| 1. |
- Daume, Stefan, et al.
(författare)
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Assessing citizen science opportunities in forest monitoring using probabilistic topic modelling
- 2014
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Ingår i: Forest Ecosystems. - : Elsevier BV. - 2095-6355 .- 2197-5620. ; 1:11, s. 1-12
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundWith mounting global environmental, social and economic pressures the resilience and stability of forests and thus the provisioning of vital ecosystem services is increasingly threatened. Intensified monitoring can help to detect ecological threats and changes earlier, but monitoring resources are limited. Participatory forest monitoring with the help of “citizen scientists” can provide additional resources for forest monitoring and at the same time help to communicate with stakeholders and the general public. Examples for citizen science projects in the forestry domain can be found but a solid, applicable larger framework to utilise public participation in the area of forest monitoring seems to be lacking. We propose that a better understanding of shared and related topics in citizen science and forest monitoring might be a first step towards such a framework.MethodsWe conduct a systematic meta-analysis of 1015 publication abstracts addressing “forest monitoring” and “citizen science” in order to explore the combined topical landscape of these subjects. We employ ‘topic modelling’, an unsupervised probabilistic machine learning method, to identify latent shared topics in the analysed publications.ResultsWe find that large shared topics exist, but that these are primarily topics that would be expected in scientific publications in general. Common domain-specific topics are under-represented and indicate a topical separation of the two document sets on “forest monitoring” and “citizen science” and thus the represented domains. While topic modelling as a method proves to be a scalable and useful analytical tool, we propose that our approach could deliver even more useful data if a larger document set and full-text publications would be available for analysis.ConclusionsWe propose that these results, together with the observation of non-shared but related topics, point at under-utilised opportunities for public participation in forest monitoring. Citizen science could be applied as a versatile tool in forest ecosystems monitoring, complementing traditional forest monitoring programmes, assisting early threat recognition and helping to connect forest management with the general public. We conclude that our presented approach should be pursued further as it may aid the understanding and setup of citizen science efforts in the forest monitoring domain.
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| 2. |
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| 3. |
- Fridman, Jonas
(författare)
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Species-specific, pan-European diameter increment models based on data of 2.3 million trees
- 2018
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Ingår i: Forest Ecosystems. - : Elsevier BV. - 2095-6355 .- 2197-5620. ; 5
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Tidskriftsartikel (refereegranskat)abstract
- Background: Over the last decades, many forest simulators have been developed for the forests of individual European countries. The underlying growth models are usually based on national datasets of varying size, obtained from National Forest Inventories or from long-term research plots. Many of these models include country- and location-specific predictors, such as site quality indices that may aggregate climate, soil properties and topography effects. Consequently, it is not sensible to compare such models among countries, and it is often impossible to apply models outside the region or country they were developed for. However, there is a clear need for more generically applicable but still locally accurate and climate sensitive simulators at the European scale, which requires the development of models that are applicable across the European continent. The purpose of this study is to develop tree diameter increment models that are applicable at the European scale, but still locally accurate. We compiled and used a dataset of diameter increment observations of over 2.3 million trees from 10 National Forest Inventories in Europe and a set of 99 potential explanatory variables covering forest structure, weather, climate, soil and nutrient deposition.Results: Diameter increment models are presented for 20 species/species groups. Selection of explanatory variables was done using a combination of forward and backward selection methods. The explained variance ranged from 10% to 53% depending on the species. Variables related to forest structure (basal area of the stand and relative size of the tree) contributed most to the explained variance, but environmental variables were important to account for spatial patterns. The type of environmental variables included differed greatly among species.Conclusions: The presented diameter increment models are the first of their kind that are applicable at the European scale. This is an important step towards the development of a new generation of forest development simulators that can be applied at the European scale, but that are sensitive to variations in growing conditions and applicable to a wider range of management systems than before. This allows European scale but detailed analyses concerning topics like CO2 sequestration, wood mobilisation, long term impact of management, etc.
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| 4. |
- Niu, Guoxiang, et al.
