Ecology

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We observed a clear reduction in the acoustic activity of sperm whales and beaked whales during the period when sonar signals were recorded at Station 5, indicating that whales ceased foraging in this area while military sonars were in use. The acoustic detection rate of sperm whales returned to pre-exercise baseline levels within the days following the CF16 exercise, while the observed reduction in beaked whale acoustic activity was more prolonged. Detection rates of Cuvier’s beaked whale clicks remained low throughout the 8-day period immediately following the exercise, and UMBW clicks were largely absent during this period. This study is observational and limited to showing correlation rather than cause and effect; nonetheless, these results are consistent with previous experimental research on the responses of beaked whales to simulated and real military sonars and suggest that whales were disturbed from normal foraging behaviour and likely displaced from the affected area during the CF16 exercise.The scale and duration of sonar use recorded during this study provides important context for the observed results. Much of the experimental work conducted to date on the responses of beaked whales and other odontocetes to sonar has involved controlled exposure experiments using animal-borne tags to record the fine-scale movements and acoustic behavior of individuals, allowing responses to be examined on the scale of minutes to hours e.g.,7,8,10. Experimental exposures to simulated sonar signals lasting approximately 15–30 min have elicited pronounced avoidance responses in Blainville’s beaked whales7, Cuvier’s beaked whales8, Baird’s beaked whales16, and northern bottlenose whales9,10. Generally, these studies were focused on the onset of the response and did not always assess the duration over which altered behaviour continued. However, the absence of foraging behaviour for several hours following exposure was noted in some cases, and focal animals performed sustained directed movement away from the exposure location during this time, covering distances of up to tens of kilometers10. In broader-scale studies examining responses of Blainville’s beaked whales to real multi-ship naval training operations on the Atlantic Undersea Test and Evaluation Center (AUTEC) in the Bahamas, displacements of up to 68 km were observed, lasting 2–4 days before whales returned to foraging in the area where they were exposed7,28. In the present study, the duration of naval sonar activity recorded during the CF16 exercise was considerably more prolonged, with bouts of sonar continuing for up to 13 consecutive hours and occurring repeatedly over an 8-day period. Although we can only make inference on species-level rather than individual-level responses based on the absence of clicks in our recordings, it is plausible that military sonar activity at this scale led to wide spatial avoidance of the affected area over an extended period.The absence of sperm whale click detections in the Station 5 recordings for 6 consecutive days during the CF16 exercise is notable; few prior studies have demonstrated sustained changes in foraging behaviour or substantial displacement of sperm whales following sonar exposure. Behavioural response studies conducted in northern Norway using controlled experimental exposures showed varying responses by sperm whales, which included changes in orientation and direction of horizontal movement, changes in acoustic behaviour, and altered dive profiles23. Exposure to lower frequency sonar signals in the 1–2 kHz range generally prompted stronger responses, including a reduction in foraging effort or transition from a foraging to non-foraging state, while exposure to higher frequency sonar signals in the range of 6–7 kHz did not appear to trigger changes in foraging behaviour21,29. More recently, Isojunno et al.30 quantified the responses of sperm whales to continuous and pulsed active sonars, and found that sound exposure level was more important than amplitude in predicting a change in foraging effort. We were not able to investigate differential responses to frequency or other sonar characteristics in this study, due to the observational nature of the study and the absence of sperm whale clicks throughout most of the exercise period. Likewise, we cannot exclude the physical presence of ships, aircraft, and submarines in the area or additional types of noise produced during maneuvers as potential factors contributing to the cessation of sperm whale and beaked whale click production and foraging behaviour.The observed changes in acoustic activity were more easily quantified for sperm whales than for beaked whales, due to higher baseline hourly presence of sperm whale clicks in the recordings. Sperm whales produce powerful echolocation clicks throughout their foraging dives, which can be recorded at ranges of 16 km or more31, and a single individual foraging in the vicinity of a hydrophone may be detected continuously