Losses of natural and semi-natural forests, mostly to agriculture, are a significant concern for biodiversity. Against this trend, the area of intensively managed plantation forests increases, and there is much debate about the implications for biodiversity. We provide a comprehensive review of the function of plantation forests as habitat compared with other land cover, examine the effects on biodiversity at the landscape scale, and synthesise context-specific effects of plantation forestry on biodiversity. Natural forests are usually more suitable as habitat for a wider range of native forest species than plantation forests but there is abundant evidence that plantation forests can provide valuable habitat, even for some threatened and endangered species, and may contribute to the conservation of biodiversity by various mechanisms. In landscapes where forest is the natural land cover, plantation forests may represent a low-contrast matrix, and afforestation of agricultural land can assist conservation by providing complementary forest habitat, buffering edge effects, and increasing connectivity. In contrast, conversion of natural forests and afforestation of natural non-forest land is detrimental. However, regional deforestation pressure for agricultural development may render plantation forestry a ‘lesser evil’ if forest managers protect indigenous vegetation remnants. We provide numerous context-specific examples and case studies to assist impact assessments of plantation forestry, and we offer a range of management recommendations. This paper also serves as an introduction and background paper to this special issue on the effects of plantation forests on biodiversity.

Plantation Forests and Biodiversity: Oxymoron or Opportunity?

Abstract High‐resolution monitoring is fundamental to understand ecosystems dynamics in an era of global change and biodiversity declines. While real‐time and automated monitoring of abiotic components has been possible for some time, monitoring biotic components—for example, individual behaviours and traits, and species abundance and distribution—is far more challenging. Recent technological advancements offer potential solutions to achieve this through: (i) increasingly affordable high‐throughput recording hardware, which can collect rich multidimensional data, and (ii) increasingly accessible artificial intelligence approaches, which can extract ecological knowledge from large datasets. However, automating the monitoring of facets of ecological communities via such technologies has primarily been achieved at low spatiotemporal resolutions within limited steps of the monitoring workflow. Here, we review existing technologies for data recording and processing that enable automated monitoring of ecological communities. We then present novel frameworks that combine such technologies, forming fully automated pipelines to detect, track, classify and count multiple species, and record behavioural and morphological traits, at resolutions which have previously been impossible to achieve. Based on these rapidly developing technologies, we illustrate a solution to one of the greatest challenges in ecology: the ability to rapidly generate high‐resolution, multidimensional and standardised data across complex ecologies.

/pdf/towards-the-fully-automated-monitoring-of-ecological-5ic7wjfa.pdf

Towards the fully automated monitoring of ecological communities

Projected shifts in the distribution range of Asiatic black bear (Ursus thibetanus) in the Hindu Kush Himalaya due to climate change

Approximately 20%-30% of plant and animal species are at risk of extinction by the end of the 21st century owing to climate change. Range shifts and range contractions in plant species will dramatically affect the distribution of animals relying on them for food and shelter. The negative impacts of climate change on forested landscapes of the northern highlands of Pakistan (NHP) could change the species composition and distribution. The Asiatic black bear (Ursus thibetanus), a forest-dwelling species, primarily depends on plants for foraging, and is assumed to be affected by climate change in NHP. Scat analyses and indigenous knowledge from Machiara National Park revealed the maximum consumption of Quercus species (natural food) and Zea mays (human grown food) by the Asiatic black bear in autumn season. We collected the occurrence data of the Asiatic black bear and its commonly used food (three Quercus spp.) in the NHP. We used the MaxEnt model to simulate current and future (in 2050 and 2070) distribution of the species under RCP4.5 (medium carbon emission scenario) and RCP8.5 (extreme carbon emission scenario). The results predict range reduction and extreme fragmentation in the habitats of all the Quercus spp. Besides, a dramatic decrease in the suitable (SH) and very highly suitable (HSH) habitats was predicted in the future. Range shift and range reduction of Quercus spp. may interrupt the denning chronology of Asiatic black bears, escalate the human-black bear conflicts and local extirpation of the species. Given the extent and magnitude of climate change, it will likely not be enough to focus solely on the conservation of the Asiatic black bear. We need more dynamic planning aiming at mitigating the effect of climate change in forested landscapes including the Quercus forests.

Impact of climate change on Asiatic black bear (Ursus thibetanus) and its autumn diet in the northern highlands of Pakistan.

Vegetation restoration potential mapping (VRPM) is of great importance for regional ecosystem restoration planning after long‐term land degradation or short‐term disasters. However, there are some problems to be solved in the current models for evaluating the potential of vegetation restoration. First, the models for VRPM are mostly established based on a knowledge‐driven index system. Although this kind of model is logically rigorous, it relies too much on expert knowledge and is relatively inefficient, especially for large‐area vegetation restoration assessments. Second, because of the spatial heterogeneity, as well as the absence of important indicators, the traditional global‐based evaluation models are difficult to adapt to the entire study area. In this study, an improved data‐driven approach, that is, a sliding‐window based similar habitat potential model, is developed for VRPM. The advantages of the new model include: (a) it is more efficient in determining the importance of each influencing factor without resorting to expert knowledge; (b) it is more locally adaptive than the global model because it performs sample training, rule building, and vegetation restoration potential calculation in each current local window. We provide a case‐study to show the modeling process and result interpretation of the new model.

A novel similar habitat potential model based on sliding‐window technique for vegetation restoration potential mapping

Animal diversity responding to different forest restoration schemes in the Qinling Mountains, China

The study of activity patterns is important for understanding the capacity of animals for adapting their behavior based on their habitat conditions. Among bears, daily activity patterns are considered to be strongly influenced by regional climate conditions. We monitored the activity patterns (active vs. inactive) of the Asiatic black bear (Ursus thibetanus) using infrared camera traps (from May 2013 to November 2016) in the Qinling Mountains, China. We used 125 photos, with 19,132 camera days from 55 camera locations. Based on relative independent capture (RIC), bears were found to be intensively active during June (5.86 ± 1.05 SE), July (8.45 ± 2.74), September (14.83 ± 6.13), and October (8.70 ± 3.43), with activity levels gradually decreasing beyond October. After this decline, activities eventually come to a halt when the bears enter in hibernation. We found that their hibernation period was shorter in the Qinling bears, with only 3 months of denning from January to March. Based on their daily patterns, bears were predominantly active during the daytime both in spring (70.83 ± 35.41%) and summer (52.09 ± 28.89%), but more active at twilight during autumn (51.12 ± 42.88%). We assumed that food preferences and food availability (due to warmer regional climatic conditions) might be responsible for such deviations in daily and monthly activity patterns.

Activity pattern study of Asiatic black bear (Ursus thibetanus) in the Qinling Mountains, China, by using infrared camera traps.

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Animal diversity responding to different forest restoration schemes in the Qinling Mountains, China

Activity pattern study of Asiatic black bear (Ursus thibetanus) in the Qinling Mountains, China, by using infrared camera traps.