(författare)
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Subtropical forest macro-decomposers rapidly transfer litter carbon and nitrogen into soil mineral-associated organic matter
- 2024
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Ingår i: Forest Ecosystems. - 2095-6355. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- Background: Forest soils in tropical and subtropical areas store a significant amount of carbon. Recent frameworks to assess soil organic matter (SOM) dynamics under evolving global conditions suggest that dividing bulk SOM into particulate and mineral-associated organic matter (POM vs. MAOM) is a promising method for identifying how SOM contributes to reducing global warming. Soil macrofauna, earthworms, and millipedes have been found to play an important role in facilitating SOM processes. However, how these two co-existing macrofaunae impact the litter decomposition process and directly impact the formation of POM and MAOM remains unclear. Methods: Here, we set up a microcosm experiment, which consisted of 20 microcosms with four treatments: earthworm and litter addition (E), millipedes and litter addition (M), earthworm, millipedes, and litter addition (E+M), and control (only litter addition) in five replicates. The soil and litter were sterilized prior to beginning the incubation experiment to remove any existing microbes. After incubating the samples for 42 days, the litter properties (mass, C, and N contents), soil physicochemical properties, as well as the C and N contents, and POM and MAOM 13C abundance in the 0–5 and 5–10 cm soil layers were measured. Finally, the relative influences of soil physicochemical and microbial properties on the distribution of C and N in the soil fractions were analyzed. Results: The litter mass, C, and N associated with all four treatments significantly decreased after incubation, especially under treatment E+M (litter mass: −58.8%, litter C: −57.0%, litter N: −75.1%, respectively), while earthworm biomass significantly decreased under treatment E. Earthworm or millipede addition alone showed no significant effects on the organic carbon (OC) and total nitrogen (TN) content in the POM fraction, but joint addition of both significantly increased OC and TN regardless of soil depth. Importantly, all three macrofauna treatments increased the OC and TN content and decreased the 13C abundance in the MAOM fraction. More than 65% of the total variations in the distribution of OC and TN throughout the two fractions can be explained by a combination of soil physicochemical and microbial properties. Changes in the OC distribution in the 0–5 cm soil layer are likely due to a decrease in soil pH and an increase in arbuscular mycorrhizal fungi (AMF), while those in the 5–10 cm layer are probably caused by increases in soil exchangeable Ca and Mg, in addition to fungi and gram-negative (GN) bacteria. The observed TN distribution changes in the 0–5 cm soil likely resulted from a decrease in soil pH and increases in AMF, GN, and gram-negative (GP) bacteria, while TN distribution changes in the 5–10 cm soil could be explained by increases in exchangeable Mg and GN bacteria. Conclusions: The results indicate that the coexistence of earthworms and millipedes can accelerate the litter decomposition process and store more C in the MAOM fractions. This novel finding helps to unlock the processes by which complex SOM systems serve as C sinks in tropical forests and addresses the importance of soil macrofauna in maintaining C-neutral atmospheric conditions under global climate change.
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| 5. |
- Pfeifer, Marion, et al.
(författare)
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Tropical forest canopies and their relationships with climate and disturbance : results from a global dataset of consistent field-based measurements
- 2018
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Ingår i: Forest Ecosystems. - : Elsevier BV. - 2095-6355 .- 2197-5620. ; 5:7
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundCanopy structure, defined by leaf area index (LAI), fractional vegetation cover (FCover) and fraction of absorbed photosynthetically active radiation (fAPAR), regulates a wide range of forest functions and ecosystem services. Spatially consistent field-measurements of canopy structure are however lacking, particularly for the tropics.MethodsHere, we introduce the Global LAI database: a global dataset of field-based canopy structure measurements spanning tropical forests in four continents (Africa, Asia, Australia and the Americas). We use these measurements to test for climate dependencies within and across continents, and to test for the potential of anthropogenic disturbance and forest protection to modulate those dependences.ResultsUsing data collected from 887 tropical forest plots, we show that maximum water deficit, defined across the most arid months of the year, is an important predictor of canopy structure, with all three canopy attributes declining significantly with increasing water deficit. Canopy attributes also increase with minimum temperature, and with the protection of forests according to both active (within protected areas) and passive measures (through topography). Once protection and continent effects are accounted for, other anthropogenic measures (e.g. human population) do not improve the model.ConclusionsWe conclude that canopy structure in the tropics is primarily a consequence of forest adaptation to the maximum water deficits historically experienced within a given region. Climate change, and in particular changes in drought regimes may thus affect forest structure and function, but forest protection may offer some resilience against this effect.