throughout multiple dive cycles. Our analysis was based on sperm whale click detections that met a threshold signal-to-noise ratio (SNR), and the results therefore provide a minimum estimate of sperm whale presence in the vicinity of the recorder. Reporting results at the level of hourly presence rather than the number of individual click detections largely mitigated the effects of excluding low-SNR clicks recorded at greater distances from the hydrophone or during higher ambient noise conditions. Likewise, the presence of sperm whales on an hourly time scale is not likely to be substantially underestimated when recordings are collected using a low duty cycle32. By contrast, beaked whales produce echolocation clicks at higher frequencies and lower source levels, with highly directional beam patterns33. These clicks are likely only detected at ranges of up to approximately 4 km when the whale is oriented toward the hydrophone, and at lesser distances when clicks are received off-axis34. As a result, there is greater variability and lower baseline detection rates of beaked whale clicks on fixed passive acoustic recorders, which reduces statistical power to assess temporal changes in acoustic activity. Moreover, the duty-cycled recording schedule used at Station 5 provided only 65 s of high-frequency data 3 times per hour, and the presence of beaked whales is likely to be underestimated by this duty cycle, with potentially greater underestimation of Mesoplodont species compared to Cuvier’s beaked whales35.Continuous recordings were collected at the East Gully and Central Gully recording sites, but included only partial temporal coverage of the exercise period and no pre-exercise baseline data. No comparable recordings were available from these locations in a prior or subsequent year to form a control dataset. As a result, we were not able to use these datasets to assess changes in acoustic activity associated with the CF16 exercise. A slight decrease in hourly presence of northern bottlenose whale clicks in the Central Gully recordings occurred on September 19th–20th, 2016; however, we are aware that an oceanographic research vessel was coincidentally in the area deploying scientific instrumentation in close proximity to the Central Gully recording site on these dates, creating an additional source of potential disturbance. Despite these limitations, we included an analysis of the recordings collected at the East and Central Gully sites for two reasons: first, to provide perspective on the geographic extent over which activities associated with the CF16 exercise occurred; and second, to illustrate the diversity in beaked whale species composition at different locations across the region. Analysis of the recordings for sonar signals revealed that higher levels of sonar activity occurred near the Station 5 recording site than near the East or Central Gully locations. Due to the distance between recording sites and the timing of the sonar signals recorded, it appears that the recorded sonar signals came from multiple source locations over the duration of the exercise. Recordings from Central Gully contained the fewest sonar signals and lowest measured received levels, likely due to the deliberate avoidance of the Gully MPA and surrounding area by exercise participants during CF16. The Gully was established as an MPA in 2004, and is one of three adjacent canyons on the eastern Scotian Shelf currently designated as critical habitat areas for the endangered Scotian Shelf population of northern bottlenose whales36. The Station 5 recording site was located approximately 300 km to the southwest, and experienced higher levels of naval sonar activity during CF16. However, none of the locations were chosen specifically to monitor CF16, and we do not have access to information on the general exercise areas used, specific locations of naval vessels, submarines, or aircraft participating in the CF16 exercise, or the source levels of transmitted sonar signals. Due to the opportunistic nature of the recordings, the received levels of sonar signals measured at Station 5 likely do not represent the highest sound levels introduced into the marine environment during the CF16 exercise.Unlike many areas where behavioural responses to sonar are commonly studied, there are no instrumented naval training ranges off eastern Canada, and cetaceans inhabiting this region are unlikely to be accustomed to regularly hearing naval active sonars. Other than during the CF16 exercise, sonar signals were not noted during a large-scale analysis of cetacean call occurrence and soundscape characterization in 2 years of recordings collected at Station 5 and numerous other passive acoustic monitoring sites off eastern Canada26. Exposure context and familiarity with a signal may be important factors influencing an individual’s response to acoustic disturbance15. Experimental research on Cuvier’s beaked whales near a U.S. naval training range located off southern California demonstrated possible distance-mediated effects