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Satellite data are increasingly used to provide information to support forest monitoring and reporting at varying levels of detail and for a range of attributes and spatial extents. Forests are dynamic environments and benefit from regular assessments to capture status and changes both locally and over large areas. Satellite data can provide products relevant to forest science and management on a regular basis (e.g. annually) for land cover, disturbance (i.e. date, extent, severity, and type), forest recovery (e.g. quantification of return of trees following disturbance), and forest structure (e.g. volume, biomass, canopy cover, stand height), with products generated over large areas in a systematic, transparent, and repeatable fashion. While pixel-based outcomes are typical based upon satellite data inputs, many end users continue to require polygon-based forest inventory information. To meet this information need and have a spatial context for forest inventory attributes such as tree species assemblages, we present a new work-flow to produce a novel spatially explicit, stand-level satellite-based forest inventory (SBFI) in Canada applying image segmentation approaches to generate spatially unique forest stands (polygons), which are the fundamental spatial unit of management-level inventories. Thus, SBFI offers spatial context to aggregate and generalize other pixel-based forest data sets. Canada has developed a National Terrestrial Ecosystem Monitoring System (NTEMS) that utilizes medium spatial resolution imagery, chiefly from Landsat, to annually characterize Canada's forests at a pixel level from 1984 until present. These NTEMS datasets are used to populate SBFI polygons with information regarding status (e.g. current land cover type, dominant tree species, or total biomass) as well as information on dynamics (e.g. has this polygon been subject to change, when, by what, and if so, how is the forest recovering). Here, we outline the information drivers for forest monitoring, present a set of products aimed at meeting these information needs, and follow to demonstrate the SBFI concept over the 650-Mha extent of Canada's forest-dominated ecosystems. In so doing, the entirety of Canada's forest ecosystems (managed and unmanaged) were mapped using the same data, attributes, and temporal representation. Moreover, the use of polygons allows for the generation of attributes such as tree species composition, and total biomass and wood volume in a stand-scale format familiar to landscape managers and suitable for strategic planning. The data, methods, and outcomes presented here are portable to other regions and input data sources, and the national SBFI outcomes for Canada are available via open access. [ABSTRACT FROM AUTHOR]

Spatial information on forest composition is invaluable for achieving scientific, ecological, and management objectives and for monitoring multiple changes in forest ecosystems. The increased flow of optical satellite data provides new opportunities to improve tree species mapping. However, the accuracy of such maps is affected by training data, and in particular on the homogeneity of individual classes. Thus, we evaluated the effect of data homogeneity in tree species classification. We performed tree species classification by considering different ways to partition data into tree species classes. The class sets considered were (i) only mixed coniferous and mixed deciduous forest classes, (ii) single-species classes, (iii) single-species, mixed coniferous and mixed deciduous classes, and (iv) single-species, mixed coniferous and mixed deciduous classes and a true mixed class. Using data from the Swedish National Forest Inventory, we varied the threshold that defined dominating species. Tree species were classified for a study area in central Sweden using Sentinel-2 data and two classification approaches: Bayesian inference and random forest (RF). Images were selected by class separability and the most informative images based on variable selection with RF. The most informative images tended to be selected by both methods. However, in forests with tree species of similar spectral behaviour, image selection on the basis of class separability was found to be more reliable. More accurate classification results were achieved as the number of classes decreased and the threshold of plot purity increased. The Bayesian classification approach of only mixed coniferous and mixed deciduous classes gave the highest OA, always greater than 90%. When discriminating between pure plots of Birch (Betula spp.), Spruce (Picea abies), Scots pine (Pinus sylvestris) and Lodgepole pine (Pinus contorta), the best OA values were 84% for Bayesian and 80% for RF. In more complicated scenarios, RF resulted in higher overall accuracies (OA). [ABSTRACT FROM AUTHOR]

Accurate and fine-scale forest data are essential to improve natural resource management, particularly in the face of climate change. Here, we present SCANFI, the Spatialized CAnadian National Forest Inventory, which provides coherent, 30 m resolution 2020 wall-to-wall maps of forest attributes (land cover type, canopy height, crown closure, aboveground tree biomass, and main species composition). These maps were developed using the NFI photo-plot dataset, a systematic regular sample grid of photo-interpreted high-resolution imagery covering all of Canada's non-arctic landmass. SCANFI was produced using temporally harmonized summer and winter Landsat spectral imagery along with hundreds of tile-level regional models based on a multiresponse k-nearest neighbours and random forest imputation method. This tile-level approach revealed the importance of radiometric variables in predicting vegetation attributes, namely winter radiometry, as the large-scale climate gradients were controlled at the tile-level. SCANFI was validated with rigorous cross-validation analyses, which revealed robust model performance for structural attributes (biomass R2 = 0.76; crown closure R2 = 0.82; height R2 = 0.78) and tree species cover (e.g., Douglas fir R2 = 0.60). SCANFI attributes were also validated with several independent external products, ranging from ground plot-based tree species cover (e.g., black spruce R2 = 0.53) to satellite LiDAR height data products (e.g., crown closure R2 = 0.71). SCANFI total aboveground biomass trends also followed those published by other studies. The methodology presented herein can be used to map time series of these attributes, identify the original training points used to make any given prediction, as well as map additional variables associated with the NFI photo-plots that are challenging to map using traditional remote sensing approaches. [ABSTRACT FROM AUTHOR]

