Automated conservation assessment of the orchid family with deep learning

International Union for Conservation of Nature (IUCN) Red List assessments are essential for prioritizing conservation needs but are resource intensive and therefore available only for a fraction of global species richness. Automated conservation assessments based on digitally available geographic occurrence records can be a rapid alternative, but it is unclear how reliable these assessments are. We conducted automated conservation assessments for 13,910 species (47.3% of the known species in the family) of the diverse and globally distributed orchid family (Orchidaceae), for which most species (13,049) were previously unassessed by IUCN. We used a novel method based on a deep neural network (IUC-NN). We identified 4,342 orchid species (31.2% of the evaluated species) as possibly threatened with extinction (equivalent to IUCN categories critically endangered [CR], endangered [EN], or vulnerable [VU]) and Madagascar, East Africa, Southeast Asia, and several oceanic islands as priority areas for orchid conservation. Orchidaceae provided a model with which to test the sensitivity of automated assessment methods to problems with data availability, data quality, and geographic sampling bias. The IUC-NN identified possibly threatened species with an accuracy of 84.3%, with significantly lower geographic evaluation bias relative to the IUCN Red List and was robust even when data availability was low and there were geographic errors in the input data. Overall, our results demonstrate that automated assessments have an important role to play in identifying species at the greatest risk of extinction.     

Global protected-area coverage and human pressure on tidal flats

Tidal flats are a globally distributed coastal ecosystem important for supporting biodiversity and ecosystem services. Local to continental-scale studies have documented rapid loss of tidal habitat driven by human impacts, but assessments of progress in their conservation are lacking. With an internally consistent estimate of distribution and change, based on Landsat satellite imagery, now available for the world's tidal flats, we examined tidal flat representation in protected areas (PAs) and human pressure on tidal flats. We determined tidal flat representation and its net change in PAs by spatially overlaying tidal flat maps with the World Database of Protected Areas. Similarly, we overlaid the most recent distribution map of tidal flats (2014–2016) with the human modification map (HM_c) (range from 0, no human pressure, to 1, very high human pressure) to estimate the human pressure exerted on this ecosystem. Sixty-eight percent of the current extent of tidal flats is subject to moderate to very high human pressure (HM_c > 0.1), but 31% of tidal flat extent occurred in PAs, far exceeding PA coverage of the marine (6%) and terrestrial (13%) realms. Net change of tidal flat extent inside PAs was similar to tidal flat net change outside PAs from 1999 to 2016. Substantial shortfalls in protection of tidal flats occurred across Asia, where large intertidal extents coincided with high to very high human pressure (HM_c > 0.4–1.0) and net tidal flat losses up to 86.4 km² (95% CI 83.9–89.0) occurred inside individual PAs in the study period. Taken together, our results show substantial progress in PA designation for tidal flats globally, but that PA status alone does not prevent all habitat loss. Safeguarding the world's tidal flats will thus require deeper understanding of the factors that govern their dynamics and effective policy that promotes holistic coastal and catchment management strategies.     

The bean method as a tool to measure sensitive behavior

Conservationists need to measure human behavior to guide decisions and evaluate their impact. However, activities can be misreported and reporting accuracy may change following conservation interventions, making it hard to verify any apparent changes. Techniques for asking sensitive questions are increasingly integrated into survey designs to improve data quality, but some can be costly or hard for nonexperts to implement. We demonstrate a straightforward, low-cost approach, the bean method in which respondents give anonymous answers by adding a colored bean to a jar to denote a yes or no response. We applied the bean method to measure wild-meat hunting and trading over 2 years at a conservation-project (hunting reduction) site in Gola Forest, Liberia. We extended the technique to accommodate questions about hunting and meat-selling frequency. We compared responses given using the bean method and direct questioning for groups that did and did not participate in conservation interventions. Results from the bean method corresponded to those from direct questioning, and there was no indication of change in question sensitivity following conservation interventions. Estimates from both methods indicated that wild-meat trading decreased in project and nonproject households (from 36% to 20%) and that hunting decreased in 1 project group (38–28%). Where inconsistent answers were given (2–6% of respondents), differences were in both directions and were most likely attributable to measurement error. The bean method was quick and straightforward to administer in a low-literacy setting. We showed how it can be modified for answers of more than 2 categories and consider it a valuable tool that could be adapted for a wide range of conservation settings.     

How expert insight into alpine peatland conservation complements global scientific evidence

Experts can provide valuable information to fill knowledge gaps in published research on management effectiveness, particularly for threatened ecosystems, for which there is often limited evidence and the need for prompt intervention to ensure their persistence. One such ecosystem, alpine peatland, is threatened by climate change and other pressures, provides vital ecosystem services, and supports unique biodiversity. In a workshop, we gathered and synthesized into an accessible format information from experts on interventions used, threat context, and intervention effectiveness for Australian alpine peatland and used this knowledge to evaluate local relevance of the global literature for this threatened ecosystem. Experts identified 15 interventions used to conserve Australian peatlands, most of which enhanced or restored peatland condition and effectively addressed diverse threats. Experts’ perspectives and global studies were strongly aligned, suggesting that research on peatland management may be broadly relevant across contexts, despite the distinct characteristics of Australian systems. Our workshop-based expert elicitation approach provided insights into current management practices unavailable in the literature.     

