Forest Study Area Research Articles

Landscape influence on dispersal of yearling male white‐tailed deer

ABSTRACTLandscape features can alter the transfer phase of dispersal and dispersal‐mediated disease transmission and gene flow. The transfer phase is poorly understood, but improved understanding of landscape effects on dispersal distance and direction would allow better prediction and mitigation of disease spread and improved delineation of management zones. To investigate how ecological settings influence dispersal in white‐tailed deer (Odocoileus virginianus), we captured and radio‐collared 409 juvenile male deer from 2 study areas in Wisconsin, USA, one dominated by public forest and another by row‐crop agriculture. Dispersal directions were non‐directed in the heavily forested study area, but there was a southeastern bias in the farmland study area. Individual dispersal distances were not related to forest cover, and study area average and maximum distances differed from expected, based on published relationships between forest cover and population‐average dispersal distance. Roads, rivers, and cities were semipermeable barriers to dispersal, but effects of barriers differed with respect to study area, suggesting that natural and anthropogenic features influence dispersal‐mediated disease transmission and gene flow. Our results suggest that dispersal models should consider movement barriers in more developed landscapes, and barriers can also be used to inform designation of biologically meaningful management units. © 2017 The Wildlife Society.

The First Estimates of Marbled Cat Pardofelis marmorata Population Density from Bornean Primary and Selectively Logged Forest.

The marbled cat Pardofelis marmorata is a poorly known wild cat that has a broad distribution across much of the Indomalayan ecorealm. This felid is thought to exist at low population densities throughout its range, yet no estimates of its abundance exist, hampering assessment of its conservation status. To investigate the distribution and abundance of marbled cats we conducted intensive, felid-focused camera trap surveys of eight forest areas and two oil palm plantations in Sabah, Malaysian Borneo. Study sites were broadly representative of the range of habitat types and the gradient of anthropogenic disturbance and fragmentation present in contemporary Sabah. We recorded marbled cats from all forest study areas apart from a small, relatively isolated forest patch, although photographic detection frequency varied greatly between areas. No marbled cats were recorded within the plantations, but a single individual was recorded walking along the forest/plantation boundary. We collected sufficient numbers of marbled cat photographic captures at three study areas to permit density estimation based on spatially explicit capture-recapture analyses. Estimates of population density from the primary, lowland Danum Valley Conservation Area and primary upland, Tawau Hills Park, were 19.57 (SD: 8.36) and 7.10 (SD: 1.90) individuals per 100 km2, respectively, and the selectively logged, lowland Tabin Wildlife Reserve yielded an estimated density of 10.45 (SD: 3.38) individuals per 100 km2. The low detection frequencies recorded in our other survey sites and from published studies elsewhere in its range, and the absence of previous density estimates for this felid suggest that our density estimates may be from the higher end of their abundance spectrum. We provide recommendations for future marbled cat survey approaches.

Micro-scale spatial correlation of magnetic susceptibility in soil profile in forest located in an industrial area

So far, studies concerning the analyses of the soil magnetic susceptibility in the soil profile have been usually making use of classic statistics. The number of papers where spatial correlations of magnetic susceptibility were analyzed is still limited. In particular, the micro-scale spatial correlations have been rarely analyzed.The goal of this study was to analyze microscale spatial correlations of magnetic susceptibility in the soil profiles collected in an old park, located in the Upper Silesian Industrial Region. In particular, the micro-correlations of κ were investigated by using measurements of soil κ values made with a SM400 device. The use of this device was necessary because the spatial resolution of other devices like Bartington MS2C or MS2H was too low. The spatial correlations of soil κ were investigated by calculating directional variograms along the soil profile and then modeling them. Analyses of spatial correlations were calculated separately for the topsoil and subsoil layers.The spatial correlations of the soil magnetic susceptibility in soil profiles collected in the forested study area were characterized by the Gaussian model with no nugget effect. The linear regression showed clear dependence between the thickness of the topsoil and the range of correlation of the soil magnetic susceptibility in the soil profile.