of sonar exposure, with more pronounced behavioural responses occurring with closer source proximity, even when received levels from the closer source were likely lower than those from more distant, high-powered sonar transmissions, which did not elicit as strong a response15. The movement and predictability of the sound source as well as the timing and duration of sonar transmissions may also be important factors influencing the behavioural response15. Whales inhabiting waters off southern California are likely habituated to hearing distant sonar due to routine naval training activities occurring on the range. Conversely, Wensveen et al.10 found that northern bottlenose whales in the eastern North Atlantic exhibited similar responses to simulated sonar signals played at various distances up to 28 km, suggesting that they perceived this novel stimuli as a potential threat even from a distance and at relatively low received levels. Bernaldo de Quiros et al.5 hypothesized that beaked whales not regularly exposed to active sonar signals may respond more strongly, both physiologically and behaviourally, which poses a concern for a region where military training activities involving the use of sonar are relatively infrequent, but occur periodically in the form of large-scale exercises involving the extensive use of active sonars and creating significant potential for acoustic disturbance.Behavioural disturbance due to anthropogenic noise may have energetic, health, and fitness consequences for deep-diving odontocete species. Disruption of normal diving patterns creates energetic costs due to the significant investment in each dive and the reduction of time available for prey intake when foraging dives are interrupted. Recent studies on the functional relationship between beaked whales and deep-sea prey resources suggest that certain characteristics of prey, including minimum size and density thresholds, are required for beaked whales to successfully meet their energetic needs12,37. While the distribution and characteristics of deep-sea prey are challenging to study and largely unknown in most regions, considerable environmental heterogeneity may be present, causing the quality of foraging habitat to vary significantly over even small horizontal scales12,37. This patchiness in habitat quality has important implications for behavioural disturbance, as even short-term displacement from high-quality habitat areas can affect the fitness of individuals and potentially lead to population-level consequences13.In addition to the consequences of sublethal disturbance, it is important to note that the likelihood of observing more acute impacts of exposure to naval active sonar, including injuries or fatalities, is extremely low in offshore regions. Individual and mass strandings of beaked whales and other cetaceans associated with military activities have typically been documented on oceanic islands with populated coastlines1,3,6. Factors affecting the probability that cetacean carcasses will wash ashore include buoyancy and decomposition rates in local water conditions, oceanic surface currents, the topography of coastlines, and the location of habitat relative to shore6. Off Nova Scotia, potential beaked whale and sperm whale habitat (consisting of water depths greater than 500 m) is located more than 100 km from the coastline, and injuries or fatalities occurring in deep water habitat in this region are unlikely to result in observed strandings. Stranding incidents involving sperm whales and beaked whales have been reported in Nova Scotia, but the cause of mortality is usually unknown38. Cetacean mortality is highly underestimated even in the aftermath of catastrophic events such as large oil spills39, and a lack of observed injuries or mortalities following offshore military activities should not be construed as evidence that no direct or immediate harm was caused.This study offered a unique opportunity to use existing passive acoustic monitoring (PAM) data to assess disturbance of poorly-known odontocete species during a real-world, large-scale military sonar exercise in a region where military sonar use at this scale is relatively uncommon. Ideally, a PAM study designed to examine disturbance in this context would collect continuous rather than duty-cycled recordings, and include ample baseline data surrounding the period of interest as well as in prior and subsequent years. Additionally, multiple acoustic sensors arranged in a dense array surrounding exercise locations would provide further insight into the spatial context of exposure and patterns of disturbance. Despite the data limitations in the present study, our results demonstrate that changes in odontocete foraging behaviour associated with acute, large-scale disturbance may be evident in PAM data even at low duty cycles. The nature of the observed effect (e.g., temporary disruption of foraging, spatial displacement, or more acute injury or distress) remains unknown, as do the number of individuals affected and the longer-term health and fitness implications. Broader baseline data on species occurrence and an improved understanding of species’ ecology and habitat use in the region are necessary for making informed mitigation decisions, allowing key habitat areas to be avoided, and understanding the impacts of naval active sonar exposure in this region on individuals and populations. More

