Altitudinal treelines are typically temperature limited such that increasing temperatures linked to global climate change are causing upslope shifts of treelines worldwide. While such elevational increases are readily predicted based on shifting isotherms, at the regional level the realized response is often much more complex, with topography and local environmental conditions playing an important modifying role. Here, we used repeated aerial photographs in combination with forest inventory data to investigate changes in treeline position in the Central Mountain Range of Taiwan over the last 60 years. A highly spatially variable upslope advance of treeline was identified in which topography is a major driver of both treeline form and advance. The changes in treeline position that we observed occurred alongside substantial increases in forest density, and lead to a large increase in overall forest area. These changes will have a significant impact on carbon stocking in the high altitude zone, while the concomitant decrease in alpine grassland area is likely to have negative implications for alpine species. The complex and spatially variable changes that we report highlight the necessity for considering local factors such as topography when attempting to predict species distributional responses to warming climate.

Short-read next generation sequencing (NGS) platforms can easily and quickly generate thousands to hundreds of thousands of sequences per sample. However, the limited length of these sequences can cause problems during fungal taxonomic identification. Here we validate the use of Pacbio sequencing, a long-read NGS method, for characterizing the fungal community (mycobiome) of Castanopsis carlesii deadwood. We report the successful use of Pacbio sequencing to generate long-read sequences of the full-length (500–780 bp) fungal ITS regions of the C. carlesii mycobiome. Our results show that the studied deadwood mycobiome is taxonomically and functionally diverse, with an average of 85 fungal OTUs representing five functional groups (animal endosymbionts, endophytes, mycoparasites, plant pathogens, and saprotrophs). Based on relative abundance data, Basidiomycota were the most frequently detected phyla (50% of total sequences), followed by unidentified phyla, and Ascomycota. However, based on presence/absence data, the most OTU-rich phyla were Ascomycota (58% of total OTUs, 72 OTUs) followed by Basidiomycota and unidentified phyla. The majority of fungal OTUs were identified as saprotrophs (70% of successfully function-assigned OTUs) followed by plant pathogens. Finally, we used phylogenetic analysis based on the full-length ITS sequences to confirm the species identification of 14/36 OTUs with high bootstrap support (99–100%). Based on the numbers of sequence reads obtained per sample, which ranged from 3,047 to 13,463, we conclude that Pacbio sequencing can be a powerful tool for characterizing moderate- and possibly high-complexity fungal communities.

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BackgroundKeteleeria davidiana var. formosana (Pinaceae), Taiwan cow-tail fir, is an endangered species listed on the IUCN Red List of Threatened Species and only two populations remain, both on the Taiwan Island. Sixteen polymorphic microsatellite loci were developed in an endangered and endemic gymnosperm species, Keteleeria davidiana var. formosana, and were tested in an additional 6 taxa, K. davidiana var. calcarea, K. davidiana var. chienpeii, K. evelyniana, K. fortunei, K. fortunei var. cyclolepis, and K. pubescens, to evaluate the genetic variation available for conservation management and to reconstruct the phylogeographic patterns of this ancient lineage.FindingsPolymorphic primer sets were developed from K. davidiana var. formosana using the modified AFLP and magnetic bead enrichment method. The number of alleles ranged from 3 to 16, with the observed heterozygosity ranging from 0.28 to 1.00. All of the loci were found to be interspecifically amplifiable.ConclusionsThese polymorphic and transferable loci will be potentially useful for future studies that will focus on identifying distinct evolutionary units within species and establishing the phylogeographic patterns and the process of speciation among closely related species.

In general, considerable human and material resources are required for performing a forest inventory survey. Using remote sensing technologies to save forest inventory costs has thus become an important topic in forest inventory-related studies. Leica ADS-40 digital aerial photographs feature advantages such as high spatial resolution, high radiometric resolution, and a wealth of spectral information. As a result, they have been widely used to perform forest inventories. We classified ADS-40 digital aerial photographs according to the complex forest land cover types listed in the Fourth Forest Resource Survey in an effort to establish a classification method for categorizing ADS-40 digital aerial photographs. Subsequently, we classified the images using the knowledge-based classification method in combination with object-based analysis techniques, decision tree classification techniques, classification parameters such as object texture, shape, and spectral characteristics, a class-based classification method, and geographic information system mapping information. Finally, the results were compared with manually interpreted aerial photographs. Images were classified using a hierarchical classification method comprised of four classification levels (levels 1 to 4). The classification overall accuracy (OA) of levels 1 to 4 is within a range of 64.29% to 98.50%. The final result comparisons showed that the proposed classification method achieved an OA of 78.20% and a kappa coefficient of 0.7597. On the basis of the image classification results, classification errors occurred mostly in images of sunlit crowns because the image values for individual trees varied. Such a variance was caused by the crown structure and the incident angle of the sun. These errors lowered image classification accuracy and warrant further studies. This study corroborates the high feasibility for mapping complex forest land cover types using ADS-40 digital aerial photographs. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.