Use of Landsat and Corona data for mapping forest cover change from the mid-1960s to 2000s: Case studies from the Eastern United States and Central Brazil

Land-cover change detection using satellite remote sensing is largely confined to the era of Landsat satellites, from 1972 to present. However, the Corona, Argon, and Lanyard intelligence satellites operated by the U.S. government between 1960 and 1972 have the potential to provide an important extension of the long-term record of Earth’s land surface. Recently declassified, the archive of images recorded by these satellites contains hundreds of thousands of photographs, many of which have very high ground resolution- 6–9 ft (1.8–2.7m) even by today’s standards. This paper demonstrates methods for extending the span of forest-cover change analysis from the Landsat-5 and -7 era (1984 to present) to the previous era covered by the Corona archive in two study areas: one area covered predominantly by urban and sub-urban land uses in the eastern US and another area by tropical forest in central Brazil. We describe co-registration of Corona and Landsat images, extraction of texture features from Corona images, classification of Corona and Landsat images, and post-classification change detection based on the resulting thematic dataset. Second-order polynomial transformation of Corona images yielded geometric accuracy relative to Landsat-7 of 18.24m for the urban area and 29.35m for the tropical forest study area, generally deemed adequate for pixel-based change detection at Landsat resolution. Classification accuracies were approximately 95% and 96% for forest/non-forest discrimination for the temperate urban and tropical forest study areas, respectively. Texture within 7×7- to 9×9-pixel (∼13.0–16.5m) neighborhoods and within 11×11-pixel (∼30m) neighborhoods were the most informative metrics for forest classification in Corona images in the temperate and tropical study areas, respectively. The trajectory of change from the 1960s to 2000s differed between the two study areas: the average annual forest loss rate in the urban area doubled from 0.68% to 1.9% from the 1960s to the mid-1980s and then decreased during the following decade. In contrast, deforestation in the Brazilian study area continued at a slightly increased pace between the 1960s and 1990s at annual loss rate of 0.62–0.79% and quickly slowed down afterward. This study demonstrates the strong potential of declassified Corona images for detecting historical forest changes in these study regions and suggests increased utility for retrieving a wide range of land cover histories around the world.

Use of an ungulate‐specific feed structure as a potential tool for controlling feral goats in Australian forest ecosystems

SummaryThe feral Goat (Capra hircus) has successfully exploited a range of landscapes around the world with occurrences of overabundance resulting in significant damage to ecological values. In forested ecosystems in Australia, there are currently limited means to control the species when compared to the range of management techniques available for other pest animals. To redress this deficiency, we designed a feed structure combined with commercially available salt blocks to attract goats to set locations in a forested study area. Structures that exploited differences in the pedal morphology (foot size and shape) of native herbivores (kangaroos and wallabies) and ungulates (feral goats and deer) were found to be highly target‐specific, with feral goats freely able to access salt blocks, whilst nontarget native species were effectively excluded. Other introduced ungulate species, Fallow Deer (Dama dama) and Red Deer (Cervus elaphus), successfully accessed salt blocks in feed structures but at a considerably lower rate than feral goats. The capacity to present a range of bait types within a target‐specific feed structure, once matched with a humane toxicant, could provide land managers with an additional cost‐effective lethal control tool for future management of feral ungulates, particularly goats.

Diet of Mexican Spotted Owls in Utah and Arizona

Mexican Spotted Owls (Strix occidentalis lucida) occupy forest-dominated environments but also inhabit rocky canyonlands. I studied the owls' diet in canyon habitats in southern Utah and northern Arizona (1991–2007), and in mixed-conifer forest in the Rincon Mountains of southeast Arizona (1996–1997). I identified 3,315 prey items in regurgitated pellets from 38 pairs of owls in canyon habitat, and 383 prey items from 5 pairs in the Rincon Mountains. In canyons and forests, vertebrates dominated owl diets (97–99% of total prey biomass) with mammals accounting for 91–92% of prey biomass. In canyons, mammalian prey was primarily woodrats (Neotoma spp., 79% biomass), followed by white-footed mice (Peromyscus spp., 11%), and cottontail rabbits (Sylvilagus spp., 5%). In forest habitat, woodrats comprised 54% of biomass, followed by Botta's pocket gophers (Thomomys bottae, 13%), and cottontail rabbits (11%). For nine owl territories in three canyon regions in Utah, diets varied among the owl pairs with contribution to total prey biomass by woodrats ranging from 65–91%, typically followed by white-footed mice ranging from 13–19%. In both canyon and forest study areas, a variety of prey were consumed in addition to murids, including rabbits, pocket gophers, sciurids (Tamias spp.), heteromyids (e.g., Perognathus spp.), various bats (Vespertilionidae), shrews (Sorex spp.), small passerine birds, and numerous arthropods.

