A multi-plot assessment of vegetation structure using a micro-unmanned aerial system (UAS) in a semi-arid savanna environment.

Unmanned Aerial Systems (UAS) have emerged as a capable platform for measuring vegetation health, structure and productivity. Products derived from UAS imagery typically have much finer spatial resolutions than traditional satellite or aircraft imagery, allowing the spectral and structural heterogeneity of vegetation to be mapped and monitored with more detail. This study uses UAS-captured imagery from the Chobe Enclave of northern Botswana. Flights were conducted across a gradient of savanna sites classified as grass-, shrub-, or tree-dominated. We compare multiple approaches for extracting woody vegetation structure from UAS imagery and assess correlations between in situ field measurements and UAS estimates. Sensor types were also compared, to determine whether multispectral data improves estimates of vegetation structure at the expense of spatial resolution. We found that leveraging multispectral reflectance information aids in crown delineation, areal estimates, and fractional cover of woody and non-woody vegetation within the study area. Comparisons are made between two crown delineation techniques, and the efficacy of each technique within savanna environments is discussed. The methods presented hold potential to inform field sampling protocols and UAS-based techniques for autonomous crown delineation in future dryland systems research. These findings advance research for field and remote sensing analyses assessing degradation in heterogeneous landscapes where varying vegetation structure has implications on land use and land functions

Modeling Community-Scale Natural Resource Use in a Transboundary Southern African Landscape: Integrating Remote Sensing and Participatory Mapping

Remote sensing analyses focused on non-timber forest product (NTFP) collection and grazing are current research priorities of land systems science. However, mapping these particular land use patterns in rural heterogeneous landscapes is challenging because their potential signatures on the landscape cannot be positively identified without fine-scale land use data for validation. Using field-mapped resource areas and household survey data from participatory mapping research, we combined various Landsat-derived indices with ancillary data associated with human habitation to model the intensity of grazing and NTFP collection activities at 100-m spatial resolution. The study area is situated centrally within a transboundary southern African landscape that encompasses community-based organization (CBO) areas across three countries. We conducted four iterations of pixel-based random forest models, modifying the variable set to determine which of the covariates are most informative, using the best fit predictions to summarize and compare resource use intensity by resource type and across communities. Pixels within georeferenced, field-mapped resource areas were used as training data. All models had overall accuracies above 60% but those using proxies for human habitation were more robust, with overall accuracies above 90%. The contribution of Landsat data as utilized in our modeling framework was negligible, and further research must be conducted to extract greater value from Landsat or other optical remote sensing platforms to map these land use patterns at moderate resolution. We conclude that similar population proxy covariates should be included in future studies attempting to characterize communal resource use when traditional spectral signatures do not adequately capture resource use intensity alone. This study provides insights into modeling resource use activity when leveraging both remotely sensed data and proxies for human habitation in heterogeneous, spectrally mixed rural land areas &nbsp;</p

Using Very-High-Resolution Multispectral Classification to Estimate Savanna Fractional Vegetation Components

Characterizing compositional and structural aspects of vegetation is critical to effectively assessing land function. When priorities are placed on ecological integrity, remotely sensed estimates of fractional vegetation components (FVCs) are useful for measuring landscape-level habitat structure and function. In this study, we address whether FVC estimates, stratified by dominant vegetation type, vary with different classification approaches applied to very-high-resolution small unoccupied aerial system (UAS)-derived imagery. Using Parrot Sequoia imagery, flown on a DJI Mavic Pro micro-quadcopter, we compare pixel- and segment-based random forest classifiers alongside a vegetation height-threshold model for characterizing the FVC in a southern African dryland savanna. Results show differences in agreement between each classification method, with the most disagreement in shrub-dominated sites. When compared to vegetation classes chosen by visual identification, the pixel-based random forest classifier had the highest overall agreement and was the only classifier not to differ significantly from the hand-delineated FVC estimation. However, when separating out woody biomass components of tree and shrub, the vegetation height-threshold performed better than both random-forest approaches. These findings underscore the utility and challenges represented by very-high-resolution multispectral UAS-derived data (~10 cm ground resolution) and their uses to estimate FVC. Semi-automated approaches statistically differ from by-hand estimation in most cases; however, we present insights for approaches that are applicable across varying vegetation types and structural conditions. Importantly, characterization of savanna land function cannot rely only on a &ldquo;greenness&rdquo; measure but also requires a structural vegetation component. Underscoring these insights is that the spatial heterogeneity of vegetation structure on the landscape broadly informs land management, from land allocation, wildlife habitat use, natural resource collection, and as an indicator of overall ecosystem function