This article shows how probability sampling and citizen science efforts can complement each other, using the USDA Forest Service's Forest Inventory and Analysis (FIA) program and the ongoing search by the National Register of Champion Trees (NRCT) for the largest specimen of each naturally occurring tree species in the United States as an example. We develop a ratio statistic (Z s ) that uses the difference in size of the largest tree of a species from each database to order the tree species according to the assumed ease with which a larger specimen than the current national champion might be found. Our results show ninety-two candidate species that have been recorded by FIA for which there is no national champion and sixty-five species for which a new champion should be easy to find. In a supplemental table, we show ninety-four species listed as observable by FIA in the NRCT but not recorded in the FIA sample. Study Implications: An interest in forests and forestry is always accompanied by an interest in trees, especially very big trees. Two very different ways of learning about trees are analyzed concurrently in a way that reveals their complementarity. The two efforts are the probability sample, conducted by the USDA Forest Service's Forest Inventory and Analysis (FIA) Program, and the citizen science effort known as the National Register of Champion Trees (NRCT). We develop a statistic that will help tree sleuths find champion trees and provide FIA practitioners with a quality control measure and an indication of which species would benefit from an increase in sample intensity. [ABSTRACT FROM AUTHOR]

The majority of pathogenic mutations in the neurofibromatosis type I (NF1) gene reduce total neurofibromin protein expression through premature truncation or microdeletion, but it is less well understood how loss-of-function missense variants drive NF1 disease. We have found that patient variants in codons 844 to 848, which correlate with a severe phenotype, cause protein instability and exert an additional dominant-negative action whereby wild-type neurofibromin also becomes destabilized through protein dimerization. We have used our neurofibromin cryogenic electron microscopy structure to predict and validate other patient variants that act through a similar mechanism. This provides a foundation for understanding genotype–phenotype correlations and has important implications for patient counseling, disease management, and therapeutics. [ABSTRACT FROM AUTHOR]

The aim of this study was to analyze the accuracy of predictions of dominant height, mean height, basal area, and volume from the nationwide forest attribute map (SR16). The analysis took advantage of field observations from 33 different forest inventory projects across Norway used for validation. Forest attributes for more than 5000 plots were predicted using non-stratified and stratified models of SR16 and the predictions were compared against corresponding ground reference values. Finally, the effect of different factors that might have influenced the prediction errors were analyzed using partial least squared regression (PLSR) to determine under which conditions the SR16 is less apt. The overall results across all plots were adequate (RMSE of 10%, MD of 2% for dominant and mean height; RMSE of 28%, MD of 4% for basal area; RMSE of 31%, MD of 5% for volume). However, when the accuracy was assessed locally for each inventory project, large differences in accuracy were observed. The MD% values for some inventory projects were substantial (>30% for basal area and volume). The results showed that stratification did not necessarily improve the results and that factors related to the forest structure had the greatest impact on the PLSR analysis. [ABSTRACT FROM AUTHOR]

Forest fragmentation is a widespread phenomenon that directly or indirectly affects the processes that take place both in forest ecosystems and in their immediate surroundings. So far, many studies confirm its negative effects, especially on biodiversity. On the other hand, there are few studies that address the effects of forest fragmentation on the amount of accumulated biomass or carbon, as well as on the characteristics of wood resources in managed forests. Therefore, issues related to timber production, which are important from the point of view of multifunctional forest management, are omitted. The aim of our research was to add to the knowledge in this area. In particular, we focused on assessing the impact of forest fragmentation on wood resources based on an analysis of edge effects in forest patches (units formed by combining forest fragments characterized by structural connectivity). Vector data describing the topography of forest fragments in Poland and the results of the National Forest Inventory (NFI) from 2015–2019 were used as material for solving this problem. The results of our research showed that the effects of fragmentation on managed pine stands depend on the age of the stand and the fertility of the habitat. In young stands growing on barren or strongly barren habitats, growing stock volume turned out to be significantly higher in the edge zone. In older stands, especially on moderately fertile habitats, significantly higher resources were found in the interior zone of forest patches. Habitat quality also had a significant effect on the amount of carbon accumulated. In strongly barren habitats, higher carbon mass was found in edge zones, while in moderately fertile habitats, stands had higher carbon volume in the interior zone. Our results illustrate that forest fragmentation is a very complex process that can increase or reduce wood resources, depending on the age of the stand and the quality of the habitat. From the standpoint of measurable benefits, it was concluded that protection from the negative effects of fragmentation should focus primarily on older stands and more fertile habitats. [ABSTRACT FROM AUTHOR]

Stand-level growth and yield models are important tools that support forest managers and policymakers. We used recent data from the Norwegian National Forest Inventory to develop stand-level models, with components for dominant height, survival (number of survived trees), ingrowth (number of recruited trees), basal area, and total volume, that can predict long-term stand dynamics (i.e. 150 years) for the main species in Norway, namely Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.), and birch (Betula pubescens Ehrh. and Betula pendula Roth). The data used represent the structurally heterogeneous forests found throughout Norway with a wide range of ages, tree size mixtures, and management intensities. This represents an important alternative to the use of dedicated and closely monitored long-term experiments established in single species even-aged forests for the purpose of building these stand-level models. Model examination by means of various fit statistics indicated that the models were unbiased, performed well within the data range and extrapolated to biologically plausible patterns. The proposed models have great potential to form the foundation for more sophisticated models, in which the influence of other factors such as natural disturbances, stand structure including species mixtures, and management practices can be included. [ABSTRACT FROM AUTHOR]