This research focuses on the quantitative and qualitative analyses of cyanobacteria and microalgae present in rainfall during the summer phytoplankton bloom season of August–September 2019. In addition, a continuous episode of rainfall over several days was selected to demonstrate the washout process of microorganisms from the air with rain.Quantity of cyanobacteria and microalgae washed out with rain during the growing seasonCurrently, there is a growing number of scientific articles on cyanobacteria and microalgae in the atmosphere8. Unfortunately, there is a reference methodology for efficiently counting the microorganisms present in the air or in rainfall. A popular method for quantifying cyanobacteria and microalgae in the air is to show the number of taxa found in the collected samples after growth6,31,42,43,44,45,46. In this study, a total of 16 taxa of airborne cyanobacteria and microalgae were found in the samples. In the rainwater samples obtained during the summer of 2019, 11 taxa of cyanobacteria and microalgae were distinguished. The green algae in the rainwater samples included Bracteacoccus sp., Oocystis sp., Coenochloris sp., Chlorella sp., and Chlorococcum sp., while the cyanobacteria included Leptolyngbya sp., Pseudanabaena sp., Synechococcus sp., and Synechocystis sp. In addition, Chrysochromulina sp., which belongs to Haptophyta, was observed.Other studies recorded the presence of several to several dozen taxa in the air6,31,42,43,44,45,46. Certainly, a number of factors, starting with atmospheric conditions and ending with physical and chemical parameters of the surrounding waters, influence the diversity of cyanobacteria and microalgae in the atmospheric air. Analyzing global trends, only cyanobacteria have been found in the atmosphere of every region of the world31. However, according to Dillon et al.47, cyanobacteria have been detected in clouds at variable abundances between ~ 1% and 50% of the total microbial community. Xu et al.48 found that cyanobacteria constituted only 1.1% of the total bacterial community in clouds. It needs to be highlighted that there is still a lack of research available to provide this type of information for rainfall samples.For the period from July to September 2019, the results showed that the number of cyanobacteria and microalgae cells present in rainfall varied over time (Fig. 1) and ranged between 100 cells L–1 and 342.2 × 103 cells L–1. From July to the end of August, the cell number was relatively low, ranging from 100 cells L–1 to 28.6 × 103 cells L–1. This variability was related to the change in the biomass of blue green algae in the Gulf of Gdańsk (Table S2; Fig. 1). Therefore, this research also shows the close relationship between the processes taking place in the Baltic Sea and the presence of cyanobacteria and microalgae in the atmosphere. As the biomass of cyanobacteria in the Baltic Sea increased, the number of cyanobacteria and microalgae cells in the rainfall samples also increased (***p  More

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Comprehensive parks in small towns generally serve the urban residents within a few kilometers of the park. Parks are generally in an area with a large flow of people in a small town15. However, the geographical blockage indicates that the users of parks in small towns are generally of limited educational level, so the investigation process is more complicated. This study adopts a multimethod design with DPOE (diagnostic post-use evaluation) as the main research method, supplemented by the analytic hierarchy process (AHP) and GIS technology, to quantitatively evaluate the current use of comprehensive parks in small cities and towns, and make a decision based on the evaluation results regarding the corresponding optimization and promotion strategy. The research was divided into the following three stages.EvaluateBasis of evaluationBased on the perspective of “human body—movement—space—place—environment”21, stimulation theory and control theory in environmental psychology are used as the main directions for setting up and investigating recreational behaviors. Field investigations were conducted on the current environment, region, culture and other relevant factors of Central Park in Qingkou Town from April to May 2020. The survey covered weekdays, weekends and holidays, sunny/rainy days and mornings and evenings. The main task of the survey was to supervise the development and use of parks in small towns, the number of users, the types of facilities, and the appearance and maintenance of the park22 and to list the problems related to the environment and its ecology, the benefits provided by groups