LIVIVO - Search results -

Search results

Result 1 - 10 of total 109

Search options

Article ; Online: A Comparison of Four Spatial Interpolation Methods for Modeling Fine-Scale Surface Fuel Load in a Mixed Conifer Forest with Complex Terrain

Hoffman, Chad M. / Ziegler, Justin P. / Tinkham, Wade T. / Hiers, John Kevin / Hudak, Andrew T.

Fire. 2023 May 25, v. 6, no. 6

2023

Abstract: Patterns of spatial heterogeneity in forests and other fire-prone ecosystems are increasingly recognized as critical for predicting fire behavior and subsequent fire effects. Given the difficulty in sampling continuous spatial patterns across scales, ... ...

Abstract	Patterns of spatial heterogeneity in forests and other fire-prone ecosystems are increasingly recognized as critical for predicting fire behavior and subsequent fire effects. Given the difficulty in sampling continuous spatial patterns across scales, statistical approaches are common to scale from plot to landscapes. This study compared the performance of four spatial interpolation methods (SIM) for mapping fine-scale fuel loads: classification (CL), multiple linear regression (LR), ordinary kriging (OK), and regression kriging (RK). These methods represent commonly used SIMs and demonstrate a diversity of non-geostatistical, geostatistical, and hybrid approaches. Models were developed for a 17.6-hectare site using a combination of metrics derived from spatially mapped trees, surface fuels sampled with an intensive network of photoload plots, and topographic variables. The results of this comparison indicate that all estimates produced unbiased spatial predictions. Regression kriging outperformed the other approaches that either relied solely on interpolation from point observations or regression-based approaches using auxiliary information for developing fine-scale surface fuel maps. While our analysis found that surface fuel loading was correlated with species composition, forest structure, and topography, the relationships were relatively weak, indicating that other variables and spatial interactions could significantly improve surface fuel mapping.
Keywords	coniferous forests ; fire behavior ; fuel loading ; fuels ; geostatistics ; kriging ; landscapes ; regression analysis ; spatial variation ; species diversity ; topography
Language	English
Dates of publication	2023-0525
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article ; Online
ISSN	2571-6255
DOI	10.3390/fire6060216
Database	NAL-Catalogue (AGRICOLA)

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: An approach to estimating forest biomass while quantifying estimate uncertainty and correcting bias in machine learning maps

Emick, Ethan / Babcock, Chad / White, Grayson W. / Hudak, Andrew T. / Domke, Grant M. / Finley, Andrew O.

Elsevier Inc. Remote Sensing of Environment. 2023 Sept., v. 295 p.113678-

2023

Abstract: Providing forest biomass estimates with desired accuracy and precision for small areas is a key challenge to incorporating forest carbon offsets into commodity trading programs. Enrolled forest carbon projects and verification entities typically rely on ... ...