Same stimuli,different responses: a pilot study assessing air pollution visibility impacts on emotional well-being in a controlled environment

● Emotional responses to visibility-reducing haze was assessed in a controlled lab. ● Valence and arousal have non-linear responses to pollution-caused low visibility. ● Repetitive exposure aggravates negative emotions in severely polluted conditions. ● Emotional bias to pollution relates with gender, decisiveness, attitude to clean air. A growing number of studies have shown that impaired visibility caused by particulate matter pollution influences emotional wellbeing. However, evidence is still scant on how this effect varies across individuals and over repetitive visual exposure in a controlled environment. Herein, we designed a lab-based experiment (41 subjects, 6 blocks) where participants were presented with real-scene images of 12 different PM_2.5 concentrations in each block. Emotional valence (negative to positive) and arousal (calm to excited) were self-rated by participants per image, and the response time for each rating was recorded. We find that as pollution level increases from 10 to 260 µg/m³, valence scores decrease, whereas arousal scores decline first and then bounce back, following a U-shaped trend. When air quality deteriorates, individual variability decreases in hedonic valence but increases in arousal. Over blocks, repetitive visual exposure increases valence at a moderate pollution level but aggravates negative emotions in severely polluted conditions (> 150 µg/m³). Finally, we find females, people who are slow in making responses, and those who are highly aroused by clean air tend to express more negative responses (so-called negativity bias) to ambient pollution than their respective counterparts. These results provide deeper insights into individual-level emotional responses to dirty air in a controlled environment. Although the findings in our pilot study should only be directly applied to the conditions assessed herein, we introduce a framework that can be replicated in different regions to assess the impact of air pollution on local emotional wellbeing.     

Objectively best or most acceptable? Expert and lay knowledge in Swedish wind power permit processes

This article analyses legal aspects of the Swedish wind power development, theoretically based on how different types of knowledge are represented in legal contexts, mainly in the courts. A sample of appealed wind power permits is analysed, a handful of relevant informants are interviewed – including two judges in the Land and Environment Court and the appeal court – and the legal setting is analysed. Of key interest here is the interplay between expert and lay statements in the court cases, which here is related to the concepts of calculating and communicative rationalities that are developed in the planning literature. The results indicate that the juridification – which takes place as a permit issue is appealed in the judiciary system – supports the calculating rationality more than the communicative, and that the plaintiffs often attempt to adapt in how they shape their argumentation.     

Overcoming Endpoint Bias in Climate Change Communication: The Case of Arctic Sea Ice Trends

Unusually cold winters, a slowing in upward global temperatures, or an increase in Arctic sea ice extent are often falsely cast as here-and-now disconfirmation of the scientific consensus on climate change. Such conclusions are examples of “end point bias,” the well documented psychological tendency to interpret a recent short-term fluctuation as a reversal of a long-term trend. End point bias poses a challenge to those trying to communicate cross-decade climate warming trends. In this study, we demonstrate that exposure to misleading scientific information on FoxNews.com that evokes end point bias can affect the beliefs of liberals and moderates as well as conservatives. We also show that the leveraging-involving-visualizing-analogizing communication model can reduce the effects of endpoint bias among moderates and liberals at the same time as it dampens both the ideological and endpoint biasing of conservatives.     

小净距偏压隧道在特殊素填土施工顺序研究

在较特殊素填土中,为能更好地确定在相同的施工方法下,不同的施工顺序对改善隧道围岩变形和衬砌内力的影响,文章重点以重庆曾家岩浅埋暗挖隧道为依托,运用二维数值模拟分析,研究在特殊回填土下,隧道不同施工顺序引起的围岩变形、衬砌内力变化、塑性区分布规律.从数值模拟结果可以看出,不同施工顺序下,围岩变形、衬砌内力、塑性区分布存在...     

灾害地貌专家系统试验研究

介绍了灾害地貌专家的建造原理与方法,阐述了灾害地貌专家知识的分类分级方法,讨论了灾害地貌专家系统中知识表示的基本原则和知识库中专家知识的组织方式,以及推理机的设计和推理规则的构造原理与方法。系统采用压缩编码方式存储各种地学专题图形和遥感图像数据,具有与图像的存储更新,查询检索、分析处理、图像显少自动制图功能。该系统可以对灾害地貌过程进行专家级的预测和评价,并对灾害地貌的综合治理与区域规划提出几种可     

装备安全管理框架和量化评价方法研究

目的实现安全管理的量化评估。方法对安全管理内容进行分析,提出安全项目、管理要求、事故内容和对策措施的确定准则,并以此为基础描述管理框架构建流程。利用专家打分法,对安全项目的权重进行了确定,并以管理要求执行情况为依据,提出量化评分方法,实现安全管理水平的定量评价。结果以某装备为例,通过专家打分法计算,得到了科学结果,说明了安全管理框架和量化评价的适用性。结论利用专家判别打分模型,可以对安全管理框架中的安全项目权重和管理要求完成情况进行定量评价,综合给出安全管理工作的评分,从而实现安全管理的量化评估。