Analysing structural diversity in two temperate forests in northeastern China

This contribution presents an analysis of the structural diversity in two temperate forest ecosystems in northeastern China, based on two large contiguous observational studies covering an area of 5.2ha (260×200m2) each. The total number of living trees in the conifer and broad-leaved forest (CBF) study area is 2927 per ha, comprising 37 species and 21 genera. The old growth forest (OGF) study area has 2276 trees per ha, including 22 species and 13 genera. Tree species are classified according to their community status as mature and immature canopy, subcanopy and shrub. A clustering process based on two distinct communities of the bivariate dbh/height distributions is used to differentiate between mature and immature canopy species. Numerical analysis is based on these four distinct cohorts. Despite advances in remote sensing, mapped tree data in large observation windows are very rare. Thus, we are able to use methods for analysing forest structure which are suitable for both, unmapped and mapped data. The two data sets are unique in that all (approximately) 27,000 tree heights are available. Accordingly, it was possible to fit bimodal height distributions and bivariate mixed dbh/height distributions to almost all individual species that were represented by sufficiently large numbers. Methods of second order statistics (SOC), including marked point statistics as well as nearest neighbor statistics (NNS) based on nearest neighbourhood structure units are also presented, including bivariate mixtures of the NNS attributes “mingling” and “dominance”. Mark correlations were investigated for several marks, including diameters, heights and nearest neighbor statistics. Finally, we discuss the most important results and motivate the need for detailed assessments in large contiguous field plots. The literature on spatial statistics is often rather technical, and there is relatively little exchange between mathematicians developing the theory and ecologists who have interesting data from observational studies, such as presented in this contribution.

Natural forest floor clearings around trees in Jeffrey pine forests reduce tree damage and mortality following wildfire

In the western United States, trees in pine-dominated forests historically characterized by frequent, low severity wildfires often support deep litter and duff accumulations due to the fire exclusion policies of the last century. These accumulations at the bases of trees can smolder for long periods of time after the passage of fire, which can result in high temperatures, cambial injury, and subsequent tree mortality. As a result, prescribed fire prescriptions often call for the manual removal of litter and duff from the bases of large trees by raking or other means before fire is applied. Here we report on the presence of naturally formed, circular clearings in the soil surface litter layer that occur around the bases of tree boles in seasonally dry forests dominated by Pinus jeffreyi (Jeffrey pine) in eastern California and Baja California (along the eastern edge of the North American Mediterranean-climate zone). We show that such clearings significantly reduce fire severity and tree mortality in surface fires. In the Lake Tahoe Basin (LTB) study area, Jeffrey pine individuals surrounded by clearings experienced much lower bole char heights, and were 1/3 as likely to support crown torching as individuals lacking the clearings; mortality of Jeffrey pine lacking clearings was more than five times higher than individuals surrounded by clearings. Clearings also reduced mortality in incense cedar and white fir. Data from both the LTB and Inyo National Forest (INF) study areas show that clearings are larger and much more common in forests that have recently burned at low severity. In both locations, natural clearings around trees were about four times more common, and existing clearings about three times wider, in recently burned versus long unburned (>60years) sites. Logistic regression models show that clearing size, specifically the percentage of tree bole surrounded by a clearing, is an important predictor of Jeffrey pine survivorship in low to moderate severity fires, but clearing measures have never been included in previously published assessments of tree survival. We suggest that these previously unreported clearings are important features of Jeffrey pine and related semiarid forests and we recommend that more in-depth studies be made of their occurrence, formation, and ecological relationships.