Abstract	Providing forest biomass estimates with desired accuracy and precision for small areas is a key challenge to incorporating forest carbon offsets into commodity trading programs. Enrolled forest carbon projects and verification entities typically rely on probabilistically sampled field data and design-based (DB) estimators to estimate carbon storage and characterize uncertainty. However, this methodology requires a large amount of field data to achieve sufficient precision and collection of these data can be prohibitively expensive. This has spurred interest in developing regional-scale maps of forest biomass that incorporate remote sensing data as an alternative to collecting expensive plot data. These maps are often generated using machine learning (ML) algorithms that combine remote sensing products and field measurements. While these maps can produce estimates across large geographic regions at fine spatial resolutions, the estimates are prone to bias and do not have associated uncertainty estimates. Here, we assess one such map developed by the National Aeronautics and Space Administration's Carbon Monitoring System. We consider model-assisted (MA) and geostatistical model-based (GMB) estimators to address map bias and uncertainty quantification. The MA and GMB estimators use a sample of field observations as the response, and the ML-produced map as an auxiliary variable to achieve statistically defensible predictions. We compare MA and GMB estimator performance to DB and direct (DR) estimators. This assessment considers both counties and a small areal extent experimental forest, all within Oregon USA. Results suggest the MA and GMB estimators perform similar to the DB estimator at the state level and in counties containing many field plots. But in counties with moderate to small field sample sizes, the GMB and MA estimators are more precise than the DB estimator. As within-county sample sizes get smaller, the GMB estimator tends to outperform MA. Results also show the DR estimator's state-level estimates are substantially larger than the DB, MA and GMB estimates, indicating that that the DR estimator may be biased. When assessing the GMB estimator for the experimental forest, we find the GMB estimator has sufficient precision for stand-level carbon accounting even when no field observations are available within the stand. Plot-level GMB uncertainty interval coverage probabilities were estimated and showed adequate coverage. This suggests that the GMB estimator is producing statistically rigorous uncertainty estimates.
Keywords	National Aeronautics and Space Administration ; Oregon ; biomass ; carbon ; carbon sequestration ; environment ; forests ; geostatistics ; uncertainty ; Remote sensing ; Bayesian hierarchical spatial modeling ; Forest inventory ; Carbon monitoring ; Model-based inference ; Design-based inference ; Small area estimation ; Machine learning ; Random forest ; Bias correction
Language	English
Dates of publication	2023-09
Publishing place	Elsevier Inc.
Document type	Article ; Online
ZDB-ID	431483-9
ISSN	0034-4257
ISSN	0034-4257
DOI	10.1016/j.rse.2023.113678
Database	NAL-Catalogue (AGRICOLA)

In stock of ZB MED Bonn / Germany

984/1289: Show issues
Z 2005/734: Show issues

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾
- See ZB MED holdings
- Order with fees

Article: Carbon monitoring and above ground biomass trends: Anchor forest opportunities for tribal, private and federal relationships

Corrao, Mark V. / Hudak, Andrew T. / Desautel, Cody / Bright, Benjamin C. / Carlo, Edil Sepúlveda

Trees, forests and people. 2022 Sept., v. 9

2022

Abstract: There are more than 300 million hectares of forested land within the conterminous United States essential to sustaining the myriad social/cultural, economic, and ecologic benefits society enjoys from these lands. Nationwide, millions of forested hectares, ...

Abstract	There are more than 300 million hectares of forested land within the conterminous United States essential to sustaining the myriad social/cultural, economic, and ecologic benefits society enjoys from these lands. Nationwide, millions of forested hectares, both private and public, are disappearing functionally and physically through serve wildfire fire and land conversion. On many of these lands, management, centered on fire suppression, has led to reductions in forest resilience to wildfire. Lands, overstocked with accumulated fuel and faced with a changing climate, are expected to continue this legacy of fire and deteriorating health. A paradigm shift is needed to face the challenges confronting forests and enhance collaborative efforts across multiple forest ownerships. Our ability to leverage emerging technologies and pair them with the knowledge of indigenous peoples presents new opportunities for success. The objectives of this study were to 1) assess the Anchor Forest concept as a framework to leverage collaborative motivations and leadership by indigenous peoples (Tribes) in eastern Washington State to improve forest ecosystem health across legal and political boundaries, ‘cross-boundary’ management, and 2) demonstrate how the NASA carbon monitoring system (CMS) mapping products of regional forestland above ground biomass (AGB) density and temporal trends can provide information that supports decisionmakers in their efforts to collaboratively approach improving forest health conditions through management activities.
Keywords	Washington (state) ; aboveground biomass ; carbon ; climate ; environmental health ; fire suppression ; forest ecosystems ; forest health ; forest land ; forests ; land use change ; leadership ; politics ; wildfires
Language	English
Dates of publication	2022-09
Publishing place	Elsevier B.V.
Document type	Article
ISSN	2666-7193
DOI	10.1016/j.tfp.2022.100302
Database	NAL-Catalogue (AGRICOLA)

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Use of Multi-Date and Multi-Spectral UAS Imagery to Classify Dominant Tree Species in the Wet Miombo Woodlands of Zambia.

