Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Long-term monitoring across elevational gradients to assess ecological hypothesis : a description of standardized sampling methods in oceanic islands and first results

We are launching a long-term study to characterize the biodiversity at different elevations in several Azorean Islands. Our aim is to use the Azores as a model archipelago to answer the fundamental question of what generates and maintains the global spatial heterogeneity of diversity in islands and to be able to understand the dynamics of change across time. An extensive, standardized sampling protocol was applied in most of the remnant forest fragments of five Azorean Islands. Fieldwork followed BRYOLAT methodology for the collection of bryophytes, ferns and other vascular plant species. A modified version of the BALA protocol was used for arthropods. A total of 70 plots (10 m x 10 m) are already established in five islands (Flores, Pico, São Jorge, Terceira and São Miguel), all respecting an elevation step of 200 m, resulting in 24 stations examined in Pico, 12 in Terceira, 10 in Flores, 12 in São Miguel and 12 in São Jorge. The first results regarding the vascular plants inventory include 138 vascular species including taxa from Lycopodiophyta (N=2), Pteridophyta (N=27), Pinophyta (N=2) and Magnoliophyta (N=107). In this contribution we also present the main research question for the next six years within the 2020 Horizon.

Efficiency of sampling methods and effort to assess arthropod diversity in Azorean native forests

The BALA project (Biodiversity of Arthropods of Laurisilva of the Azores) is a research initiative to quantify the spatial distribution of arthropod biodiversity in native forests of the Azores archipelago. Arthropods were collected using a combination of two techniques, targeting epigean (ground dwelling) and canopy (arboreal) arthropods: pitfall traps (with Turquin and Ethylene solutions) and beating samples (using the three most dominant plant species). A total of 109 transects distributed amongst 18 forest fragments in seven of the nine Azorean islands were used in this study. The performance of alternative sampling methods and effort were tested. No significant differences were found in the accumulated number of species captured whether an alternative method was used or whether another transect with similar effort was established in another location within the same fragment. A combination of Ethylene and Turquin traps captured more species per individual, Turquin and beating captured more species per sample, and Turquin captured more species per unit time. An optimization exercise was performed and we found that the protocol applied during recent years is very close to optimal, allowing its future replication with confidence. The minimum combinations of sampling effort and methods, in order to monitor or to inventory diversity, taking into account different proportions of sample completeness are discussed.

Accuracy and efficiency evaluation of point-centered quarter method variations for vegetation sampling in an araucaria forest

In order to verify Point-Centered Quarter Method (PCQM) accuracy and efficiency, using different numbers of individuals by per sampled area, in 28 quarter points in an Araucaria forest, southern Paraná, Brazil. Three variations of the PCQM were used for comparison associated to the number of sampled individual trees: standard PCQM (SD-PCQM), with four sampled individuals by point (one in each quarter), second measured (VAR1-PCQM), with eight sampled individuals by point (two in each quarter), and third measuring (VAR2-PCQM), with 16 sampled individuals by points (four in each quarter). Thirty-one species of trees were recorded by the SD-PCQM method, 48 by VAR1-PCQM and 60 by VAR2-PCQM. The level of exhaustiveness of the vegetation census and diversity index showed an increasing number of individuals considered by quadrant, indicating that VAR2-PCQM was the most accurate and efficient method when compared with VAR1-PCQM and SD-PCQM.

Comparison of Neck Skin Excision and Whole Carcass Rinse Sampling Methods for Microbiological Evaluation of Broiler Carcasses before and after Immersion Chilling

Sampling protocols for detecting Salmonella on poultry differ among various countries. In the United States, the U.S. Department of Agriculture Food Safety and Inspection Service dictates that whole broiler carcasses should be rinsed with 400 ml of 1% buffered peptone water, whereas in the European Union 25-g samples composed of neck skin from three carcasses are evaluated. The purpose of this study was to evaluate a whole carcass rinse (WCR) and a neck skin excision (NS) procedure for Salmonella and Escherichia coli isolation from the same broiler carcass. Carcasses were obtained from three broiler processing plants. The skin around the neck area was aseptically removed and bagged separately from the carcass, and microbiological analysis was performed. The corresponding carcass was bagged and a WCR sample was evaluated. No significant difference (alpha <= 0.05) in Salmonella prevalence was found between the samples processed by the two methods, but both procedures produced many false-negative Salmonella results. Prechill, 37% (66 carcasses), 28% (50 carcasses), and 51% (91 carcasses) of the 180 carcasses examined were positive for Salmonella by WCR, NS, and both procedures combined, respectively. Postchill, 3% (5 carcasses), 7% (12 carcasses), and 10% (17 carcasses) of the 177 carcasses examined were positive for Salmonella by the WCR, NS, and combination of both procedures, respectively. Prechill, E. coli plus coliform counts were 3.0 and 2.6 log CFU/ml by the WCR and NS methods, respectively. Postchill. E. coli plus coliform counts were 1.7 and 1.4 log CFU/ml by the WCR and NS methods, respectively.

