Nicholas Skowronski

Simulated impacts of insect defoliation on forest carbon dynamics

Many temperate and boreal forests are subject to insect epidemics. In the eastern US, over 41 million meters squared of tree basal area are thought to be at risk of gypsy moth defoliation. However, the decadal-to-century scale implications of defoliation events for ecosystem carbon dynamics are not well understood. In this study, the effects of defoliation intensity, periodicity and spatial pattern on the carbon cycle are investigated in a set of idealized model simulations. A mechanistic terrestrial biosphere model, ecosystem demography model 2, is driven with observations from a xeric oak‐pine forest located in the New Jersey Pine Barrens. Simulations indicate that net ecosystem productivity (equal to photosynthesis minus respiration) decreases linearly with increasing defoliation intensity. However, because of interactions between defoliation and drought effects, aboveground biomass exhibits a nonlinear decrease with increasing defoliation intensity. The ecosystem responds strongly with both reduced productivity and biomass loss when defoliation periodicity varies from 5 to 15 yr, but exhibits a relatively weak response when defoliation periodicity varies from 15 to 60 yr. Simulations of spatially heterogeneous defoliation resulted in markedly smaller carbon stocks than simulations with spatially homogeneous defoliation. These results show that gypsy moth defoliation has a large effect on oak‐pine forest biomass dynamics, functioning and its capacity to act as a carbon sink.

Simulation and sensitivity analysis of carbon storage and fluxes in the New Jersey Pinelands

A major challenge in modeling the carbon dynamics of vegetation communities is the proper parameterization and calibration of eco-physiological variables that are critical determinants of the ecosystem process-based model behavior. In this study, we improved and calibrated a biochemical process-based WxBGC model by using in situ AmeriFlux eddy covariance tower observations. We simulated carbon dynamics of fire-dominated forests at tower sites and upscaled the tower site-based simulations to regional scale for the New Jersey Pinelands using LANDSAT-ETM land cover and DAYMET climate data. The Extended Fourier Amplitude Sensitivity Test approach was used to assess the higher-order sensitivity of model to critical eco-physiological parameters. The model predictions of CO2 net ecosystem exchange (NEE) and gross ecosystem production (GEP) were in agreement with the eddy covariance measurements at the three tower sites in 2005. However, the model showed poor fit in 2006, grossly overestimating NEE and the ratio of ecosystem respiration to GEP because the model did not reflect the carbon loss caused by severe defoliation related to an outbreak of gypsy moths in that year. The model simulations indicated that wildfire reduced annual NEE in pine/scrub oak forest, while prescribed burning in oak/pine and pine/oak stands led to temporary increase in NEE for a period 1-2 years post burning. The uncertainty and sensitivity of the model carbon simulations were mainly attributable to the 2nd- and higher-order interactions between carbon allocation parameters, specific leaf area and fire mortality intensity.

Decision support tools to improve the effectiveness of hazardous fuel reduction treatments in the New Jersey Pine Barrens

Our goal is to assist the New Jersey Forest Fire Service and federal wildland fire managers in the New Jersey Pine Barrens evaluate where and when to conduct hazardous fuel reduction treatments. We used remotely sensed LIDAR (Light Detection and Ranging System) data and field sampling to estimate fuel loads and consumption during prescribed fire treatments. This information was integrated with data on prescribed fire treatments conducted by the New Jersey Forest Fire Service over the last 15 years to produce and interpret maps of current fuel loads. Forest productivity measurements and models were then used to estimate rates of fuel accumulation through time. We could then calculate return intervals for desired fuel load conditions. Through formal workshops and frequent discussions with state and federal fire managers, our results enhance the ability of these agencies to make key decisions regarding the effectiveness and longevity of hazardous fuels treatments.