Shamaoma, Hastings / Chirwa, Paxie W / Zekeng, Jules C / Ramoelo, Abel / Hudak, Andrew T / Handavu, Ferdinand / Syampungani, Stephen

Sensors (Basel, Switzerland)

2023 Volume 23, Issue 4

Abstract: Accurate maps of tree species distributions are necessary for the sustainable management of forests with desired ecological functions. However, image classification methods to produce species distribution maps for supporting sustainable forest management ...

Abstract	Accurate maps of tree species distributions are necessary for the sustainable management of forests with desired ecological functions. However, image classification methods to produce species distribution maps for supporting sustainable forest management are still lacking in the Miombo woodland ecoregion. This study used multi-date multispectral Unmanned Aerial Systems (UAS) imagery collected at key phenological stages (leaf maturity, transition to senescence, and leaf flushing) to classify five dominant canopy species of the wet Miombo woodlands in the Copperbelt Province of Zambia. Object-based image analysis (OBIA) with a random forest algorithm was used on single date, multi-date, and multi-feature UAS imagery for classifying the dominant canopy tree species of the wet Miombo woodlands. It was found that classification accuracy varies both with dates and features used. For example, the August image yielded the best single date overall accuracy (OA, 80.12%, 0.68 kappa), compared to October (73.25% OA, 0.59 kappa) and May (76.64% OA, 0.63 kappa). The use of a three-date image combination improved the classification accuracy to 84.25% OA and 0.72 kappa. After adding spectral indices to multi-date image combination, the accuracy was further improved to 87.07% and 0.83 kappa. The results highlight the potential of using multispectral UAS imagery and phenology in mapping individual tree species in the Miombo ecoregion. It also provides guidance for future studies using multispectral UAS for sustainable management of Miombo tree species.
MeSH term(s)	Zambia ; Image Processing, Computer-Assisted ; Imagery, Psychotherapy ; Plant Leaves ; Forests
Language	English
Publishing date	2023-02-16
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s23042241
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article: An Assessment of Fire Refugia Importance Criteria Ranked by Land Managers

Martinez, Anthony / Hudak, Andrew / Kolden, Crystal / Meddens, Arjan

Fire. 2019 May 22, v. 2, no. 2

2019

Abstract: There is evidence that forest resiliency is declining in the western US due to recent increases in both areas burned by wildfire and the number of large fires. Fire refugia may increase forest resiliency; however, for land managers to incorporate fire ... ...

Abstract	There is evidence that forest resiliency is declining in the western US due to recent increases in both areas burned by wildfire and the number of large fires. Fire refugia may increase forest resiliency; however, for land managers to incorporate fire refugia into their management plans, methods need to be developed to identify and rank criteria for what make fire refugia important. As part of a larger effort to build a spatially explicit ranking model for unburned islands in the inland northwestern US, we investigated the perceived importance of criteria used to inform a ranking model to identify high-value fire refugia. We developed a survey targeting land managers within the inland northwestern US. Participants were asked to score a predetermined list of criteria by their importance for determining the value of fire refugia. These scores were analyzed to identify trends among respondents that could be used to develop a fire refugia ranking model. The results indicate that respondents generally organized criteria into two groups: Human infrastructure and wildlife habitat. However, there was little consensus among respondents in their scoring of fire refugia importance criteria, suggesting that a single region-wide fire refugia ranking model may not be feasible. More research with a larger sample size is needed to develop targeted ranking models.
Keywords	forests ; infrastructure ; islands ; managers ; models ; refuge habitats ; surveys ; wildfires ; wildlife habitats ; Northwestern United States
Language	English
Dates of publication	2019-0522
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ISSN	2571-6255
DOI	10.3390/fire2020027
Database	NAL-Catalogue (AGRICOLA)

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Environmental influences on density and height growth of natural ponderosa pine regeneration following wildfires

Hammond, Darcy H. / Strand, Eva K. / Morgan, Penelope / Hudak, Andrew T. / Newingham, Beth Ann

Fire. 2021 Oct. 21, v. 4, no. 4

2021

Abstract: Over the past century the size and severity of wildfires, as well as post-fire recovery processes (e.g., seedling establishment), have been altered from historical levels due to management policies and changing climate. Tree seedling establishment and ... ...

