Landscape monitoring reveals initial trends in occupancy and activity of bats in multiple‐use forests

A successful and justified multiannual afforestation programme requires a good insight into the objectives and awareness of the constraints of the new forests, a planning strategy and a thorough research on the missing aspects. Socio-economic constraints mainly relate to social aspects of the farmers involved, who must be assured of a viable income. Therefore the new forest types and silvicultural systems should produce a reasonable return, without neglecting however the global multiple use objective. Planning has to deal with specific goals, the area of new forests, the location and size, accompanying measures and a time scale.

Spatial Fidelity of Plant, Vertebrate, and Invertebrate Assemblages in Multiple-Use Forest in Eastern Australia

Conservation Biology ◽

10.1046/j.1523-1739.1998.97075.x ◽

1998 ◽

Vol 12 (4) ◽

pp. 822-835 ◽

Cited By ~ 103

Author(s):

Ian Oliver ◽

Andrew J. Beattie ◽

Alan York

Keyword(s):

Multiple Use ◽

Eastern Australia ◽

Invertebrate Assemblages

Drivers of Bornean Orangutan Distribution across a Multiple-Use Tropical Landscape

Remote Sensing ◽

10.3390/rs13030458 ◽

2021 ◽

Vol 13 (3) ◽

pp. 458

Author(s):

Sol Milne ◽

Julien G. A. Martin ◽

Glen Reynolds ◽

Charles S. Vairappan ◽

Eleanor M. Slade ◽

...

Keyword(s):

Forest Cover ◽

Food Resource ◽

Multiple Use ◽

Natural Forests ◽

Bornean Orangutan ◽

Aerial Surveys ◽

Significant Difference ◽

The Difference ◽

Fig Trees ◽

Abundance And Distribution

Logging and conversion of tropical forests in Southeast Asia have resulted in the expansion of landscapes containing a mosaic of habitats that may vary in their ability to sustain local biodiversity. However, the complexity of these landscapes makes it difficult to assess abundance and distribution of some species using ground-based surveys alone. Here, we deployed a combination of ground-transects and aerial surveys to determine drivers of the critically endangered Bornean Orangutan (Pongo pygmaeus morio) distribution across a large multiple-use landscape in Sabah, Malaysian Borneo. Ground-transects and aerial surveys using drones were conducted for orangutan nests and hemi-epiphytic strangler fig trees (Ficus spp.) (an important food resource) in 48 survey areas across 76 km2, within a study landscape of 261 km2. Orangutan nest count data were fitted to models accounting for variation in land use, above-ground carbon density (ACD, a surrogate for forest quality), strangler fig density, and elevation (between 117 and 675 m). Orangutan nest counts were significantly higher in all land uses possessing natural forest cover, regardless of degradation status, than in monoculture plantations. Within these natural forests, nest counts increased with higher ACD and strangler fig density, but not with elevation. In logged forest (ACD 14–150 Mg ha−1), strangler fig density had a significant, positive relationship with orangutan nest counts, but this relationship disappeared in a forest with higher carbon content (ACD 150–209 Mg ha−1). Based on an area-to-area comparison, orangutan nest counts from ground transects were higher than from counts derived from aerial surveys, but this did not constitute a statistically significant difference. Although the difference in nest counts was not significantly different, this analysis indicates that both methods under-sample the total number of nests present within a given area. Aerial surveys are, therefore, a useful method for assessing the orangutan habitat use over large areas. However, the under-estimation of nest counts by both methods suggests that a small number of ground surveys should be retained in future surveys using this technique, particularly in areas with dense understory vegetation. This study shows that even highly degraded forests may be a suitable orangutan habitat as long as strangler fig trees remain intact after areas of forest are logged. Enrichment planting of strangler figs may, therefore, be a valuable tool for orangutan conservation in these landscapes.

PartSeg: a tool for quantitative feature extraction from 3D microscopy images for dummies

BMC Bioinformatics ◽

10.1186/s12859-021-03984-1 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Grzegorz Bokota ◽

Jacek Sroka ◽

Subhadip Basu ◽

Nirmal Das ◽

Pawel Trzaskoma ◽

...

Keyword(s):

Quantitative Analysis ◽

Cell Nucleus ◽

Ad Hoc ◽

Multiple Use ◽

Entry Barrier ◽

Multi Scale ◽

3D Microscopy ◽

Nuclear Structures ◽

Bulk Processing ◽

Microscopy Images

Abstract Background Bioimaging techniques offer a robust tool for studying molecular pathways and morphological phenotypes of cell populations subjected to various conditions. As modern high-resolution 3D microscopy provides access to an ever-increasing amount of high-quality images, there arises a need for their analysis in an automated, unbiased, and simple way. Segmentation of structures within the cell nucleus, which is the focus of this paper, presents a new layer of complexity in the form of dense packing and significant signal overlap. At the same time, the available segmentation tools provide a steep learning curve for new users with a limited technical background. This is especially apparent in the bulk processing of image sets, which requires the use of some form of programming notation. Results In this paper, we present PartSeg, a tool for segmentation and reconstruction of 3D microscopy images, optimised for the study of the cell nucleus. PartSeg integrates refined versions of several state-of-the-art algorithms, including a new multi-scale approach for segmentation and quantitative analysis of 3D microscopy images. The features and user-friendly interface of PartSeg were carefully planned with biologists in mind, based on analysis of multiple use cases and difficulties encountered with other tools, to offer an ergonomic interface with a minimal entry barrier. Bulk processing in an ad-hoc manner is possible without the need for programmer support. As the size of datasets of interest grows, such bulk processing solutions become essential for proper statistical analysis of results. Advanced users can use PartSeg components as a library within Python data processing and visualisation pipelines, for example within Jupyter notebooks. The tool is extensible so that new functionality and algorithms can be added by the use of plugins. For biologists, the utility of PartSeg is presented in several scenarios, showing the quantitative analysis of nuclear structures. Conclusions In this paper, we have presented PartSeg which is a tool for precise and verifiable segmentation and reconstruction of 3D microscopy images. PartSeg is optimised for cell nucleus analysis and offers multi-scale segmentation algorithms best-suited for this task. PartSeg can also be used for the bulk processing of multiple images and its components can be reused in other systems or computational experiments.