Bats from Fazenda Intervales, Southeastern Brazil: species account and comparison between different sampling methods

Assessing the composition of an area's bat fauna is typically accomplished by using captures or by monitoring echolocation calls with bat detectors. The two methods may not provide the same data regarding species composition. Mist nets and harp traps may be biased towards sampling low flying species, and bat detectors biased towards detecting high intensity echolocators. A comparison of the bat fauna of Fazenda Intervales, southeastern Brazil, as revealed by mist nets and harp trap captures, checking roosts and by monitoring echolocation calls of flying bats illustrates this point. A total of 17 species of bats was sampled. Fourteen bat species were captured and the echolocation calls of 12 species were recorded, three of them not revealed by mist nets or harp traps. The different sampling methods provided different pictures of the bat fauna. Phyllostomid bats dominated the catches in mist nets, but in the field their echolocation calls were never detected. No single sampling approach provided a complete assessment of the bat fauna in the study area. In general, bats producing low intensity echolocation calls, such as phyllostomids, are more easily assessed by netting, and bats producing high intensity echolocation calls are better surveyed by bat detectors. The results demonstrate that a combined and varied approach to sampling is required for a complete assessment of the bat fauna of an area.

Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment

Conservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas.

Circulating matrix metalloproteinase 9 levels in relation to sampling methods, femoral and carotid atherosclerosis.

OBJECTIVES To examine whether circulating levels of matrix metalloproteinase 9 (MMP-9) were associated with ultrasound-assessed intima-media thickness (IMT) and echolucent plaques in the carotid and femoral arteries. To examine preanalytical sources of variability in MMP-9 concentrations related to sampling procedures. SUBJECTS AND DESIGN Plasma and serum MMP-9 levels were compared with ultrasound assessed measures of femoral and carotid atherosclerosis, in a cross-sectional study of 61-year-old men (n = 473). Preanalytical sources of variability in MMP-9 levels were examined in 10 healthy subjects. Main outcome measures were circulating levels of MMP-9 in serum and plasma, IMT of the carotid and femoral arteries, and plaque status based on size and echolucency. SETTING Research unit at university hospital. RESULTS Plasma concentrations of total and active MMP-9 were associated with femoral artery IMT independently of traditional cardiovascular risk factors, and were higher in subjects with moderate to large femoral plaques. Plasma MMP-9 concentration was higher in men with echolucent femoral plaques (P = 0.006) compared with subjects without femoral plaques. No similar associations were found for carotid plaques. MMP-9 concentrations were higher in serum than in plasma, and higher when sampling was performed with Vacutainer than with syringe. MMP-9 levels in serum were more strongly associated with peripheral neutrophil count compared with MMP-9 levels in plasma. CONCLUSIONS Plasma MMP-9 levels were associated with atherosclerosis in the femoral artery, and total MMP-9 concentration was higher in men with echolucent femoral plaques. The choice of sample material and sampling method affect the measurements of circulating MMP-9 levels.

Comparison of Airborne Laser Scanning Methods for Estimating Forest Structure Indicators Based on Lorenz Curves

The purpose of this study was to compare a number of state-of-the-art methods in airborne laser scan- ning (ALS) remote sensing with regards to their capacity to describe tree size inequality and other indi- cators related to forest structure. The indicators chosen were based on the analysis of the Lorenz curve: Gini coefficient ( GC ), Lorenz asymmetry ( LA ), the proportions of basal area ( BALM ) and stem density ( NSLM ) stocked above the mean quadratic diameter. Each method belonged to one of these estimation strategies: (A) estimating indicators directly; (B) estimating the whole Lorenz curve; or (C) estimating a complete tree list. Across these strategies, the most popular statistical methods for area-based approach (ABA) were used: regression, random forest (RF), and nearest neighbour imputation. The latter included distance metrics based on either RF (NN–RF) or most similar neighbour (MSN). In the case of tree list esti- mation, methods based on individual tree detection (ITD) and semi-ITD, both combined with MSN impu- tation, were also studied. The most accurate method was direct estimation by best subset regression, which obtained the lowest cross-validated coefficients of variation of their root mean squared error CV(RMSE) for most indicators: GC (16.80%), LA (8.76%), BALM (8.80%) and NSLM (14.60%). Similar figures [CV(RMSE) 16.09%, 10.49%, 10.93% and 14.07%, respectively] were obtained by MSN imputation of tree lists by ABA, a method that also showed a number of additional advantages, such as better distributing the residual variance along the predictive range. In light of our results, ITD approaches may be clearly inferior to ABA with regards to describing the structural properties related to tree size inequality in for- ested areas.

Comparison between splenic and lymph node aspirations as sampling methods for the parasitological detection of Leishmania chagasi infection in dogs

The sensitivities of spleen and lymph node cultures for the diagnosis of canine visceral leishmaniasis were compared in 64 anti-Leishmania antibody positive dogs from an endemic area in Brazil. The sensitivity of spleen cultures for Leishmania detection was 97.9%; in lymph node cultures it was 25%. Positive spleen culture was more frequent (p = 0.048, Fisher's exact probability test) in symptomatic (28 out of 33 animals) than in asymptomatic animals (19 out of 31 animals). These results support the use of spleen instead of lymph node aspiration as the choice method for the parasitological diagnosis of the infection.