Fire management and carbon sequestration in Pine Barren Forests

Prescribed burning is the major viable option that land managers have for reducing hazardous fuels and ensuring the regeneration of fire-dependent species in a cost-effective manner in Pine Barren ecosystems. Fuels management activities are directly linked to carbon (C) storage and rates of C sequestration by forests. To evaluate the effects of prescribed burning on forest C dynamics, we quantified consumption and accumulation of the forest floor and understory vegetation and measured net CO2 exchange in upland forest stands in the New Jersey Pinelands burned with prescribed fires. Prescribed fires released an average of 470 ± 137 g C m−2 from the litter layer and understory, equivalent to approximately 2–3 yr of sequestered C in undisturbed upland forests. Canopy and understory foliage averaged 85% of preburn periods, and CO2 uptake at near-full sunlight conditions averaged 79% of preburn levels during the following growing season. On an annual basis, stands lost C during the year of the burn, but released C was recovered within 2–3 yr. Field measurements and model simulations suggest that continued prescribed burning in upland fire-dependent pine-dominated stands would have little appreciable effect on long-term forest C dynamics at the landscape scale.

Multiscale Simulation of a Prescribed Fire Event in the New Jersey Pine Barrens Using ARPS-CANOPY

Smoke prediction products are one of the tools used by land management personnel for decision making regarding prescribed fires. This study documents the application to a prescribed fire of a smoke prediction system that employs ARPS-CANOPY, a modified version of the Advanced Regional Prediction System (ARPS) model containing a canopy submodel, as the meteorological driver. In this paper, the performance of ARPS-CANOPY in simulating meteorological fields in the vicinity of a low-intensity fire is assessed using flux-tower data collected prior to and during a low-intensity prescribed fire in the New Jersey Pine Barrens in March 2011. A three-dimensional high-resolution plant area density dataset is utilized to define the characteristics of the canopy, and the fire is represented in ARPS-CANOPY as a heat flux to the atmosphere. The standard ARPS model is compared with reanalysis and upper-air data to establish that the model can simulate the observed synoptic-mesoscale and planetary boundary layer features that are salient to this study. ARPS-CANOPY profiles of mean turbulent kinetic energy, wind speed/direction, and temperature exhibit patterns that appear in the flux-tower observations during both the preburn phase of the experiment and the period of time the flux tower experienced perturbed atmospheric conditions due to the impinging fire. Last, the character and source of turbulence in and around the fire line are examined. These results are encouraging for smoke prediction efforts since transport of smoke from low-intensity fires is highly sensitive to the near-surface meteorological conditions and, in particular, turbulent flows.

Structure-level fuel load assessment in the wildland-urban interface: a fusion of airborne laser scanning and spectral remote-sensing methodologies

Large-scale fuel assessments are useful for developing policy aimed at mitigating wildfires in the wildland–urban interface (WUI), while finer-scale characterisation is necessary for maximising the effectiveness of fuel reduction treatments and directing suppression activities. We developed and tested an objective, consistent approach for characterising hazardous fuels in the WUI at the scale of individual structures by integrating aerial photography, airborne laser scanning and cadastral datasets into a hazard assessment framework. This methodology is appropriate for informing zoning policy questions, targeting presuppression planning and fuel reduction treatments, and assisting in prioritising structure defence during suppression operations. Our results show increased variability in fuel loads with decreasing analysis unit area, indicating that fine-scale differences exist that may be omitted owing to spatial averaging when using a coarser, grid-based approach. Analyses using a local parcel database indicate that approximately 75% of the structures in this study have ownership of less than 50% of the 30 m buffer around their building, illustrating the complexity of multiple ownerships when attempting to manage fuels in the WUI. Our results suggest that our remote-sensing approach could augment, and potentially improve, ground-based survey approaches in the WUI.

Database for landscape-scale carbon monitoring sites

This report describes the database used to compile, store, and manage intensive ground-based biometric data collected at research sites in Colorado, Minnesota, New Hampshire, New Jersey, North Carolina, and Wyoming, supporting research activities of the U.S. North American Carbon Program (NACP). This report also provides details of each site, the sampling design and collection standards for biometric measurements, the database design, data summary examples, and the uses of intensive ground-based biometric data. Additional information on location descriptions, data, databases, and documentation may be accessed at http://www.nrs.fs.fed.us/data/lcms.