Background: The Norwegian forest resource map (SR16) maps forest attributes by combining national forest inventory (NFI), airborne laser scanning (ALS) and other remotely sensed data. While the ALS data were acquired over a time interval of 10 years using various sensors and settings, the NFI data are continuously collected. Aims of this study were to analyze the effects of stratification on models linking remotely sensed and field data, and assess the accuracy overall and at the ALS project level. Materials and methods: The model dataset consisted of 9203 NFI field plots and data from 367 ALS projects, covering 17 Mha and 2/3 of the productive forest in Norway. Mixed-effects regression models were used to account for differences among ALS projects. Two types of stratification were used to fit models: 1) stratification by the three main tree species groups spruce, pine and deciduous resulted in species-specific models that can utilize a satellite-based species map for improving predictions, and 2) stratification by species and maturity class resulted in stratum-specific models that can be used in forest management inventories where each stand regularly is visually stratified accordingly. Stratified models were compared to general models that were fit without stratifying the data. Results: The species-specific models had relative root-mean-squared errors (RMSEs) of 35%, 34%, 31%, and 12% for volume, aboveground biomass, basal area, and Lorey's height, respectively. These RMSEs were 2–7 percentage points (pp) smaller than those of general models. When validating using predicted species, RMSEs were 0–4 pp. smaller than those of general models. Models stratified by main species and maturity class further improved RMSEs compared to species-specific models by up to 1.8 pp. Using mixed-effects models over ordinary least squares models resulted in a decrease of RMSE for timber volume of 1.0–3.9 pp., depending on the main tree species. RMSEs for timber volume ranged between 19%–59% among individual ALS projects. Conclusions: The stratification by tree species considerably improved models of forest structural variables. A further stratification by maturity class improved these models only moderately. The accuracy of the models utilized in SR16 were within the range reported from other ALS-based forest inventories, but local variations are apparent. [ABSTRACT FROM AUTHOR]

Background: Forest carbon models are recognized as suitable tools for the reporting and verification of forest carbon stock and stock change, as well as for evaluating the forest management options to enhance the carbon sink provided by sustainable forestry. However, given their increased complexity and data availability, different models may simulate different estimates. Here, we compare carbon estimates for Romanian forests as simulated by two models (CBM and EFISCEN) that are often used for evaluating the mitigation options given the forest-management choices. Results: The models, calibrated and parameterized with identical or harmonized data, derived from two successive national forest inventories, produced similar estimates of carbon accumulation in tree biomass. According to CBM simulations of carbon stocks in Romanian forests, by 2060, the merchantable standing stock volume will reach an average of 377 m3 ha−1, while the carbon stock in tree biomass will reach 76.5 tC ha−1. The EFISCEN simulations produced estimates that are about 5% and 10%, respectively, lower. In addition, 10% stronger biomass sink was simulated by CBM, whereby the difference reduced over time, amounting to only 3% toward 2060. Conclusions: This model comparison provided valuable insights on both the conceptual and modelling algorithms, as well as how the quality of the input data may affect calibration and projections of the stock and stock change in the living biomass pool. In our judgement, both models performed well, providing internally consistent results. Therefore, we underline the importance of the input data quality and the need for further data sampling and model improvements, while the preference for one model or the other should be based on the availability and suitability of the required data, on preferred output variables and ease of use. [ABSTRACT FROM AUTHOR]

Forest fragmentation has a relevant impact on biodiversity. An interesting alternative to estimate these indices is to use sampling data. This study aims to estimate aggregation index (AI) and the degree of clumping of forested landscape based on AI. The assessment was conducted using different point distances, inventory regions and cardinal directions. For this purpose, a dataset from one five-year periods (2007–2011) of the Swedish National Forest Inventory (NFI) was used. The estimation of AI from field-based inventory can give us a general picture of the current status of forest landscape. The results also show that the estimated AI is a distance dependent function. The corresponding estimated variance of the index is smaller for longer distances. The obtained results indicate that the estimated variance depends on both sample size and pair point distances. Estimated AI showed different values in different cardinal directions. To compare two regions or a given region over time, a given point distance should be used. The main advantage of the applied procedure is that a range of AI values can be produced rather than a single number. Furthermore, in field-based inventory, the obtained results are more reliable, because one works implicitly with a single forest definition only. [ABSTRACT FROM AUTHOR]

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It has been reported that high mobility group nucleosomal binding domain 2 (HMGN2) is a nucleus‐related protein that regulates gene transcription and plays a critical role in bacterial clearance. An elevated level of HMGN2 reduced integrin α5/β1 expression of human pulmonary epithelial A549 cells was demonstrated during Klebsiella pneumoniae infection, thus weakening bacterial adhesion and invasion. However, the mechanism by which HMGN2 regulates integrin expression remains unclear. This study found that a transcription factor‐nuclear factor I (NFI), which serves as the potential target of HMGN2 regulated integrin expression. The results showed that HMGN2 was able to promote NFIA and NFIB expression by increasing H3K27 acetylation of NFIA/B promoter regions. The integrin α5/β1 expression was significantly enhanced by knockdown of NFIA/B via a siRNA approach. Meanwhile, NFIA/B silence could also compromise the inhibition effect of HMGN2 on the integrin α5/β1 expression. Mechanistically, it was demonstrated that HMGN2 facilitated the recruitment of NFI on the promoter regions of integrin α5/β1 according to the chromatin immunoprecipitation assay. In addition, it was further demonstrated that the knockdown of NFIA/B induced more adhesion of Klebsiella pneumoniae on pulmonary epithelial A549 cells, which could be reversed by the application of an integrin inhibitor RGD. The results revealed a regulatory role of HMGN2 on the transcription level of integrin α5/β1, indicating a potential treatment strategy against Klebsiella pneumoniae‐induced infectious lung diseases. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to construct a nationwide stand age model by using National Forest Inventory (NFI) data and nationwide airborne laser scanning (ALS) data. In plantation forestry, age is usually known. While this is not the case in boreal managed forests, age is still seldom predicted in forest management inventories. Measuring age accurately in situ is also very laborious. On the other hand, tree age is one of the accurately measured sample tree attributes in NFI field data. Many countries also have a nationwide coverage of airborne laser scanning (ALS) data. In this study, we merged these data sources and constructed a nationwide, area-based model for stand age. Results: While constructing the model, we omitted old forests from the data, since the correlation between ALS height metrics and stand age diminished at stands with age > 100 years. Additionally, the effect of growth conditions was considerable, so we also utilized different geographical and NFI variables such as site fertility and soil type in the modeling. The resultant nationwide model for the stand age of managed forests yielded a root mean square error (RMSE) of about 14 years. The model could be improved further by additional forest structure variables, but such information may not be available in practice. Conclusions: The results showed that the prediction of stand age by ALS, geographical and NFI information was challenging, but still possible with moderate success. This study is an example of the joint use of NFI and nationwide ALS data and re-use of NFI data in research. [ABSTRACT FROM AUTHOR]