Comparative abundance and diversity of Dryininae (Hymenoptera, Dryinidae) in three savannah phytophysiognomies in southeastern Brazil, under three sampling methods

Comparative abundance and diversity of Dryininae (Hymenoptera, Dryinidae) in three savannah phytophysiognomies in southeastern Brazil, under three sampling methods. This study aimed to assess the abundance and diversity of Dryininae in riparian vegetation, Brazilian savannah, and savannah woodland vegetation at the Estação Ecológica de Jataí, in Luiz Antônio, State of São Paulo, Brazil, by using Moericke, Malaise, and light traps. The sampling was carried out from December 2006 to November 2009, and 371 specimens of Dryininae were caught, with the highest frequencies in spring and summer. Fourteen species of Dryinus Latreille, 1804 and one of Thaumatodryinus Perkins, 1905 were identified. The highest frequencies of Dryinus in the riparian vegetation differed significantly from those obtained in the Brazilian savannah and savannah woodland vegetation. In the riparian vegetation, the highest number of Dryinus was collected using light traps and the interactions between abundance and the collection method used were significant. The number of specimens of Dryinus collected in the Brazilian savannah and savannah woodland vegetation using Malaise traps did not differ significantly from those obtained using Moericke traps. Males significantly outnumbered females in the sex ratio of Dryinus. The species diversity of Dryinus based on females collected using Malaise traps was high in the Brazilian savannah. Furthermore, high species richness of female Dryinus was observed in riparian vegetation (six species) and Brazilian savannah (five). The light trap was the most successful method for sampling diversity of Dryininae.

Sampling strategies for tropical forest nutrient cycling studies: a case study in São Paulo, Brazil

The precise sampling of soil, biological or micro climatic attributes in tropical forests, which are characterized by a high diversity of species and complex spatial variability, is a difficult task. We found few basic studies to guide sampling procedures. The objective of this study was to define a sampling strategy and data analysis for some parameters frequently used in nutrient cycling studies, i. e., litter amount, total nutrient amounts in litter and its composition (Ca, Mg, Κ, Ν and P), and soil attributes at three depths (organic matter, Ρ content, cation exchange capacity and base saturation). A natural remnant forest in the West of São Paulo State (Brazil) was selected as study area and samples were collected in July, 1989. The total amount of litter and its total nutrient amounts had a high spatial independent variance. Conversely, the variance of litter composition was lower and the spatial dependency was peculiar to each nutrient. The sampling strategy for the estimation of litter amounts and the amount of nutrient in litter should be different than the sampling strategy for nutrient composition. For the estimation of litter amounts and the amount of nutrients in litter (related to quantity) a large number of randomly distributed determinations are needed. Otherwise, for the estimation of litter nutrient composition (related to quality) a smaller amount of spatially located samples should be analyzed. The determination of sampling for soil attributes differed according to the depth. Overall, surface samples (0-5 cm) showed high short distance spatial dependent variance, whereas, subsurface samples exhibited spatial dependency in longer distances. Short transects with sampling interval of 5-10 m are recommended for surface sampling. Subsurface samples must also be spatially located, but with transects or grids with longer distances between sampling points over the entire area. Composite soil samples would not provide a complete understanding of the relation between soil properties and surface dynamic processes or landscape aspects. Precise distribution of Ρ was difficult to estimate.

Differential growth responses to water balance of coexisting deciduous tree species are linked to wood density in a Bolivian tropical dry forest

A seasonal period of water deficit characterizes tropical dry forests (TDFs). There, sympatric tree species exhibit a diversity of growth rates, functional traits, and responses to drought, suggesting that each species may possess different strategies to grow under different conditions of water availability. The evaluation of the long-term growth responses to changes in the soil water balance should provide an understanding of how and when coexisting tree species respond to water deficit in TDFs. Furthermore, such differential growth responses may be linked to functional traits related to water storage and conductance. We used dendrochronology and climate data to retrospectively assess how the radial growth of seven coexisting deciduous tree species responded to the seasonal soil water balance in a Bolivian TDF. Linear mixed-effects models were used to quantify the relationships between basal area increment and seasonal water balance. We related these relationships with wood density and sapwood production to assess if they affect the growth responses to climate. The growth of all species responded positively to water balance during the wet season, but such responses differed among species as a function of their wood density. For instance, species with a strong growth response to water availability averaged a low wood density which may facilitate the storage of water in the stem. By contrast, species with very dense wood were those whose growth was less sensitive to water availability. Coexisting tree species thus show differential growth responses to changes in soil water balance during the wet season. Our findings also provide a link between wood density, a trait related to the ability of trees to store water in the stem, and wood formation in response to water availability.