Linking environmental variables with regional- scale variability in ecological structure and standing stock of carbon within UK kelp forests

Kelp forests represent some of the most productive and diverse habitats on Earth. Understanding drivers of ecological patterns at large spatial scales is critical for effective management and conservation of marine habitats. We surveyed kelp forests dominated by Laminaria hyperborea (Gunnerus) Foslie 1884 across 9° latitude and >1000 km of coastline and measured a number of physical parameters at multiple scales to link ecological structure and standing stock of carbon with environmental variables. Kelp density, biomass, morphology and age were generally greater in exposed sites within regions, highlighting the importance of wave exposure in structuring L. hyperborea populations. At the regional scale, wave-exposed kelp canopies in the cooler regions (the north and west of Scotland) were greater in biomass, height and age than in warmer regions (southwest Wales and England). The range and maximal values of estimated standing stock of carbon contained within kelp forests was greater than in historical studies, suggesting that this ecosystem property may have been previously undervalued. Kelp canopy density was positively correlated with large-scale wave fetch and fine-scale water motion, whereas kelp canopy biomass and the standing stock of carbon were positively correlated with large-scale wave fetch and light levels and negatively correlated with temperature. As light availability and summer temperature were important drivers of kelp forest biomass, effective management of human activities that may affect coastal water quality is necessary to maintain ecosystem functioning, while increased temperatures related to anthropogenic climate change may impact the structure of kelp forests and the ecosystem services they provide.

Linking environmental variables with regional- scale variability in ecological structure and standing stock of carbon within UK kelp forests

Kelp forests represent some of the most productive and diverse habitats on Earth. Understanding drivers of ecological patterns at large spatial scales is critical for effective management and conservation of marine habitats. We surveyed kelp forests dominated by Laminaria hyperborea (Gunnerus) Foslie 1884 across 9° latitude and >1000 km of coastline and measured a number of physical parameters at multiple scales to link ecological structure and standing stock of carbon with environmental variables. Kelp density, biomass, morphology and age were generally greater in exposed sites within regions, highlighting the importance of wave exposure in structuring L. hyperborea populations. At the regional scale, wave-exposed kelp canopies in the cooler regions (the north and west of Scotland) were greater in biomass, height and age than in warmer regions (southwest Wales and England). The range and maximal values of estimated standing stock of carbon contained within kelp forests was greater than in historical studies, suggesting that this ecosystem property may have been previously undervalued. Kelp canopy density was positively correlated with large-scale wave fetch and fine-scale water motion, whereas kelp canopy biomass and the standing stock of carbon were positively correlated with large-scale wave fetch and light levels and negatively correlated with temperature. As light availability and summer temperature were important drivers of kelp forest biomass, effective management of human activities that may affect coastal water quality is necessary to maintain ecosystem functioning, while increased temperatures related to anthropogenic climate change may impact the structure of kelp forests and the ecosystem services they provide.

Forests as landscapes of social inequality: tropical forest cover and land distribution among shifting cultivators

Can social inequality be seen imprinted in a forest landscape? We studied the relationship between land holding, land use, and inequality in a peasant community in the Peruvian Amazon where farmers practice swidden-fallow cultivation. Longitudinal data on land holding, land use, and land cover were gathered through field-level surveys (n = 316) and household interviews (n = 51) in 1994/1995 and 2007. Forest cover change between 1965 and 2007 was documented through interpretation of air photos and satellite imagery. We introduce the concept of “land use inequality” to capture differences across households in the distribution of forest fallowing and orchard raising as key land uses that affect household welfare and the sustainability of swidden-fallow agriculture. We find that land holding, land use, and forest cover distribution are correlated and that the forest today reflects social inequality a decade prior. Although initially land-poor households may catch up in terms of land holdings, their use and land cover remain impoverished. Differential land use investment through time links social inequality and forest cover. Implications are discussed for the study of forests as landscapes of inequality, the relationship between social inequality and forest composition, and the forest-poverty nexus.

Enzymatic upgrading of eucalypt paper-grade kraft pulp within dissolving pulp production

Dissolving-grade pulps are commonly used for the production of cellulose derivatives and regenerated cellulose. High cellulose content, low content of non-cellulosic material, high brightness, a uniform molecular weight distribution and high cellulose reactivity are the key features that determine the quality of a dissolving pulp. The first part of this work was an optimization study regarding the application of selected enzymes in different stages of a new purification process recently developed in Novozymes for purifying an eucalypt Kraft pulp into dissolving pulp, as an alternative to the pre-hydrolysis kraft (PHK) process. In addition, a viscosity reduction was achieved by cellulase (endoglucanase) treatment in the beginning of the sequence, while the GH11 and GH10 xylanases contributed to boost the brightness of the final pulp. The second part of the work aimed at exploring different auxiliary enzyme activities together with a key xylanase towards further removal of recalcitrant hemicelluloses from a partially bleached Eucalypt Kraft pulp. The resistant fraction (ca. 6% xylan in pulp) was not hydrolysable by the different combinations of enzymes tested. Production of a dissolving pulp was successful when using a cold caustic extraction (CCE) stage in the end of the sequence O-X-DHCE-X-HCE-D-CCE. The application of enzymes improved process efficiency. The main requirements for the production of a dissolving pulp (suitable for viscose making) were fulfilled: 2,7% residual xylan, 92,4% of brightness, a viscosity within the values of a commercial dissolving pulp and increased reactivity.