Bioclimatic Extremes Drive Forest Mortality in Southwest, Western Australia

Extreme and persistent reductions in annual precipitation and an increase in the mean diurnal temperature range have resulted in patch scale forest mortality following the summer of 2010–2011 within the Forest study area near Perth, Western Australia. The impacts of 20 bioclimatic indicators derived from temperature, precipitation and of actual and potential evapotranspiration are quantified. We found that spatially aggregated seasonal climatologies across the study area show 2011 with an annual mean of 17.7 °C (± 5.3 °C) was 1.1 °C warmer than the mean over recent decades (1981–2011,- 16.6 °C ± 4.6 °C) and the mean has been increasing over the last decade. Compared to the same period, 2010–2011 summer maximum temperatures were 1.4 °C (31.6 °C ± 2.0 °C) higher and the annual mean diurnal temperature range (Tmax−Tmin) was 1.6 °C higher (14.7 °C ± 0.5 °C). In 2009, the year before the forest mortality began, annual precipitation across the study area was 69% less (301 mm ± 38 mm) than the mean of 1981–2010 (907 mm ± 69 mm). Using Système Pour l'Observation de la Terre mission 5 (SPOT-5) satellite imagery captured after the summer of 2010–2011 we map a broad scale forest mortality event across the Forested study area. This satellite-climatology based methodology provides a means of monitoring and mapping similar forest mortality events- a critical contribution to our understanding the dynamical bioclimatic drivers of forest mortality events.

Use of Airborne Gamma Radiometrics to Infer Soil Properties for a Forested Area in British Columbia, Canada

We obtained radiometric data from a public-domain archive maintained by Natural Resources Canada and processed them to produce a ternary image for a portion of the Cariboo region. A field program was used to evaluate what information could be reliably inferred from the available data. This initial investigation confirmed that the radiometrics for this area exhibited consistent and useful patterns to interpret the lithology, mineralogy, depth, and moisture status of the surficial materials. Different colour patterns in the ternary image correlated well with different compositions of the various tills. We noted a clear association between higher values of radioactive emission and more recently deposited aeolian, alluvial, and glaciofluvial sediments that contained higher concentrations of relatively unweathered minerals. We observed a clear pattern of lower emission from wetlands and areas of wet soil. Airborne radiometrics, even at 500-m line spacing, provided invaluable and precise information—not otherwise obtainable—for mapping or modelling spatial variation in properties of the surficial material within the forested study area in British Columbia. We recommend further investigations to develop operational procedures for the use of such data in mapping surficial materials.

Non-invasive genetic approaches for estimation of ungulate population size: a study on roe deer (Capreolus capreolus) based on faeces

Estimating population size is particularly difficult for animal species living in concealing habitats with dense vegetation. This is the case for roe deer as for many other ungulates. Our objective was to develop a non–invasive genetic capture–mark–recapture approach based on roe deer faeces collected along transects. In a pilot study, we collected 1,790 roe deer faeces during five sampling days in a forested study area in south western Germany. We extracted DNA from 410 of these samples and carried out microsatellite analysis using seven dinucleotide markers. The analyses resulted in 328 useable consensus genotypes which were assigned to 174 individuals. The population size estimated using a Bayesian approach was 94 (82–111) male and 136 (121–156) female roe deer. Our study shows that non–invasive genetic methods are a valuable management tool for roe deer.

Carbon storage, timber production, and biodiversity: comparing ecosystem services with multi‐criteria decision analysis

Increasingly, land managers seek ways to manage forests for multiple ecosystem services and functions, yet considerable challenges exist in comparing disparate services and balancing trade-offs among them. We applied multi-criteria decision analysis (MCDA) and forest simulation models to simultaneously consider three objectives: (1) storing carbon, (2) producing timber and wood products, and (3) sustaining biodiversity. We used the Forest Vegetation Simulator (FVS) applied to 42 northern hardwood sites to simulate forest development over 100 years and to estimate carbon storage and timber production. We estimated biodiversity implications with occupancy models for 51 terrestrial bird species that were linked to FVS outputs. We simulated four alternative management prescriptions that spanned a range of harvesting intensities and forest structure retention. We found that silvicultural approaches emphasizing less frequent harvesting and greater structural retention could be expected to achieve the greatest net carbon storage but also produce less timber. More intensive prescriptions would enhance biodiversity because positive responses of early successional species exceeded negative responses of late successional species within the heavily forested study area. The combinations of weights assigned to objectives had a large influence on which prescriptions were scored as optimal. Overall, we found that a diversity of silvicultural approaches is likely to be preferable to any single approach, emphasizing the need for landscape-scale management to provide a full range of ecosystem goods and services. Our analytical framework that combined MCDA with forest simulation modeling was a powerful tool in understanding trade-offs among management objectives and how they can be simultaneously accommodated.