of parks, or the benefits provided to the surrounding enterprises and schools. Especially after the epidemic, residents have had a more active and urgent need for the participation of green space. To cover a wider range of weather and time conditions, data were collected in sequence during the observation period according to a preset scheme for four periods of the day, alternating between two working days and one weekend each week23. Two team members (interviewers) were in contact with tourists at different times in the park from 8 am to 8 pm. In order to minimize selection errors, each respondent was invited to participate in the survey (the targets included adults, children, and adolescents). Elderly people who agreed to participate in the survey were asked about their visit activities and usage behaviors in the park, such as the frequency of visits, distance, and satisfaction with respect to park maintenance, safety, and infrastructure construction24. Finally, the survey requested relevant social demographic information, such as age, highest education level, and marital status (with or without children).Construction of a performance evaluation index system for comprehensive park landscapes in small townsThe evaluation index of the general applicability of small-town parks was established using a field investigation and the combination of the American landscape performance series (LPS)25. The index system was divided into three levels. The first level was the target level, that is, the evaluation index system of the comprehensive landscape performance of small-town parks. The second level was the criterion level, including environmental performance, health performance and economic performance. As the embodiment of the second level, the three-level index layer mainly includes park construction, infrastructure setting, landscape quality, garden atmosphere, and tourist behavior. Considering the accuracy of comprehensive park evaluation in small towns, the three-level index layer was used to obtain 19 related indexes after expert advice and screening20.Questionnaire designSince this study is aimed at parks in small towns and the surrounding residents generally have a low level of education, to obtain more effective data, the questionnaire was in the form of ticking. In terms of content, the questionnaire was divided into two parts. The first part collected basic information about tourists, such as the mode of transportation to the park and visit frequency. Second, there were 19 evaluation index factors. The Likert method was used to evaluate the index26, and the answers each had five levels: very satisfied, satisfied, average, dissatisfied and very dissatisfied.Combination weight analysisSome papers in the past ten years have discussed the limitations of the AHP in dealing with the complexity and uncertainty of evaluation indicators and used fuzzy comprehensive evaluation methods to deal with the problem of uncertainty27,28,29,30. However, the fuzzy evaluation method has gradually been eliminated due to its inability to quickly determine the evaluation content31. Therefore, this study used indicator weights for analysis and evaluation. On the basis of the AHP analytic hierarchy process, the coefficient of variation (CV) is added to the weight of each indicator32. The main purpose of adopting this method is to establish a landscape performance evaluation system for Qingkou Central Park, refer to the satisfaction evaluation of tourists through the DPOE, and determine the content that the park needs to be optimized.SurveyThe places where tourists gather or where tourists are the most often have a certain reference significance for the planning and design of parks. Therefore, collecting data on tourist gathering places is needed in the research process33. An increasing number of studies have pointed to the use of social media to examine users’ daily life behaviors and spatial distribution relationships. Wood et al. attempted to evaluate the access rate of entertainment venues based on the location of photos posted on Flickr34. Hamstead et al. use geolocation data from Flickr and Twitter to assess changes in the use of all parks in New York city35. Because the identification system for comprehensive parks in most small towns is not clear, tourists cannot clearly identify a place to visit or a location they often visit. Therefore, the following attempts were made: (1) A total of 182 points of interest of tourists in Qingkou Central Park were collected through Octopus Aata Collector 8, Six-Feet and other software. (2) The distribution of interest points and on-site observations were used to identify five gathering points that cover most of the park landscape. They were named A, B, C, D and E (Table 1) for fixed video recording. The average weekday traffic and weekend traffic information was obtained. (3) The collected data were imported into Excel for sorting, and the utilization of parks was visually expressed in different time periods through GIS. (4) From May to August 2020, 