High-Throughput Prediction of Acacia and Eucalypt Lignin Syringyl/Guaiacyl Content Using FT-Raman Spectroscopy and Partial Least Squares Modeling

High-throughput techniques are necessary to efficiently screen potential lignocellulosic feedstocks for the production of renewable fuels, chemicals, and bio-based materials, thereby reducing experimental time and expense while supplanting tedious, destructive methods. The ratio of lignin syringyl (S) to guaiacyl (G) monomers has been routinely quantified as a way to probe biomass recalcitrance. Mid-infrared and Raman spectroscopy have been demonstrated to produce robust partial least squares models for the prediction of lignin S/G ratios in a diverse group of Acacia and eucalypt trees. The most accurate Raman model has now been used to predict the S/G ratio from 269 unknown Acacia and eucalypt feedstocks. This study demonstrates the application of a partial least squares model composed of Raman spectral data and lignin S/G ratios measured using pyrolysis/molecular beam mass spectrometry (pyMBMS) for the prediction of S/G ratios in an unknown data set. The predicted S/G ratios calculated by the model were averaged according to plant species, and the means were not found to differ from the pyMBMS ratios when evaluating the mean values of each method within the 95 % confidence interval. Pairwise comparisons within each data set were employed to assess statistical differences between each biomass species. While some pairwise appraisals failed to differentiate between species, Acacias, in both data sets, clearly display significant differences in their S/G composition which distinguish them from eucalypts. This research shows the power of using Raman spectroscopy to supplant tedious, destructive methods for the evaluation of the lignin S/G ratio of diverse plant biomass materials. © 2015, The Author(s).

Pasture production and composition response after killing Eucalypt trees with herbicides in central Queensland

Clearing woodlands is practised world-wide to increase crop and livestock production, but can result in unintended consequences including woody regrowth and land degradation. The pasture response of 2 eucalypt woodlands in the central Queensland rangelands to killing trees with herbicides, in the presence or absence of grazing and regular spring burning, was recorded over 7 or 8 years to determine the long-term sustainability of these common practices. Herbage mass and species composition plus tree dynamics were monitored in 2 replicated experiments at each site. For 8 years following herbicide application, killing Eucalyptus populnea F. Muell. (poplar box) trees resulted in a doubling of native pasture herbage mass from that of the pre-existing woodland, with a tree basal area of 8.7 m2 ha-1. Conversely, over 7 years with a similar range of seasons, killing E. melanophloia F. Muell. (silver-leaved ironbark) trees of a similar tree basal area had little impact on herbage mass grown or on pasture composition for the first 4 years before production then increased. Few consistent changes in pasture composition were recorded after killing the trees, although there was an increase in the desirable grasses Dichanthium sericeum (R. Br.) A. Camus (Queensland bluegrass) and Themeda triandra Forssk. (kangaroo grass) when grazed conservatively. Excluding grazing allowed more palatable species of the major grasses to enhance their prominence, but seasonal conditions still had a major influence on their production in particular years. Pasture crown basal area was significantly higher where trees had been killed, especially in the poplar box woodland. Removing tree competition did not have a major effect on pasture composition that was independent of other management impositions or seasons, and it did not result in a rapid increase in herbage mass in both eucalypt communities. The slow pasture response to tree removal at one site indicates that regional models and economic projections relating to tree clearing require community-specific inputs.

Topographical map of Jersey City, Hoboken, and the adjacent country : describing minutely the courses of rivers and brooks, the township and original patent lines, railways, turnpike, carriage and bridle roads, the present farm boundaries with the names of their proprietors : a correct plan of public grounds and gentlemen's country seats, the position of farm houses, forests, swamps, and marshes, showing a complete view of the face of the country /

Shows cadastral and topographic data (land tracts with proprietors' names) in unurbanized areas.

Resources of the southern fields and forests, medical, economical, and agricultural : being also a medical botany of the Confederate States; with practical information on the useful properties of the trees, plants and shrubs /

RBC donor (copy 2): Ernest Haywood Collection.

Dendroecology of Aspidosperma polyneuron Müll. Arg. (Apocynaceae) trees in two different geomorphological growth conditions in Atlantic forests, Paraná State, Brazil.

2016

Dendroecology of Drimys brasiliensis Miers (Winteraceae) in two Atlantic cloud forests in Paraná State, Southern Brazil.