Abstract	Over the past century the size and severity of wildfires, as well as post-fire recovery processes (e.g., seedling establishment), have been altered from historical levels due to management policies and changing climate. Tree seedling establishment and growth drive future overstory tree dynamics after wildfire. Post-fire tree regeneration can be highly variable depending on burn severity, pre-fire forest condition, tree regeneration strategies, and climate conditions; however, few studies have examined how different abiotic and biotic factors impact seedling density and growth and the interactions among those factors. We measured seedling density and height growth in 2015-2016 on three wildfires that burned in ponderosa pine (Pinus ponderosa) forests during the time period 2000-2007 across broad environmental and burn severity gradients. Using a non-parametric multiplicative regression model, we found that downed woody fuel load, duff depth, and fall precipitation best explained variation in seedling density, while the distance to nearest seed tree, a soil productivity index, duff depth, and spring precipitation as snow best explained seedling height growth. Overall, burn severity and climate were found important in tree regeneration although the primary factors influencing density and growth vary. Drier conditions and changes to precipitation seasonality have the potential to influence tree establishment, survival, and growth in post-fire environments, which could lead to significant impacts for long-term forest recovery.
Keywords	Pinus ponderosa ; burn severity ; forests ; fuel loading ; overstory ; plant establishment ; regression analysis ; seedlings ; soil productivity ; spring ; trees ; wildfires
Language	English
Dates of publication	2021-1021
Document type	Article
ISSN	2571-6255
DOI	10.3390/fire4040080
Database	NAL-Catalogue (AGRICOLA)

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Evaluating the Use of Lidar to Discern Snag Characteristics Important for Wildlife

Stitt, Jessica M. / Hudak, Andrew T. / Silva, Carlos A. / Vierling, Lee A. / Vierling, Kerri T.

Remote Sensing. 2022 Feb. 03, v. 14, no. 3

2022

Abstract: Standing dead trees (known as snags) are historically difficult to map and model using airborne laser scanning (ALS), or lidar. Specific snag characteristics are important for wildlife; for instance, a larger snag with a broken top can serve as a nesting ...

Abstract	Standing dead trees (known as snags) are historically difficult to map and model using airborne laser scanning (ALS), or lidar. Specific snag characteristics are important for wildlife; for instance, a larger snag with a broken top can serve as a nesting platform for raptors. The objective of this study was to evaluate whether characteristics such as top intactness could be inferred from discrete-return ALS data. We collected structural information for 198 snags in closed-canopy conifer forest plots in Idaho. We selected 13 lidar metrics within 5 m diameter point clouds to serve as predictor variables in random forest (RF) models to classify snags into four groups by size (small (<40 cm diameter) or large (≥40 cm diameter)) and intactness (intact or broken top) across multiple iterations. We conducted these models first with all snags combined, and then ran the same models with only small or large snags. Overall accuracies were highest in RF models with large snags only (77%), but kappa statistics for all models were low (0.29–0.49). ALS data alone were not sufficient to identify top intactness for large snags; future studies combining ALS data with other remotely sensed data to improve classification of snag characteristics important for wildlife is encouraged.
Keywords	coniferous forests ; lidar ; models ; remote sensing ; statistics ; wildlife ; Idaho
Language	English
Dates of publication	2022-0203
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ZDB-ID	2513863-7
ISSN	2072-4292
ISSN	2072-4292
DOI	10.3390/rs14030720
Database	NAL-Catalogue (AGRICOLA)

Order via subito

Article: Environmental Influences on Density and Height Growth of Natural Ponderosa Pine Regeneration following Wildfires

Hammond, Darcy H. / Strand, Eva K. / Morgan, Penelope / Hudak, Andrew T. / Newingham, Beth A.