Background: The nuclear factor I (NFI) is a family of transcription factors consisting of four distinct but closely related genes, NFIA, NFIB, NFIC and NFIX, which are important in the development of various tissues and organs in mammals. Recent study results have shown that NFI family may play a critical role in the progression of various human tumors and have been identified as key tumor suppressors and oncogenes for many cancers. However, the expression levels and distinctive prognostic values of the NFI family remain poorly explored in most cancers. Materials and Methods: In the present study, the differences in mRNA expression of the NFI family in various cancers were investigated using the Oncomine and TCGA databases, and the mRNA expression, genetic alteration and DNA methylation of the NFI family members in various cancers were examined using cBioPortal for Cancer Genomics. In addition, the prognostic significance of the NFI family was assessed in multiple cancers using the Kaplan-Meier plotter (KM plotter) and SurvExpress databases. Results: The mRNA expression levels in the NFI family were significantly downregulated in most cancers compared with normal tissues and DNA hypermethylation might downregulate the NFI family expression. Although NFIX expression was not downregulated in kidney, colorectal and prostate cancers. Furthermore, NFIB expression was upregulated in gastric cancer. Further survival analyses based on the KM plotter and SurvExpress databases showed dysregulations of the NFI genes were significantly correlated with survival outcomes in breast, lung, and head and neck cancers. Decreased expression levels of NFIA, NFIB and NFIC were associated with poor overall survival (OS) in head and neck cancer. Low mRNA expression of NFIA and NFIB was significantly associated with OS and first progression in lung adenocarcinoma, but not in lung squamous cell carcinoma. In addition, potential correlations between NFI family members and survival outcomes were also observed in liver, esophageal, kidney and cervical cancer. Conclusion: The results from the present study indicated certain members of the NFI family could be promising therapeutic targets and novel prognostic biomarkers for human cancers. [ABSTRACT FROM AUTHOR]

Growth, feed intake, feed efficiency, and carcass and meat quality characteristics of 136 Angus steers differing in genetic merit for post-weaning residual feed intake (RFIp) were measured over 251 days in a large commercial feedlot. The steers were evaluated in two groups, low (Low-RFI) and high (High-RFI) genetic RFIp, measured by estimated breeding values for RFIp (RFIp-EBV). The difference in RFIp-EBV between the Low- and High-RFI groups was 1.05 kg/day (–0.44 vs 0.61 kg/day; P < 0.05). The Low- and High-RFI steers were similar (P > 0.05) in age (445 vs 444 days) and weight (435 vs 429 kg) at induction, and at the end of the feeding period (705 vs 691 kg). Average daily gain (ADG) over 251 days had a small negative association with variation in RFIp-EBV (P < 0.05), reflecting a 3.6% greater ADG accompanying a difference of 1 kg/day in RFIp-EBV. Pen feed intake and feed conversion by the Low-RFI group were 10.4 kg/day and 9.3 kg/kg, and for the High-RFI group were 11.1 kg/day and 10.4 kg/kg, but without availability of individual animal feed-intake data it was not possible to test for significant differences. Carcass weight and dressing-percentage was similar for the Low- and High-RFI steers. High-RFI steers had a significantly (P < 0.05) greater depth of subcutaneous rib fat at induction and finished with 5 mm more (P < 0.05) fat at the 10/11th ribs on the carcass than the Low-RFI steers. Cross-sectional area of the eye-muscle and three measures of intramuscular or marbling fat did not differ (P > 0.05) between the Low- and High-RFI steers. Shear force was higher (P < 0.05) in meat samples aged for 1 day from the Low-RFI steers, but there was no difference (P > 0.05) from the High-RFI steers after 7 days of ageing. Compression values for meat samples aged for 1 day did not differ between the RFI groups but were higher in meat samples aged for 7 days from the Low-RFI steers. For these Angus steers, genetic superiority in RFI was associated phenotypically with superior weight gain, decreased rib fat depth, slightly less tender meat, and no compromise in marbling fat or other carcass and meat quality traits. [ABSTRACT FROM AUTHOR]

Summary Regulation of the epigenome during in vivo specification of brain stem cells is still poorly understood. Here, we report DNA methylome analyses of directly sampled cortical neural stem and progenitor cells (NS/PCs) at different development stages, as well as those of terminally differentiated cortical neurons, astrocytes, and oligodendrocytes. We found that sequential specification of cortical NS/PCs is regulated by two successive waves of demethylation at early and late development stages, which are responsible for the establishment of neuron- and glia-specific low-methylated regions (LMRs), respectively. The regulatory role of demethylation of the gliogenic genes was substantiated by the enrichment of nuclear factor I (NFI)-binding sites. We provide evidence that de novo DNA methylation of neuron-specific LMRs establishes glia-specific epigenotypes, essentially by silencing neuronal genes. Our data highlight the in vivo implications of DNA methylation dynamics in shaping epigenomic features that confer the differentiation potential of NS/PCs sequentially during development. [ABSTRACT FROM AUTHOR]