Fungal planet description sheets: 716–784

Novel species of fungi described in this study include those from various countries as follows: Australia, Chaetopsina eucalypti on Eucalyptus leaf litter, Colletotrichum cobbittiense from Cordyline stricta × C. australis hybrid, Cyanodermella banksiae on Banksia ericifolia subsp. macrantha, Discosia macrozamiae on Macrozamia miquelii, Elsinoë banksiigena on Banksia marginata, Elsinoë elaeocarpi on Elaeocarpus sp., Elsinoë leucopogonis on Leucopogon sp., Helminthosporium livistonae on Livistona australis, Idriellomyces eucalypti (incl. Idriellomyces gen. nov.) on Eucalyptus obliqua, Lareunionomyces eucalypti on Eucalyptus sp., Myrotheciomyces corymbiae (incl. Myrotheciomyces gen. nov., Myrotheciomycetaceae fam. nov.), Neolauriomyces eucalypti (incl. Neolauriomyces gen. nov., Neolauriomycetaceae fam. nov.) on Eucalyptus sp., Nullicamyces eucalypti (incl. Nullicamyces gen. nov.) on Eucalyptus leaf litter, Oidiodendron eucalypti on Eucalyptus maidenii, Paracladophialophora cyperacearum (incl. Paracladophialophoraceae fam. nov.) and Periconia cyperacearum on leaves of Cyperaceae, Porodiplodia livistonae (incl. Porodiplodia gen. nov., Porodiplodiaceae fam. nov.) on Livistona australis, Sporidesmium melaleucae (incl. Sporidesmiales ord. nov.) on Melaleuca sp., Teratosphaeria sieberi on Eucalyptus sieberi, Thecaphora aus-traliensis in capsules of a variant of Oxalis exilis. Brazil, Aspergillus serratalhadensis from soil, Diaporthe pseudo-inconspicua from Poincianella pyramidalis, Fomitiporella pertenuis on dead wood, Geastrum magnosporum on soil, Marquesius aquaticus (incl. Marquesius gen. nov.) from submerged decaying twig and leaves of unidentified plant, Mastigosporella pigmentata from leaves of Qualea parviflorae, Mucor souzae from soil, Mycocalia aquaphila on decaying wood from tidal detritus, Preussia citrullina as endophyte from leaves of Citrullus lanatus, Queiroziella brasiliensis (incl. Queiroziella gen. nov.) as epiphytic yeast on leaves of Portea leptantha, Quixadomyces cearen-sis (incl. Quixadomyces gen. nov.) on decaying bark, Xylophallus clavatus on rotten wood. Canada, Didymella cari on Carum carvi and Coriandrum sativum. Chile, Araucasphaeria foliorum (incl. Araucasphaeria gen. nov.) on Araucaria araucana, Aspergillus tumidus from soil, Lomentospora valparaisensis from soil. Colombia, Corynespora pseudocassiicola on Byrsonima sp., Eucalyptostroma eucalyptorum on Eucalyptus pellita, Neometulocladosporiella eucalypti (incl. Neometulocladosporiella gen. nov.) on Eucalyptus grandis × urophylla, Tracylla eucalypti (incl. Tracyllaceae fam. nov., Tracyllalales ord. nov.) on Eucalyptus urophylla. Cyprus, Gyromitra anthracobia (incl. Gyromitra subg. Pseudoverpa) on burned soil. Czech Republic, Lecanicillium restrictum from the surface of the wooden barrel, Lecanicillium testudineum from scales of Trachemys scripta elegans. Ecuador, Entoloma yanacolor and Saproamanita quitensis on soil. France, Lentithecium carbonneanum from submerged decorticated Populus branch. Hungary, Pleuromyces hungaricus (incl. Pleuromyces gen. nov.) from a large Fagus sylvatica log. Iran, Zymoseptoria crescenta on Aegilops triuncialis. Malaysia, Ochroconis musicola on Musa sp. Mexico, Cladosporium michoacanense from soil. New Zealand, Acrodontium metrosideri on Metrosideros excelsa, Polynema podocarpi on Podocarpus totara, Pseudoarthrographis phlogis (incl. Pseudoarthrographis gen. nov.) on Phlox subulata. Nigeria, Coprinopsis afrocinerea on soil. Pakistan, Russula mansehraensis on soil under Pinus roxburghii. Russia, Baoran­ gia alexandri on soil in deciduous forests with Quercus mongolica. South Africa, Didymocyrtis brachylaenae on Brachylaena discolor. Spain, Alfaria dactylis from fruit of Phoenix dactylifera, Dothiora infuscans from a blackened wall, Exophiala nidicola from the nest of an unidentified bird, Matsushimaea monilioides from soil, Terfezia morenoi on soil. United Arab Emirates, Tirmania honrubiae on soil. USA, Arxotrichum wyomingense (incl. Arxotrichum gen. nov.) from soil, Hongkongmyces snookiorum from submerged detritus from a fresh water fen, Leratiomyces tesquorum from soil, Talaromyces tabacinus on leaves of Nicotiana tabacum. Vietnam, Afroboletus vietnamensis on soil in an evergreen tropical forest, Colletotrichum condaoense from Ipomoea pes-caprae. Morphological and culture characteristics along with DNA barcodes are provided. © 2018 Naturalis Biodiversity Center & Westerdijk Fungal Biodiversity Institute