Fire. 2021 Oct. 21, v. 4, no. 4

2021

Abstract	Over the past century the size and severity of wildfires, as well as post-fire recovery processes (e.g., seedling establishment), have been altered from historical levels due to management policies and changing climate. Tree seedling establishment and growth drive future overstory tree dynamics after wildfire. Post-fire tree regeneration can be highly variable depending on burn severity, pre-fire forest condition, tree regeneration strategies, and climate; however, few studies have examined how different abiotic and biotic factors impact seedling density and growth and the interactions among those factors. We measured seedling density and height growth in the period 2015–2016 on three wildfires that burned in ponderosa pine (Pinus ponderosa) forests in the period 2000–2007 across broad environmental and burn severity gradients. Using a non-parametric multiplicative regression model, we found that downed woody fuel load, duff depth, and fall precipitation best explained variation in seedling density, while the distance to nearest seed tree, a soil productivity index, duff depth, and spring precipitation as snow best explained seedling height growth. Overall, results highlight the importance of burn severity and post-fire climate in tree regeneration, although the primary factors influencing seedling density and height growth vary. Drier conditions and changes to precipitation seasonality have the potential to influence tree establishment, survival, and growth in post-fire environments, which could lead to significant impacts for long-term forest recovery.
Keywords	Pinus ponderosa ; burn severity ; climate ; forests ; fuel loading ; overstory ; plant establishment ; regression analysis ; seedlings ; soil productivity ; spring ; trees ; wildfires
Language	English
Dates of publication	2021-1021
Publishing place	Multidisciplinary Digital Publishing Institute
Document type	Article
ISSN	2571-6255
DOI	10.3390/fire4040080
Database	NAL-Catalogue (AGRICOLA)

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Integrating active fire behavior observations and multitemporal airborne laser scanning data to quantify fire impacts on tree growth: A pilot study in mature Pinus ponderosa stands

Sparks, Aaron M. / Smith, Alistair M. S. / Hudak, Andrew T. / Corrao, Mark V. / Kremens, Robert L. / Keefe, Robert F.

Forest Ecology and Management. 2023 Oct. 01, v. 545 p.121246-

2023

Abstract: Methods that integrate pre-, active-, and post-fire measurements to quantify fire effects across multiple spatial scales are needed to improve our understanding of ecological effects following fire and for informing natural resource management decisions ... ...

Abstract	Methods that integrate pre-, active-, and post-fire measurements to quantify fire effects across multiple spatial scales are needed to improve our understanding of ecological effects following fire and for informing natural resource management decisions that rely on post-fire growth and yield estimates. Given growth and yield modeling systems require tree level measurements to parameterize diameter and height distributions, effective datasets require both tree and stand level characterization. However, most stand-to-landscape scale fire effects studies use optical multispectral data (e.g., 30 m spatial resolution Landsat data) which are too coarse to quantify tree-level effects and is limited in its ability to quantify changes in forest structure. Most studies also fail to integrate active fire behavior observations, such as heat flux, limiting their ability to identify mechanisms of tree injury and mortality and/or predict fire effects. Combining active fire observations and structural measurements derived from multitemporal airborne laser scanning (ALS) data has been proposed to quantify fire effects on tree structure and growth but has yet to be tested. In this pilot study, we used a combination of fire behavior and heat flux metrics, including Fire Radiative Power per unit area (FRP: W m⁻²) and Fire Radiative Energy per unit area (FRE: J m⁻²), along with multitemporal fie
Keywords	Landsat ; Pinus ponderosa ; administrative management ; data collection ; energy ; fire behavior ; forest ecology ; forests ; heat transfer ; mortality ; natural resource management ; tree damage ; tree growth ; trees ; Fire ; Fire effects ; Fire behavior ; Severity ; LiDAR ; Height growth ; Conifers
Language	English
Dates of publication	2023-1001
Publishing place	Elsevier BV
Document type	Article ; Online
ZDB-ID	751138-3
ISSN	0378-1127
ISSN	0378-1127
DOI	10.1016/j.foreco.2023.121246
Database	NAL-Catalogue (AGRICOLA)