Although wall-to-wall, accurate, and up-to-date forest composition maps at the stand level are a fundamental input for many applications, ranging from global environmental issues to local forest management planning, countrywide mapping approaches on the tree type level remain rare. This paper presents and validates an innovative remote sensing based approach for a countrywide mapping of broadleaved and coniferous trees in Switzerland with a spatial resolution of 3 m. The classification approach incorporates a random forest classifier, explanatory variables from multispectral aerial imagery and a Digital Terrain Model (DTM) from Airborne Laser Scanning (ALS) data, digitized training polygons and independent validation data from the National Forest Inventory (NFI). The methodological workflow was optimized for an area of 41,285 km² that is characterized by temperate forests within a complex topography. Whereas high model overall accuracies (0.99) and kappa (0.98) were achieved, the comparison of the tree type map with independent NFI data revealed significant deviations that are related to underestimations of broadleaved trees (median of -3.17%). Constraints of the tree type mapping approach are mostly related to the acquisition date and time of the imagery and the topographic (negative) effects on the prediction. A comparison with the most recent High Resolution Layers (HRL) forest 2012 from the European Environmental Agency revealed that the tree type map is superior regarding spatial resolution, level of detail and accuracy. The high-quality map achieved with the approach presented here is of great value for optimizing forest management and planning activities and is also an important information source for applications outside the forestry sector. [ABSTRACT FROM AUTHOR]

A climate change mitigation mechanism for emissions reduction from reduced deforestation and forest degradation, plus forest conservation, sustainable management of forest, and enhancement of carbon stocks (REDD+), has received an international political support in the climate change negotiations. The mechanism will require, among others, an unprecedented technical capacity for monitoring, reporting and verification of carbon emissions from the forest sector. A functional monitoring, reporting and verification requires inventories of forest area, carbon stock and changes, both for the construction of forest reference emissions level and compiling the report on the actual emissions, which are essentially lacking in developing countries, particularly in Africa. The purpose of this essay is to contribute to a better understanding of the state and prospects of forest monitoring and reporting in the context of REDD+ in Africa. We argue that monitoring and reporting capacities in Africa fall short of the stringent requirements of the methodological guidance for monitoring, reporting and verification for REDD+, and this may weaken the prospects for successfully implementing REDD+ in the continent. We presented the challenges and prospects in the national forest inventory, remote sensing and reporting infrastructures. A North-South, South-South collaboration as well as governments own investments in monitoring, reporting and verification system could help Africa leapfrog in monitoring and reporting. These could be delivered through negotiations for the transfer of technology, technical capacities, and experiences that exist among developed countries that traditionally compile forest carbon reports in the context of the Kyoto protocol. [ABSTRACT FROM AUTHOR]

Spatially explicit knowledge of aboveground biomass (AGB) in large areas is important for accurate carbon accounting and quantifying the effect of forest disturbance on the terrestrial carbon cycle. We estimated AGB from 1990 to 2011 in northern Guangdong, China, based on a spatially explicit dataset derived from six years of national forest inventory (NFI) plots, Landsat time series imagery (1986-2011) and Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radars (PALSAR) 25 m mosaic data (2007-2010). Four types of variables were derived for modeling and assessment. The random forest approach was used to seek the optimal variables for mapping and validation. The root mean square error (RMSE) of plot-level validation was between 6.44 and 39.49 (t/ha), the normalized root-mean-square error (NRMSE) was between 7.49% and 19.01% and mean absolute error (MAE) was between 5.06 and 23.84 t/ha. The highest coefficient of determination R² of 0.8 and the lowest NRMSE of 7.49% were reported in 2006. A clear increasing trend of mean AGB from the lowest value of 13.58 t/ha to the highest value of 66.25 t/ha was witnessed between 1988 and 2000, while after 2000 there was a fluctuating ascending change, with a peak mean AGB of 67.13 t/ha in 2004. By integrating AGB change with forest disturbance, the trend in disturbance area closely corresponded with the trend in AGB decrease. To determine the driving forces of these changes, the correlation analysis was adopted and exploratory factor analysis (EFA) method was used to find a factor rotation that maximizes this variance and represents the dominant factors of nine climate elements and nine human activities elements affecting the AGB dynamics. Overall, human activities contributed more to short-term AGB dynamics than climate data. Harvesting and human-induced fire in combination with rock desertification and global warming made a strong contribution to AGB changes. This study provides valuable information for the relationships between forest AGB and climate as well as forest disturbance in subtropical zones. [ABSTRACT FROM AUTHOR]

Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily gridded European climate data set with the MOD17 algorithm to create the regional NPP dataset MODIS EURO. For evaluation of this new dataset, we compare MODIS EURO with terrestrial driven NPP from analyzing and harmonizing forest inventory data (NFI) from 196,434 plots in 12 European countries as well as the global MODIS NPP dataset for the years 2000 to 2012. Comparing these three NPP datasets, we found that the global MODIS NPP dataset differs from NFI NPP by 26%, while MODIS EURO only differs by 7%. MODIS EURO also agrees with NFI NPP across scales (from continental, regional to country) and gradients (elevation, location, tree age, dominant species, etc.). The agreement is particularly good for elevation, dominant species or tree height. This suggests that using improved climate data allows the MOD17 algorithm to provide realistic NPP estimates for Europe. Local discrepancies between MODIS EURO and NFI NPP can be related to differences in stand density due to forest management and the national carbon estimation methods. With this study, we provide a consistent, temporally continuous and spatially explicit productivity dataset for the years 2000 to 2012 on a 1-km resolution, which can be used to assess climate change impacts on ecosystems or the potential biomass supply of the European forests for an increasing bio-based economy. MODIS EURO data are made freely available at ftp://palantir.boku.ac.at/Public/MODIS_EURO. [ABSTRACT FROM AUTHOR]