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| 6. |
- Pommerening, Arne
(författare)
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Global woodland structure from local interactions: new nearest-neighbour functions for understanding the ontogenesis of global forest structure
- 2020
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Ingår i: Forest Ecosystems. - : Elsevier BV. - 2095-6355 .- 2197-5620. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Background A number of hypotheses and theories, such as the Janzen-Connell hypothesis, have been proposed to explain the natural maintenance of biodiversity in tropical and temperate forest ecosystems. However, to date the details of the processes behind this natural maintenance are still unclear. Recently two new nearest-neighbour characteristics were proposed and in this paper we demonstrate how they can contribute to a better understanding of the ontogenesis of global forest structure from localised neighbourhoods. Methods We applied the new species and size segregation functions together with appropriate test procedures to four example woodland data sets from China at Daqingshan, Jiaohe, Jiulongshan and Xiaolongshan forest regions. In addition we quantified the morphology of the new characteristics and modelled a neighbourhood allometric coefficient linking the two functions. Results The results revealed quite different species segregation patterns with both conspecific and heterospecific attraction. We found these to be generally matched by equivalent size segregation patterns of attraction of similar and different sizes. It was straightforward to model the size segregation function from the knowledge of the species segregation function by estimating a neighbourhood allometric coefficient. Conclusions The new characteristics have helped to quantify the extent and rate of decline of neighbourhood interactions in terms of spatial species and size diversity. Through the allometric neighbourhood coefficient the analysis highlighted once more how closely related species and size segregation are, thus supporting the mingling-size hypothesis. Using both a traditional and a restricted random-labelling test has provided a valuable tool for understanding the exact nature of species-mingling and size-inequality relationships.
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| 7. |
- Pommerening, Arne, et al.
(författare)
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Methods of modelling relative growth rate
- 2015
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Ingår i: Forest Ecosystems. - : Elsevier BV. - 2095-6355 .- 2197-5620. ; 2
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Tidskriftsartikel (refereegranskat)abstract
- Background: Analysing and modelling plant growth is an important interdisciplinary field of plant science. The useof relative growth rates, involving the analysis of plant growth relative to plant size, has more or less independentlyemerged in different research groups and at different times and has provided powerful tools for assessing thegrowth performance and growth efficiency of plants and plant populations. In this paper, we explore how theseisolated methods can be combined to form a consistent methodology for modelling relative growth rates. Methods: We review and combine existing methods of analysing and modelling relative growth rates and applya combination of methods to Sitka spruce (Picea sitchensis (Bong.) Carr.) stem-analysis data from North Wales (UK)and British Douglas fir (Pseudotsuga menziesii (Mirb.) Franco) yield table data. Results: The results indicate that, by combining the approaches of different plant-growth analysis laboratories andusing them simultaneously, we can advance and standardise the concept of relative plant growth. Particularly thegrowth multiplier plays an important role in modelling relative growth rates. Another useful technique has beenthe recent introduction of size-standardised relative growth rates. Conclusions: Modelling relative growth rates mainly serves two purposes, 1) an improved analysis of growthperformance and efficiency and 2) the prediction of future or past growth rates. This makes the concept of relativegrowth ideally suited to growth reconstruction as required in dendrochronology, climate change and forest declineresearch and for interdisciplinary research projects beyond the realm of plant science.
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| 8. |
- Pya, Natalya, et al.
(författare)
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Incorporating shape constraints in generalized additive modelling of the height-diameter relationship for Norway spruce
- 2016
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Ingår i: Forest Ecosystems. - : Springer. - 2095-6355 .- 2197-5620. ; 3
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Tidskriftsartikel (refereegranskat)abstract
- Background: Measurements of tree heights and diameters are essential in forest assessment and modelling. Tree heights are used for estimating timber volume, site index and other important variables related to forest growth and yield, succession and carbon budget models. However, the diameter at breast height (dbh) can be more accurately obtained and at lower cost, than total tree height. Hence, generalized height-diameter (h-d) models that predict tree height from dbh, age and other covariates are needed. For a more flexible but biologically plausible estimation of covariate effects we use shape constrained generalized additive models as an extension of existing h-d model approaches. We use causal site parameters such as index of aridity to enhance the generality and causality of the models and to enable predictions under projected changeable climatic conditions.Methods: We develop unconstrained generalized additive models (GAM) and shape constrained generalized additive models (SCAM) for investigating the possible effects of tree-specific parameters such as tree age, relative diameter at breast height, and site-specific parameters such as index of aridity and sum of daily mean temperature during vegetation period, on the h-d relationship of forests in Lower Saxony, Germany.Results: Some of the derived effects, e.g. effects of age, index of aridity and sum of daily mean temperature have significantly non-linear pattern. The need for using SCAM results from the fact that some of the model effects show partially implausible patterns especially at the boundaries of data ranges. The derived model predicts monotonically increasing levels of tree height with increasing age and temperature sum and decreasing aridity and social rank of a tree within a stand. The definition of constraints leads only to marginal or minor decline in the model statistics like AIC. An observed structured spatial trend in tree height is modelled via 2-dimensional surface fitting.Conclusions: We demonstrate that the SCAM approach allows optimal regression modelling flexibility similar to the standard GAM but with the additional possibility of defining specific constraints for the model effects. The longitudinal character of the model allows for tree height imputation for the current status of forests but also for future tree height prediction.
