact on the forest structure and composition variables analyzed. In general, areas with no recent management activities experienced the greatest change from 1911 to the early 2000s. If approximating historical forest conditions is a land management goal the documented changes in forest structure and composition from 1911 to the early 2000s indicate that active restoration, including fire use and mechanical thinning, is needed in many areas.