Background & Aims Knockout studies of the murine Nuclear Factor I-C ( NFI-C) transcription factor revealed abnormal skin wound healing and growth of its appendages, suggesting a role in controlling cell proliferation in adult regenerative processes. Liver regeneration following partial hepatectomy ( PH) is a well-established regenerative model whereby changes elicited in hepatocytes lead to their rapid and phased proliferation. Although NFI-C is highly expressed in the liver, no hepatic function was yet established for this transcription factor. This study aimed to determine whether NFI-C may play a role in hepatocyte proliferation and liver regeneration. Methods Liver regeneration and cell proliferation pathways following two-thirds PH were investigated in NFI-C knockout (ko) and wild-type (wt) mice. Results We show that the absence of NFI-C impaired hepatocyte proliferation because of plasminogen activator I (PAI-1) overexpression and the subsequent suppression of urokinase plasminogen activator ( uPA) activity and hepatocyte growth factor (HGF) signalling, a potent hepatocyte mitogen. This indicated that NFI-C first acts to promote hepatocyte proliferation at the onset of liver regeneration in wt mice. The subsequent transient down regulation of NFI-C, as can be explained by a self-regulatory feedback loop with transforming growth factor beta 1 (TGF-ß1), may limit the number of hepatocytes entering the first wave of cell division and/or prevent late initiations of mitosis. Conclusion NFI-C acts as a regulator of the phased hepatocyte proliferation during liver regeneration. [ABSTRACT FROM AUTHOR]

Here, we identify a role for the matrilin-2 (Matn2) extracellular matrix protein in controlling the early stages of myogenic differentiation. We observed Matn2 deposition around proliferating, differentiating and fusing myoblasts in culture and during muscle regeneration in vivo. Silencing of Matn2 delayed the expression of the Cdk inhibitor p21 and of the myogenic genes Nfix, MyoD and Myog, explaining the retarded cell cycle exit and myoblast differentiation. Rescue of Matn2 expression restored differentiation and the expression of p21 and of the myogenic genes. TGF-β1 inhibited myogenic differentiation at least in part by repressing Matn2 expression, which inhibited the onset of a positive-feedback loop whereby Matn2 and Nfix activate the expression of one another and activate myoblast differentiation. In vivo, myoblast cell cycle arrest and muscle regeneration was delayed in Matn2[sup -/-] relative to wild-type mice. The expression levels of Trf3 and myogenic genes were robustly reduced in Matn2[sup -/-] fetal limbs and in differentiating primary myoblast cultures, establishing Matn2 as a key modulator of the regulatory cascade that initiates terminal myogenic differentiation. Our data thus identify Matn2 as a crucial component of a genetic switch that modulates the onset of tissue repair. [ABSTRACT FROM AUTHOR]

Background Sulfotransferase 1A1 (SULT1A1) gene expression is tissue specific, with little to no expression in normal breast epithelia. Expression in breast tumors has been documented, but the transcriptional regulation of SULT1A1 in human breast tissue is poorly understood. We identified Nuclear Factor I (NFI) as a transcription factor family involved in the regulation of SULT1A1 expression. Methods Transcription Factor Activation Profiling Plate Array assay was used to identify the possible transcription factors that regulate the gene expression of SULT1A1in normal breast MCF-10A cells and breast cancer ZR-75-1 cells. Expression levels of NFI-C and SULT1A1 were determined by real-time RT-PCR using total RNA isolated from 84 human liver samples. Expression levels of SULT1A1, NFI-A, NFI-B, NFI-C, and NFI-X were also determined in different human breast cancer cell lines (MCF-7, T-47D, ZR-75-1, and MDA-MB-231), in the transformed human epithelial cell line MCF-10A, and in ZR-75-1 cells that were transfected with siRNAs directed against NFI-A, NFI-B, NFI-C, or NFI-X for 48 h. The copy numbers of SULT1A1 in cell lines ZR-75-1, MCF-7, T-47D, MDA-MB-231, and MCF-10A were determined using a pre-designed Custom Plus TaqMan® Copy Number kit from Life Technologies. Results In normal human liver samples, SULT1A1 mRNA level was positively associated with NFIC. In different human breast cancer and normal epithelial cell lines, SULT1A1 expression was positively correlated with NFI-B and NFI-C. SULT1A1 expression was decreased 41% and 61% in ZR-75-1 cells treated with siRNAs against NFI-A and NFI-C respectively. SULT1A1 gene expression was higher in cells containing more than one SULT1A1 copy numbers. Conclusions Our data suggests that SULT1A1 expression is regulated by NFI, as well as SULT1A1 copy number variation in human breast cancer cell lines. These data provide a mechanistic basis for the differential expression of SULT1A1 in different tissues and different physiological states of disease. [ABSTRACT FROM AUTHOR]

Context: Old-growth trees play a very important role in the maintenance of biodiversity in forests. However, no clear definition is yet available to help identify them since tree age is usually not recorded in National Forest Inventories. Aims: To develop and test a new method to identify old-growth trees using a species-specific threshold for tree diameter in National Forest Inventories. Methods: Different nonlinear mixed models for diameter-age were generated using data from the Spanish Forest Inventory in order to identify the most appropriate one for Aleppo pine in its South-western distribution area. The asymptote of the optimal model indicates the threshold diameter for defining an old-growth tree. Additionally, five site index curves were examined to analyze the influence of site quality on these models. Results: The Hossfled III mixed model was found to be the most appropriate to fit diameter-age curves for Aleppo pine trees. The overall diameter at breast height threshold for old-growth trees was 40.6 cm, although over a range of sites with increasing site quality, the threshold figure was 36.0, 38.0, 40.4, 43.1, and 46.3 cm, respectively. Conclusions: This method allows the identification of old-growth trees and therefore of biodiversity hotspots, thus providing decision makers with a useful tool for management purposes. [ABSTRACT FROM AUTHOR]