High spatial resolution burn severity mapping of the New Jersey Pine Barrens with WorldView-3 near-infrared and shortwave infrared imagery

ABSTRACT The WorldView-3 (WV-3) sensor, launched in 2014, is the first high-spatial resolution scanner to acquire imagery in the shortwave infrared (SWIR). A spectral ratio of the SWIR combined with the near-infrared (NIR) can potentially provide an effective differentiation of wildfire burn severity. Previous high spatial resolution sensors were limited to data from the visible and NIR for mapping burn severity, for example using the normalized difference vegetation index (NDVI). Drawing on a study site in the Pine Barrens of New Jersey, USA, we investigate optimal processing methods for analysing WV-3 data, with a focus on the pre-fire minus post-fire differenced normalized burn ratio (dNBR). Although the imagery, originally acquired with a 3.7 m instantaneous field of view, was aggregated to 7.5 m pixels by DigitalGlobe due to current licensing constraints, a slight additional smoothing of the data was nevertheless found to help reduce noise in the multi-temporal dNBR imagery. The highest coefficient of determination (R2) of the regressions of dNBR with the field-based composite burn index was obtained with a dNBR ratio produced with the NIR1 and SWIR6 bands. Only a very small increase in R2 was found when dNBR was calculated using the average of NIR1 and NIR2 for the NIR bands, and SWIR5 to SWIR8 for the SWIR bands. dNBR calculated using SWIR1 as the NIR band produced notably lower R2 values than when either NIR1 or NIR2 were used. Differenced NDVI data was found to produce models with a much lower R2 than dNBR, emphasizing the importance of the shortwave infrared region for monitoring fire severity. High spatial resolution dNBR data from WV-3 can potentially provide valuable information on finer details regarding burn severity patterns than can be obtained from Landsat 30 m data.

Missing Rings, Synchronous Growth, and Ecological Disturbance in a 36-Year Pitch Pine (Pinus rigida) Provenance Study

Provenance studies are an increasingly important analog for understanding how trees adapted to particular climatic conditions might respond to climate change. Dendrochronological analysis can illuminate differences among trees from different seed sources in terms of absolute annual growth and sensitivity to external growth factors. We analyzed annual radial growth of 567 36-year-old pitch pine (Pinus rigida Mill.) trees from 27 seed sources to evaluate their performance in a New Jersey Pine Barrens provenance experiment. Unexpectedly, missing rings were prevalent in most trees, and some years—1992, 1999, and 2006—had a particularly high frequency of missing rings across the plantation. Trees from local seed sources (<55 km away from the plantation) had a significantly smaller percentage of missing rings from 1980–2009 (mean: 5.0%), relative to northernmost and southernmost sources (mean: 9.3% and 7.9%, respectively). Some years with a high frequency of missing rings coincide with outbreaks of defoliating insects or dry growing season conditions. The propensity for missing rings synchronized annual variations in growth across all trees and might have complicated the detection of potential differences in interannual variability among seed sources. Average ring width was significantly larger in seed sources from both the southernmost and warmest origins compared to the northernmost and coldest seed sources in most years. Local seed sources had the highest average radial growth. Adaptation to local environmental conditions and disturbances might have influenced the higher growth rate found in local seed sources. These findings underscore the need to understand the integrative impact of multiple environmental drivers, such as disturbance agents and climate change, on tree growth, forest dynamics, and the carbon cycle.

The Fire Research Program at the Silas Little Experimental Forest, New Lisbon, New Jersey

In this chapter, we document the development and current research efforts of the fire research program at the Silas Little Experimental Forest of the Northern Research Station, USDA Forest Service, in the Pinelands of southern New Jersey. The 450,000-ha (1.1 million-acre) Pinelands National Reserve contains some of the most challenging fuel types for wildland fire managers in the eastern USA. These highly flammable forests occur adjacent to extensive wildland–urban interface and major transportation corridors. We first briefly discuss the ecological setting of upland forests in the Pinelands, highlighting how fire, past industrialization, and other disturbances have shaped the composition and structure of these forests. We then document the establishment of the Experimental Forest and the fire research program. We focus on the career of Dr. Silas Little, a silviculturist with the Northeastern Forest Experiment Station, Upper Darby, PA. Beginning in the late 1930s, his research on prescribed burning practices and silviculture in the Pinelands resulted in cost-effective methods to reduce wildfire risk while promoting the regeneration of commercially important timber species. We discuss how many of the prescribed burning practices developed during these research efforts are now used operationally by the New Jersey Forest Fire Service (NJFFS) and federal wildland fire managers in the Pinelands. Finally, we highlight current and future research efforts at the Experimental Forest.