Effects of single-tree selection harvesting on Rose-breasted Grosbeak (Pheucticus leudovicianus) demography in a northern hardwood forest

Single-tree selection harvesting is frequently used in the tolerant hardwood forests of North America, but little is known about how it affects the reproductive success of migratory songbirds. Many songbirds that breed in tolerant hardwoods, including the Rose-breasted Grosbeak (Pheucticus leudovicianus) are experiencing population declines across their breeding ranges. We studied habitat characteristics and reproductive success of Rose-breasted Grosbeaks in stands harvested 0–5, 16–20, and 21–25years previously and in reference stands (un-harvested for >50years) in Algonquin Provincial Park, Ontario, Canada (n=3 per age class). Recently harvested stands had higher cover from regenerative growth and lower sapling, understory, and canopy cover than other treatments, whereas reference stands had higher basal area and sapling cover. Pairing success was significantly lower in the reference stands than in all other post-harvest treatments, and the number of fledglings per successful nest was significantly lower in the reference stands than in the 0–5years post-harvest stands. Density and population growth rate were significantly positively correlated, suggesting that density may be an adequate indicator of habitat quality for Rose-breasted Grosbeaks in forested landscapes. Older males were present at higher densities, initiated their nests earlier, and produced significantly more fledglings per nest than younger males in all treatments. Habitat characteristics did not differ significantly between nests with second-year and after-second-year males, suggesting greater reproductive output of older males was likely due to experience rather than monopolization of better quality territories. We concluded that single-tree selection harvesting was beneficial to Rose-breasted Grosbeaks in our predominantly forested study area. Population growth rates were below replacement levels in the 21–25 years post-harvest and reference treatments, but populations were stable in the younger regenerating stands. Thus, in a continuously forested landscape this species’ declines are probably not attributable to single-tree selection harvesting.

Canopy radiation transmission for an energy balance snowmelt model

To better estimate the radiation energy within and beneath the forest canopy for energy balance snowmelt models, a two stream radiation transfer model that explicitly accounts for canopy scattering, absorption and reflection was developed. Upward and downward radiation streams represented by two differential equations using a single path assumption were solved analytically to approximate the radiation transmitted through or reflected by the canopy with multiple scattering. This approximation results in an exponential decrease of radiation intensity with canopy depth, similar to Beer's law for a deep canopy. The solution for a finite canopy is obtained by applying recursive superposition of this two stream single path deep canopy solution. This solution enhances capability for modeling energy balance processes of the snowpack in forested environments, which is important when quantifying the sensitivity of hydrologic response to input changes using physically based modeling. The radiation model was included in a distributed energy balance snowmelt model and results compared with observations made in three different vegetation classes (open, coniferous forest, deciduous forest) at a forest study area in the Rocky Mountains in Utah, USA. The model was able to capture the sensitivity of beneath canopy net radiation and snowmelt to vegetation class consistent with observations and achieve satisfactory predictions of snowmelt from forested areas from parsimonious practically available information. The model is simple enough to be applied in a spatially distributed way, but still relatively rigorously and explicitly represent variability in canopy properties in the simulation of snowmelt over a watershed.

