Listening to Insect Agency: Reconsidering Relations Through Ecological Sound Art

Insects are vitally important to the survival of life on earth. Yet, in many western societies, humans have become quite averse to insects, and this is exacerbated by a narrative of fear, avoidance, and elimination. If we are to act on utilitarian evidence alone, insect decline caused by anthropogenic impacts makes it critically important to improve our relations with our insect kin. In this paper, we argue that listening to insects – and speculating as to how they listen – can move us towards relations based in curiosity, respect, and a recognition of their value. We present two works of ecological sound art that focus on cryptic insect sounds beyond the limits of human hearing ability: HVAC (2022) and Formiphony (2020). By foregrounding cryptic sound, we emphasize the vast unknown sound-worlds of insects in our shared environments. Through this expansion of our listening, we can recognize insect agency as expressed through decisions concerning their sonic relations. These works have been presented in performance, exhibits, lectures, radio, and albums, bringing a broad audience into conversation about our relations with insects

Listening to tropical forest soils

Acoustic monitoring has proven to be an effective tool for monitoring biotic soundscapes in the marine, terrestrial, and aquatic realms. Recently it has been suggested that it could also be an effective method for monitoring soil soundscapes, but has been used in very few studies, primarily in temperate and polar regions. We present the first study of soil soundscapes using passive acoustic monitoring in tropical forests, using a novel analytical pipeline allowing for the use of in-situ recording of soundscapes with minimal soil disturbance. We found significant differences in acoustic index values between burnt and unburnt forests and the first indications of a diel cycle in soil soundscapes. These promising results and methodological advances highlight the potential of passive acoustic monitoring for large-scale and long-term monitoring of soil biodiversity. We use the results to discuss research priorities, including relating soil biophony to community structure and ecosystem function, and the use of appropriate hardware and analytical techniques

TLR9 Signaling Suppresses the Canonical Plasma Cell Differentiation Program in Follicular B Cells

The relative potency and quality of mouse B cell response to Toll-like receptors (TLRs) signaling varies significantly depending on the B cell subset and on the TLR member being engaged. Although it has been shown that marginal zone cells respond faster than follicular (FO) splenic B cells to TLR4 stimulus, FO B cells retain full capacity to proliferate and generate plasmablasts and plasma cells (PBs/PCs) with 2–3 days delayed kinetics. It is not clear whether this scenario could be extended to other members of the TLR family. Here, using quantitative cell culture conditions optimized for B cell growth and differentiation, we show that TLR9 signaling by CpG, while promoting vigorous proliferation, completely fails to induce differentiation of FO B cells into PBs/PCs. Little or absent Ig secretion following TLR9 stimulus was accompanied by lack of expression of cell surface markers and canonical transcription factors involved in PB/PC differentiation. Moreover, not only TLR9 did not induce plasmocyte differentiation, but it also strongly inhibited the massive PB/PC differentiation of FO B cells triggered by LPS/TLR4. Our study reveals unexpected opposite roles for TLR4 and TLR9 in the control of plasma cell differentiation program and disagrees with previous conclusions obtained in high-density cultures conditions on the generation of plasmocytes by TRL9 signaling. The potential implications of these findings on the role of TLR9 in controlling self-tolerance, clonal sizes and regulation of humoral responses are discussed

The role of environmental filtering, geographic distance and dispersal barriers in shaping the turnover of plant and animal species in Amazonia

To determine the effect of rivers, environmental conditions, and isolation by distance on the distribution of species in Amazonia. Location: Brazilian Amazonia. Time period: Current. Major taxa studied: Birds, fishes, bats, ants, termites, butterflies, ferns + lycophytes, gingers and palms. We compiled a unique dataset of biotic and abiotic information from 822 plots spread over the Brazilian Amazon. We evaluated the effects of environment, geographic distance and dispersal barriers (rivers) on assemblage composition of animal and plant taxa using multivariate techniques and distance- and raw-data-based regression approaches. Environmental variables (soil/water), geographic distance, and rivers were associated with the distribution of most taxa. The wide and relatively old Amazon River tended to determine differences in community composition for most biological groups. Despite this association, environment and geographic distance were generally more important than rivers in explaining the changes in species composition. The results from multi-taxa comparisons suggest that variation in community composition in Amazonia reflects both dispersal limitation (isolation by distance or by large rivers) and the adaptation of species to local environmental conditions. Larger and older river barriers influenced the distribution of species. However, in general this effect is weaker than the effects of environmental gradients or geographical distance at broad scales in Amazonia, but the relative importance of each of these processes varies among biological groups

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Sustainability, Resilience, and the Contribution of Private Urban Gardens

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