In stock of ZB MED Bonn / Germany

Z 6026: Show issues

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾
- See ZB MED holdings
- Order with fees

Article: Influence of flight parameters on UAS-based monitoring of tree height, diameter, and density

Swayze, Neal C / Tinkham, Wade T / Vogeler, Jody C / Hudak, Andrew T

Elsevier Inc. Remote sensing of environment. 2021 Sept. 15, v. 263

2021

Abstract: Increased focus on restoring forest structural variation and spatial pattern in dry conifer forests has led to greater emphasis on forest monitoring strategies that can be summarized across scales. To inform restoration objectives with data sources that ... ...

Abstract	Increased focus on restoring forest structural variation and spatial pattern in dry conifer forests has led to greater emphasis on forest monitoring strategies that can be summarized across scales. To inform restoration objectives with data sources that can characterize individual trees, groups of trees, and the entire stand, different remote sensing strategies such as aerial and terrestrial light detection and ranging (LiDAR) have been explored. Unfortunately, high equipment and operational costs of aerial systems, along with limited spatial extent of terrestrial scanners, have restricted widespread adoption of these technologies for repeated forest monitoring. This study investigates applications of unmanned aerial system (UAS) imagery for Structure from Motion derived modeling of individual tree and stand-level metrics. Specifically, we evaluate how flight parameters impact UAS extracted height and imputed DBH accuracies against field stem-mapped values. In total, 30 UAS image datasets collected from combinations of three altitudes, two flight patterns, and five camera orientations were assessed. Tree heights were extracted using a variable window function that searched UAS-derived canopy height models, while DBH was sampled from point cloud slices at 1.32–1.42 m using a least squares circle fitting algorithm. The sample trees were then filtered against National Forest Inventory data from the study region to ensure reasonable matching of extracted heights and diameters. The matched values were used to create a height to diameter relationship for predicting missing DBH values. Extracted and imputed tree values were compared against stem-mapped values to determine tree commission and omission rates, the accuracy and precision of extracted tree height, DBH, as well as overstory and understory stand density. Finding that, 1) tree extraction accuracy and correctness was maximized (F-score = 0.77) for nadir crosshatch UAS flight designs; 2) extracted tree height R² with stem-mapped values was high (R² ≥ 0.98) for all UAS flight parameters, but the quality (mean error = 0.79 cm) and quantity (~10% of all trees) of extracted DBH values was maximized for lower altitude, nadir crosshatch acquisitions; 3) the distribution of predicted DBH values most closely matched field observed values for off-nadir crosshatch flight designs; 4) using either off-nadir or crosshatch flight designs at lower altitudes maximized correlation (r > 0.70) and accuracy (basal area within 2 m² ha⁻¹) of stand density estimates. This study demonstrates a novel UAS-based inventory strategy for estimating individual tree structural attributes (i.e., location, height, and DBH) in dry conifer forests, without the need for in situ field observations.
Keywords	algorithms ; altitude ; cameras ; canopy height ; conifers ; data collection ; flight ; forest inventory ; lidar ; national forests ; overstory ; stand density ; tree height ; trees ; understory ; unmanned aerial vehicles
Language	English
Dates of publication	2021-0915
Publishing place	Elsevier Inc.
Document type	Article
Note	NAL-AP-2-clean
ZDB-ID	431483-9
ISSN	0034-4257
ISSN	0034-4257
DOI	10.1016/j.rse.2021.112540
Database	NAL-Catalogue (AGRICOLA)

In stock of ZB MED Bonn / Germany

984/1289: Show issues
Z 2005/734: Show issues

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾
- See ZB MED holdings
- Order with fees

To top

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Bonn / Germany

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Bonn / Germany

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Bonn / Germany

Order via subito

Inter-library loan at ZB MED