Quantifying bias in pattern indices extracted from spatially offset landscape samples

Modern ecological models often account for the influence of the surrounding environment by using landscape pattern indices (LPIs) as measures of landscape structure. Ideally, the landscape samples from which these LPIs are extracted should be centered on the locations where the response variable was measured. However, in situations where this is not possible due to a lack of adequate full-coverage landcover data, the question arises as to what degree this circumstance creates a bias in the value of the LPIs, thereby obscuring their relation with the response variable. To address this question, we extracted four representative LPIs from 30 rectangular (3 × 6 km) landscape samples evenly distributed across a 10 000 km2 boreal forest study area. These rectangles were subjected to systematic displacements across a range of distances (0.5 to 2.5 km) and directions, after which we recomputed the LPIs. We found that a 1 km spatial offset led to an average of 15% deviation of original LPI values. Unfortunately, as the offset increased, the range of resulting deviations also widened, making it difficult to predict this effect. Our findings fill a gap in the literature on landscape pattern analysis and suggest that researchers should avoid LPIs extracted from spatially offset landscape samples.

High Apparent Annual Survival and Stable Territory Dynamics of Chestnut-Backed Antbird (Myrmeciza exsul) in a Large Costa Rican Rain Forest Preserve

Antbirds (Thamnophilidae) are a diverse component of neotropical forest avifaunas, and are particularly vulnerable to population declines and extirpations in fragmented landscapes. We lack estimates of apparent survival and dispersal for the majority of species, despite their value in effectively managing populations of understory birds. We studied a population of Chestnut-backed Antbird (Myrmeciza exsul) from 2004 to 2009 in a large rain forest preserve in northern Costa Rica to generate estimates of apparent annual survival (ϕ), and breeding dispersal (i.e., movement from one breeding territory to another) in continuous forest. Estimates of ϕ (± SE) of adults based on weighted model averages were high (males: 0.794 ± 0.037; females: 0.798 ± 0.050) compared to independent juveniles (males: 0.629 ± 0.159; females: 0.629 ± 0.168). Detection (recapture/reobservation) probabilities (p) were higher for males (adults: 0.916 ± 0.034; juveniles: 0.915 ± 0.049) than for females (adults: 0.544 ± 0.104; juveniles: 0.540 ± 0.115). Overall annual turnover (disappearing from the study area territory switching) was comparable to other antbirds (∼32%). Territory switching was rare, and generally limited to short movements to adjacent or nearby territories (mean distance moved = 372 m, range = 145–840 m, n = 9). Our results suggest Chestnut-backed Antbirds: (1) have relatively high adult annual survival, and (2) have limited breeding dispersal, even in a large, forested study area.

Phenological change detection while accounting for abrupt and gradual trends in satellite image time series

A challenge in phenology studies is understanding what constitutes phenological change amidst background variation. The majority of phenological studies have focused on extracting critical points in the seasonal growth cycle, without exploiting the full temporal detail. The high degree of phenological variability between years demonstrates the necessity of distinguishing long-term phenological change from temporal variability. Here, we demonstrate the phenological change detection ability of a method for detecting change within time series. BFAST, Breaks For Additive Seasonal and Trend, integrates the decomposition of time series into trend, seasonal, and remainder components with methods for detecting change. We tested BFAST by simulating 16-day NDVI time series with varying amounts of seasonal amplitude and noise, containing abrupt disturbances (e.g. fires) and long-term phenological changes. This revealed that the method is able to detect the timing of phenological changes within time series while accounting for abrupt disturbances and noise. Results showed that the phenological change detection is influenced by the signal-to-noise ratio of the time series. Between different land cover types the seasonal amplitude varies and determines the signal-to-noise ratio, and as such the capacity to differentiate phenological changes from noise. Application of the method on 16-day NDVI MODIS images from 2000 until 2009 for a forested study area in south eastern Australia confirmed these results. It was shown that a minimum seasonal amplitude of 0.1 NDVI is required to detect phenological change within cleaned MODIS NDVI time series using the quality flags. BFAST identifies phenological change independent of phenological metrics by exploiting the full time series. The method is globally applicable since it analyzes each pixel individually without the setting of thresholds to detect change within a time series. Long-term phenological changes can be detected within NDVI time series of a large range of land cover types (e.g. grassland, woodlands and deciduous forests) having a seasonal amplitude larger than the noise level. The method can be applied to any time series data and it is not necessarily limited to NDVI.