300 copies of paper questionnaires were distributed at nodes A, B, C, D and E. (5) In addition, the questionnaire content was imported into Excel for simple processing, classification and deletion of duplicate data. (6) Finally, the spatial and temporal distribution results and comprehensive evaluation results of tourists in comprehensive parks in small towns were obtained, and optimization suggestions were summarized.Table 1 Landscape node and application of the Central Park.Full size tableSpatial distribution and experience of respondentsThe behavior track, gathering area and spatial distribution of tourists in the park affect the evaluation of the park. However, due to the different behavioral habits of tourists, some areas of the park will have a crowd gathering effect36. As a result, the use of environmental resources in the park is uneven, resulting in the waste of environmental resources and ecological damage.During the study, to make the data more accurate, a total of six samples were randomly selected from three working days and three weekends from May to July 2020 for data collection. The collection method consisted of five people at five important nodes in the park that basically cover the popular areas (including A. Northeast Main Entrance Square, B. Southwest Main Entrance Square, C. West Secondary Entrance Square, D. Sports Theme Square, and E. Waterfront wooden platform); the sites were filmed from 06:00 to 20:00 (fifteen minutes were taken from 06:00–08:00, 08:00–11:00, 11:00–13:00, 13:00–17:00 and 17:00–20:00 for each time period) to record the activity track of tourists in a day. Then, the average weekday samples and weekend samples were averaged, and the data of the flow of people and the length of stay were processed. The flow of people in the different periods of each node of the two samples was sorted using Excel, and coordinate marks were made on the construction drawings according to the image data to screen out repeated and unreasonable data37,38. Then, ArcGIS was used to perform data visualization (scenic spot heat), and the following conclusions could be drawn: there was a significant difference in the stay time of tourists at different nodes (Fig. 2).Figure 2Schematic diagram of the flow of people in different times and spaces.Full size imageThrough node analysis, it was found that tourists stayed in the park for at least 30 min. Compared with the research process, it took approximately 1 h and 10 min to complete the whole track through the Six-Foot app, which showed that tourists stayed in the park for a longer time. Among them, the passenger flow peaks were during 06:00–08:00, 11:00–13:00 and 17:00–20:00, while the passenger flow was lower at other times. In addition, according to observation and survey data summary, passenger flow was not evenly concentrated among the five node areas6. Overall, node A and node B had a large flow of tourists and a longer stay time. Node D was ranked next, while node C and node E had less traffic and shorter stay times.Overview of respondentsAccording to the POE field survey and questionnaire survey, 292 valid questionnaires (recovery rate 97.3%) were obtained, among which 58.2% (169 persons) were female, slightly higher than the 41.8% (123 persons) that were male. Among them, 40.5% (118 persons) were carrying children under 8 years old. In terms of age, young people between 30 and 39 years old accounted for 43.7% (128 people), most of whom carried children, followed by younger people between 19 and 29 years old and young people between 40 and 49 years old, which fully showed that the urban center where the park is located was dominated by young people. Among the visitors, 71.9% (210 people) were local residents, 18.5% (54 people) were temporary residents, and 9.6% (28 people) were foreign tourists. In terms of how people arrived at the park, most of them came by walking (116 people), accounting for 38.9%, followed by electric vehicles and private cars (61 people each), accounting for 21.6%. Among them, 53% (154 people) chose to come to the park when they were free, and 24% (70 people) came to the park three or four times a week. In the park system of this small town, the public green space served the local residents to a large extent and gradually became a recreational place for the real-time entertainment of nearby residents (Table 2).AHP-CV comprehensive weight analysisThe development of the AHP-CV combined weights has led to a change in the method of determining indicator weights from a single subjectiveness to a comprehensive objectivity39. In order to avoid the evolution of the AHP to a single weighting method, the AHP method is combined with the SW and CV methods here to calculate objective weight, based on the principle of minimum information entropy combining two kinds of weighted information40.

1.

To ensure the reliability of the data, first, check the consistency of the paired comparison matrix:$${text{RC }} = {text{ IC}}/{text{IR}}$$
If RC  More

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