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| 9. |
- Rappa, Nolan James
(författare)
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Multiple forest structural elements are needed to promote beetle biomass, diversity and abundance
- 2022
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Ingår i: Forest Ecosystems. - : Elsevier BV. - 2095-6355 .- 2197-5620. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Background: Retention forestry is a management strategy aiming to mitigate biodiversity loss by retaining structural elements such as dead trees that would otherwise be removed. Here we analyze the biomass, diversity and abundance among forest beetles collected using window traps on 128 1-ha forest sites reflecting gradients in the amount of structural elements in southwestern Germany. Results: We found that beetle biomass increased with mean diameter at breast height (a measure of tree size), and decreased with stand structural complexity. Biomass of individual feeding guilds responded differently to forest structural elements, namely lying deadwood, understory complexity, tree basal area and stand structural complexity. Beetle family diversity increased with the effective number of layers, i.e. 1-m forest strata occupied by vegetation assessed via terrestrial laser scanning. Abundance of feeding guilds responded to only elevation and share of deciduous trees. Community composition in terms of biomass was structured by forest elements similar to biomass of individual feeding guilds, with the addition of lying deadwood. This differed from community composition in terms of abundance of feeding guilds, which was structured by primarily standing deadwood volume and share of deciduous trees. Conclusions: Our results show that biomass, diversity and abundance respond differently to forest structural elements. This suggests that the concurrent prioritization of multiple forest elements is needed to promote forest beetles, with more focus placed on the differing resource needs among feeding guilds. In addition, retention strategies should also consider the varying responses of beetle biodiversity metrics when assessing the importance of forest structural elements.
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| 10. |
- Saarela, Svetlana, et al.
(författare)
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Mapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors
- 2020
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Ingår i: Forest Ecosystems. - : Elsevier BV. - 2095-6355 .- 2197-5620. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Background The increasing availability of remotely sensed data has recently challenged the traditional way of performing forest inventories, and induced an interest in model-based inference. Like traditional design-based inference, model-based inference allows for regional estimates of totals and means, but in addition for wall-to-wall mapping of forest characteristics. Recently Light Detection and Ranging (LiDAR)-based maps of forest attributes have been developed in many countries and been well received by users due to their accurate spatial representation of forest resources. However, the correspondence between such mapping and model-based inference is seldom appreciated. In this study we applied hierarchical model-based inference to produce aboveground biomass maps as well as maps of the corresponding prediction uncertainties with the same spatial resolution. Further, an estimator of mean biomass at regional level, and its uncertainty, was developed to demonstrate how mapping and regional level assessment can be combined within the framework of model-based inference. Results Through a new version of hierarchical model-based estimation, allowing models to be nonlinear, we accounted for uncertainties in both the individual tree-level biomass models and the models linking plot level biomass predictions with LiDAR metrics. In a 5005 km(2)large study area in south-central Sweden the predicted aboveground biomass at the level of 18 m x18 m map units was found to range between 9 and 447 Mg center dot ha(-1). The corresponding root mean square errors ranged between 10 and 162 Mg center dot ha(-1). For the entire study region, the mean aboveground biomass was 55 Mg center dot ha(-1)and the corresponding relative root mean square error 8%. At this level 75% of the mean square error was due to the uncertainty associated with tree-level models. Conclusions Through the proposed method it is possible to link mapping and estimation within the framework of model-based inference. Uncertainties in both tree-level biomass models and models linking plot level biomass with LiDAR data are accounted for, both for the uncertainty maps and the overall estimates. The development of hierarchical model-based inference to handle nonlinear models was an important prerequisite for the study.
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