An airborne laser scanning (ALS) dominant height model was developed based on data from a national scanning survey with the aim of developing a digital terrain model (DTM) for Denmark. Data obtained in the ongoing Danish national forest inventory (NFI) were used as reference data. The data comprised a total of 2072 measurements of dominant height on NFI sample plots inventoried in 2006-2007 and their corresponding ALS data. The dominant height model included four variables derived from the ALS point cloud distribution. The variables were related to canopy height, canopy density and species composition on individual plots. The RMSE of the final model was 2.25 m and the model explained 93.9% of the variation (R 2). The model was successful in predicting dominant height across a wide range of forest tree species, stand heights, stand densities, canopy cover and growing conditions. The study demonstrated how low-density ALS data obtained in a survey not specifically aimed at forest applications may be used for obtaining biophysical forest properties such as dominant height, thereby reducing the overall forest inventory costs. [ABSTRACT FROM AUTHOR]

Even though astrocytes are critical for both normal brain functions and the development and progression of neuropathological states, including neuroinflammation associated with neurodegenerative diseases, the mechanisms controlling gene expression during astrocyte differentiation are poorly understood. Thus far, several signaling pathways were shown to regulate astrocyte differentiation, including JAK-STAT, bone morphogenic protein-2/Smads, and Notch. More recently, a family of nuclear factor-1 (NFI-A, -B, -C, and -X) was implicated in the regulation of vertebral neocortex development, with NFI-A and -B controlling the onset of gliogenesis. Here, we developed an in vitro model of differentiation of stem cells towards neural progenitors (NP) and subsequently astrocytes. The transition from stem cells to progenitors was accompanied by an expected change in the expression profile of markers, including Sox-2, Musashi-1, and Oct4. Subsequently, generated astrocytes were characterized by proper morphology, increased glutamate uptake, and marker gene expression. We used this in vitro differentiation model to study the expression and functions of NFIs. Interestingly, stem cells expressed only background levels of NFIs, while differentiation to NP activated the expression of NFI-A. More importantly, NFI-X expression was induced during the later stages of differentiation towards astrocytes. In addition, NFI-X and -C were required for the expression of glial fibrillary acidic protein and secreted protein acidic and rich in cystein-like protein 1, which are the markers of astrocytes at the later stages of differentiation. We conclude that an expression program of NFIs is executed during the differentiation of astrocytes, with NFI-X and -C controlling the expression of astrocytic markers at late stages of differentiation. [ABSTRACT FROM AUTHOR]

In the first sample-based Danish National Forest Inventory (NFI) initiated in 2002, measurements were not obtained for some plots owing to there being insufficient time to complete the measurements for the inexperienced measurement crews and lack of access to some plots on privately owned land. Nationally, the percentage of missing observations ranged from 1.8 to 7.8% in different years. Missing observations may cause the complete case estimator of forest cover mean and variance to be biased. An unbiased estimator of forest cover for NFI data with missing observations was derived, which is almost as efficient as the full data estimator. The estimator of the standard error of the estimate is unbiased, giving the correct coverage when calculating the 95% confidence interval (CI). Applied to the Danish NFI data, the estimator gave a forest cover estimate of 12.4% with an estimated standard error of 0.002576, resulting in a 95% CI of 11.9-12.9%. This corresponds to an estimated total of 534,888 ha forest land with confidence limits of 513,159-556,618 ha. [ABSTRACT FROM AUTHOR]

Forests currently cover over 20% of the Australian continent and are an important resource, subject to a wide range of economic and environmental pressures. These lands support substantial numbers of forest-dependent species with national forest inventories providing important information on biodiversity. National scale information on these forests has been collected or collated since 1988 under the National Forest Inventory (NFI) programme, but substantial problems with the ‘snap shot’ approach have been recognized, particularly with respect to monitoring change and a consequent move towards a permanent and sample-based continental forest monitoring framework (CFMF) has been proposed. CFMF is proposed to consist of three Tiers: (1) satellite imagery of the continent to identify forest and change in forest cover; (2) systematic high-resolution remotely sensed data and (3) permanent ground points at 20×20 km grid interception points. The CFMF approach is in line with the international trend of national forest inventories in developed countries although the Tier 2 approach offers a useful extension. An alternative inventory approach is provided by the National Carbon Accounting System (NCAS) which models the mass of carbon and nitrogen in seven separate living and dead biomass pools for any point under forest or agriculture land use since 1970. The NCAS approach allows fine spatial and temporal monitoring of changes in these carbon and nitrogen biomass pools, and predictions of changes that result from policy or management decisions. This paper briefly reviews NFI, NCAS and the proposed CFMF, with particular emphasis on issues of use and potential for monitoring biodiversity in this biologically very diverse country. [ABSTRACT FROM AUTHOR]

Gene regulatory networks (GRNs), consisting of transcription factors and their target sites, control neurogenesis and cell-fate specification in the developing central nervous system. In this study, we use integrated single-cell RNA and single-cell ATAC sequencing (scATAC-seq) analysis in developing mouse and human retina to identify multiple interconnected, evolutionarily conserved GRNs composed of cell-type-specific transcription factors that both activate genes within their own network and inhibit genes in other networks. These GRNs control temporal patterning in primary progenitors, regulate transition from primary to neurogenic progenitors, and drive specification of each major retinal cell type. We confirm that NFI transcription factors selectively activate expression of genes promoting late-stage temporal identity in primary retinal progenitors and identify other transcription factors that regulate rod photoreceptor specification in postnatal retina. This study inventories cis - and trans -acting factors that control retinal development and can guide cell-based therapies aimed at replacing retinal neurons lost to disease. [Display omitted] • Single-cell profile of chromatin accessibility changes during mouse retinal development • Identification of conserved gene regulatory networks controlling retinal development • NFI factors directly active genes promoting late-stage retinal progenitor identity • Identification of regulators of rod photoreceptor specification Using integrated analysis of gene expression and chromatin accessibility at the single-cell level, Lyu et al. identify evolutionarily conserved gene regulatory networks that regulate temporal patterning, neurogenesis, and cell-fate specification for all major cell types in the developing mouse and human retina and functionally validate these predictions. [ABSTRACT FROM AUTHOR]