2016

Classification of plant communities, structure and diversity of forests in Acre, Brazil.

2016

Climate seasonality limits leaf carbon assimilation and wood productivity in tropical forests.

The seasonal climate drivers of the carbon cy- cle in tropical forests remain poorly known, although these forests account for more carbon assimilation and storage than any other terrestrial ecosystem. Based on a unique combina- tion of seasonal pan-tropical data sets from 89 experimental sites (68 include aboveground wood productivity measure- ments and 35 litter productivity measurements), their asso- ciated canopy photosynthetic capacity (enhanced vegetation index, EVI) and climate, we ask how carbon assimilation and aboveground allocation are related to climate seasonal- ity in tropical forests and how they interact in the seasonal carbon cycle. We found that canopy photosynthetic capacity seasonality responds positively to precipitation when rain- fall is < 2000 mm yr-1 (water-limited forests) and to radia- tion otherwise (light-limited forests). On the other hand, in- dependent of climate limitations, wood productivity and lit- terfall are driven by seasonal variation in precipitation and evapotranspiration, respectively. Consequently, light-limited forests present an asynchronism between canopy photosyn- thetic capacity and wood productivity. First-order control by precipitation likely indicates a decrease in tropical forest pro- ductivity in a drier climate in water-limited forest, and in cur- rent light-limited forest with future rainfall < 2000 mm yr-1.

A methodological framework to assess the carbon balance of tropical managed forests.

Background: Managed forests are a major component of tropical landscapes. Production forests as designated by national forest services cover up to 400 million ha, i.e. half of the forested area in the humid tropics. Forest management thus plays a major role in the global carbon budget, but with a lack of unified method to estimate carbon fluxes from tropical managed forests. In this study we propose a new time- and spatially-explicit methodology to estimate the above-ground carbon budget of selective logging at regional scale. Results: The yearly balance of a logging unit, i.e. the elementary management unit of a forest estate, is modelled by aggregating three sub-models encompassing (i) emissions from extracted wood, (ii) emissions from logging damage and deforested areas and (iii) carbon storage from post-logging recovery. Models are parametrised and uncertainties are propagated through a MCMC algorithm. As a case study, we used 38 years of National Forest Inventories in French Guiana, northeastern Amazonia, to estimate the above-ground carbon balance (i.e. the net carbon exchange with the atmosphere) of selectively logged forests. Over this period, the net carbon balance of selective logging in the French Guianan Permanent Forest Estate is estimated to be comprised between 0.12 and 1.33 Tg C, with a median value of 0.64 Tg C. Uncertainties over the model could be diminished by improving the accuracy of both logging damage and large woody necromass decay submodels. Conclusions: We propose an innovating carbon accounting framework relying upon basic logging statistics. This flexible tool allows carbon budget of tropical managed forests to be estimated in a wide range of tropical regions

Machine learning per l'idrologia: applicazione del metodo random forests per la previsione degli eventi di piena fluviale con un approccio probabilistico

Le tecniche di Machine Learning sono molto utili in quanto consento di massimizzare l’utilizzo delle informazioni in tempo reale. Il metodo Random Forests può essere annoverato tra le tecniche di Machine Learning più recenti e performanti. Sfruttando le caratteristiche e le potenzialità di questo metodo, la presente tesi di dottorato affronta due casi di studio differenti; grazie ai quali è stato possibile elaborare due differenti modelli previsionali. Il primo caso di studio si è incentrato sui principali fiumi della regione Emilia-Romagna, caratterizzati da tempi di risposta molto brevi. La scelta di questi fiumi non è stata casuale: negli ultimi anni, infatti, in detti bacini si sono verificati diversi eventi di piena, in gran parte di tipo “flash flood”. Il secondo caso di studio riguarda le sezioni principali del fiume Po, dove il tempo di propagazione dell’onda di piena è maggiore rispetto ai corsi d’acqua del primo caso di studio analizzato. Partendo da una grande quantità di dati, il primo passo è stato selezionare e definire i dati in ingresso in funzione degli obiettivi da raggiungere, per entrambi i casi studio. Per l’elaborazione del modello relativo ai fiumi dell’Emilia-Romagna, sono stati presi in considerazione esclusivamente i dati osservati; a differenza del bacino del fiume Po in cui ai dati osservati sono stati affiancati anche i dati di previsione provenienti dalla catena modellistica Mike11 NAM/HD. Sfruttando una delle principali caratteristiche del metodo Random Forests, è stata stimata una probabilità di accadimento: questo aspetto è fondamentale sia nella fase tecnica che in fase decisionale per qualsiasi attività di intervento di protezione civile. L'elaborazione dei dati e i dati sviluppati sono stati effettuati in ambiente R. Al termine della fase di validazione, gli incoraggianti risultati ottenuti hanno permesso di inserire il modello sviluppato nel primo caso studio all’interno dell’architettura operativa di FEWS.