Using mixed estimation for combining airborne laser scanning data in two different forest areas

Airborne laser scanning (ALS) data have become the most accurate remote sensing technology for forest inventories. When planning new inventories the costs of fieldwork could be reduced if datasets of old inventory areas are effectively reused in the new area. The aim of this study was to apply mixed estimation using a combination of existing and new field datasets in area-based approach. Additionally, combining datasets with mixed estimation was compared with constructing new local models with smaller datasets. The two forest study areas were in Juuka and Matalansalo, which are located about 120 km apart in eastern Finland. ALS-based regression models were constructed using datasets of Matalansalo (472 reference plots) and Juuka (10–212 reference plots). Models were developed for the basal area median tree diameter and height, mean tree height, stem number, basal area and volume. The work was based on a simulation approach which involved five methods for approximating the regression coefficients. The first method merged the datasets using ordinary least squares (OLS) regression models, whereas the second and third methods combined datasets using mixed estimation on different weighting principles, and the final two estimated local models with predetermined and new independent variables. The results indicate that mixed estimation can improve the accuracy of derived stand variables compared with basic OLS models. Additionally, a sample of 40–50 plots was enough to build local models for basal area and volume and produce at least the equal accuracy of results than any other methods in this study.

Detecting trend and seasonal changes in satellite image time series

A wealth of remotely sensed image time series covering large areas is now available to the earth science community. Change detection methods are often not capable of detecting land cover changes within time series that are heavily influenced by seasonal climatic variations. Detecting change within the trend and seasonal components of time series enables the classification of different types of changes. Changes occurring in the trend component often indicate disturbances (e.g. fires, insect attacks), while changes occurring in the seasonal component indicate phenological changes (e.g. change in land cover type). A generic change detection approach is proposed for time series by detecting and characterizing Breaks For Additive Seasonal and Trend (BFAST). BFAST integrates the decomposition of time series into trend, seasonal, and remainder components with methods for detecting change within time series. BFAST iteratively estimates the time and number of changes, and characterizes change by its magnitude and direction. We tested BFAST by simulating 16-day Normalized Difference Vegetation Index (NDVI) time series with varying amounts of seasonality and noise, and by adding abrupt changes at different times and magnitudes. This revealed that BFAST can robustly detect change with different magnitudes (> 0.1 NDVI) within time series with different noise levels (0.01–0.07 σ) and seasonal amplitudes (0.1–0.5 NDVI). Additionally, BFAST was applied to 16-day NDVI Moderate Resolution Imaging Spectroradiometer (MODIS) composites for a forested study area in south eastern Australia. This showed that BFAST is able to detect and characterize spatial and temporal changes in a forested landscape. BFAST is not specific to a particular data type and can be applied to time series without the need to normalize for land cover types, select a reference period, or change trajectory. The method can be integrated within monitoring frameworks and used as an alarm system to flag when and where changes occur.

Uncertainty in detecting climate change impact on the projected yield of black spruce ( Picea mariana)

The empirical growth and yield (G&Y) curves used in most timber supply models assume that growth conditions are invariable over time, which may not be correct given the projected future climate. However, errors in G&Y models can be quite large, and we therefore wanted to know the probability of detecting climate change-induced growth anomalies as a departure from current G&Y predictions. The work was carried out in a boreal forest study area in Eastern Canada, where Picea mariana Mill. BSP (black spruce) is the dominant species. Climate change effects were incorporated into G&Y predictions as correction factors obtained from process-based simulations of growth using current or projected climate. Uncertainty in G&Y projections was quantified through the inclusion of sampling and model errors in a bootstrap re-sampling scheme that yielded a percentile distribution of possible differences between G&Y curves that included or did not include climate change effects. Results yielded an average projected increase in productivity of 29% under future climate conditions for the black spruce strata in the study area. The probability of the climate change-modified G&Y predictions being significantly different from the current G&Y projections is 75% when considering the sampling error alone, and of 67% when both the sampling and modelling errors are included. Although incomplete in terms of what sources of error have been included, this study demonstrates the type of information that can be generated on the propagation of uncertainty in G&Y projections and, ultimately, on timber supply.