During brain development numerous and diverse set of cells, neurons, astrocytes and oligodendrocytes, are generated from a single layer of progenitors; the required gene expression program is executed by variety of transcription factors. Three of these regulatory proteins, NFIA, NFIB and NFIX, are members of the Nuclear Factor One (NFI) transcription factor family. NFIs are expressed in the ventricular zones of the embryonic neocortex, hippocampus and spinal cord as well as postmitotic neurons and glia, cerebellar granule progenitors populating the external granule layer in the hindbrain, regulating neural differentiation, particularly gliogenesis. NFIs are also present in differentiated cells of the adult brain, where their function has not been determined. Interestingly, NFIA and NFIB levels are upregulated in astrocytomas, inversely correlating with the tumor grade while patent survival increases. Moreover, in glioma and medulloblastoma mouse models insertional mutagenesis of NFI genes exacerbates tumor growth. NFI's action as a tumor suppressor in brain cancer is consistent with their role in gliogenesis and cerebellar granule neurogenesis. CDO, an extracellular protein that promotes neurogenesis, is upregulated in NFIA or NFIB null hippocampus and cerebellum. In differentiating human neural progenitor cell culture, CDO expression increases as expression of NFIB, the prominent NFI in this system, decreases. Indeed, NFIs can bind the NFI motifs in the 5kb promoter region of CDO and occupy two sites in human neural progenitors in vivo. NFIs can also inhibit CDO promoter activation in luciferase promoter assays. Meanwhile, two miRNAs that are abundant in human neural progenitors, miR124 and miR153, can bind the NFIB 3' UTR and repress its expression. Interestingly, in astrocytomas, miR124 expression is also inversely correlated with that of NFIB and increased tumour grade. We are investigating whether targets downstream from NFIB or upstream regulators of NFIB are in fact significant regulators of NFI function in vivo. [ABSTRACT FROM AUTHOR]

Because of the worldwide shortage of graftable corneas, alternatives to restore visual impairments, such as the production of a functional human cornea by tissue engineering, have emerged. Self-renewal of the corneal epithelium through the maintenance of a sub-population of corneal stem cells is required to maintain the functionality of such a reconstructed cornea. We previously reported an association between stem cell differentiation and the level to which they express the transcription factors Sp1 and NFI. In this study, we investigated the impact of replacing irradiated 3T3 (i3T3) murine fibroblast feeder cells by irradiated human corneal fibroblasts (iHFL) on the expression of Sp1 and NFI and evaluated their contribution to the proliferative properties of human corneal epithelial cells (hCECs) in both monolayer cultures and human tissue engineered corneas (hTECs). hCECs co-cultured with iHFL could be maintained for up to two more passages than when they were grown with i3T3. Western Blot and electrophoretic mobility shift assays (EMSAs) revealed no significant difference in the feeder-layer dependent increase in Sp1 at both the protein and DNA binding level, respectively, between HCECs grown with either i3T3 or iHFL. On the other hand, a significant increase in the expression and DNA binding of NFI was observed at each subsequent passage when hCECs were co-cultured along with i3T3. These changes were found to result from an increased expression of the NFIA and NFIB isoforms in hCECs grown with i3T3. Exposure of hCECs to cycloheximide revealed an increased stability of NFIB that likely resulted from post-translational glycosylation of this protein when these cells were co-cultured with i3T3. In addition, iHFL were as efficient as i3T3 at preserving corneal, slow-cycling, epithelial stem cells in the basal epithelium of the reconstructed hTECs. Furthermore, we observed an increased expression of genes whose encoded products promote hCECs differentiation along several passages in hCECs co-cultured with either type of feeder layer. Therefore, the iHFL feeder layer appears to be the most effective at maintaining the proliferative properties of hCECs in culture most likely by preserving high levels of Sp1 and low levels of NFIB, which is known for its gene repressor and cell differentiation properties. [ABSTRACT FROM AUTHOR]

Key message: There is a need to improve the consistency of international information concerning the conservation status assessment of the species and habitat types in the Natura 2000 reports. National Forest Inventories could contribute towards a more objective and harmonised assessment although their use shows some challenges as low precision for rare or small area habitats. Recommendations for a set of 12 structural and functional indicators are provided. Context: There are differences among Member States as regards applying conservation status assessment and priorities according to the Directive on the conservation of natural habitats (Habitats Directive). Aims: This paper aims to analyse the consistency as regards forest habitat types reporting and the use and suitability of National Forest Inventories (NFIs) to assess their conservation status, as well as to provide recommendations for harmonised assessments through NFIs. Methods: A survey was carried out concerning the use of NFI data to report within the commitments of the Habitat Directive. The survey covered 13 European countries, accounting for 62% of forest habitat area. Additionally, case studies were carried out in four countries. Results: The identification of forest habitat types and the set of quantitative and/or qualitative indicators differ between countries. The use of NFI data is being considered in seven countries and it is expected to increase for the 2013–2018 reporting period. The main challenges reported of use of NFI data are related to the habitat identification and their mapping, and the monitoring frequency, design and costs (i.e. rare or small area habitats). Conclusion: It is necessary to improve the comparability of the conservation status assessments between countries. [ABSTRACT FROM AUTHOR]