Spatial Distribution Of Catch Research Articles

Is my fishing gear impacting the habitat? An impact assessment in four fisheries in the Northwest Mexican Pacific

The impacts of fishing activities on habitats for commercially important species may, directly and indirectly, influence species and associated communities. These effects include those on target species, bycatch species, habitats, etc. In this study, the impact of small-scale fisheries on habitats was evaluated in four fishing communities from the Northwest Mexican Pacific. The species and size selectivity of several fishing gear were evaluated, and the spatial distribution of catches was studied to assess the impacts of fishing gear using a Consequence Spatial Analysis (CSA). Our results showed that in finfish fisheries from Guaymas and Isla Natividad, the catch of the target species represents more than 75% of the total catch and in El Rosario, the catch represents less than 50%. We assessed 42 habitat types in four communities, which were qualified with low-risk scores. The fishing gears used to target commercial species are selective to optimal sizes above their maturity size. The results contribute to improving management in data-poor fisheries by evaluating the impacts of fishing on habitats and discussing their relevance for implementation.

Environmental Influences on Illex argentinus Trawling Grounds in the Southwest Atlantic High Seas

To understand the spatial temporal distribution characteristics of Illex argentinus caught by trawl fishing vessels in the Southwestern Atlantic Ocean and their relationship with key marine environmental factors, this study analyzed the temporal and spatial changes in the fishing ground center of trawl vessels at the ten-day scale from December 2019 to May 2022, combining Chinese trawl fishing log data marine environmental data with satellite remote sensing marine environmental data. Utilizing the Maxent model, ten-day intervals were used as the temporal scale, and ten marine environmental factors, including sea surface temperature, sea surface height, sea surface salinity, chlorophyll concentration, temperature at 50 m and 100 m depth, and the meridional and zonal velocities of ocean currents were quantitatively analyzed to explore the correlation between the spatial distribution of catch and environmental factors. The study reveals that the trawl fishing grounds for Illex argentinus are divided into southern and northern grounds. The southern grounds first appear near 45°20′ S in December, gradually moving southeastward in February and March. The northern grounds do not appear until April, near 42° S in the high seas. On the ten-day time scale, the central fishing grounds of Illex argentinus show significant spatial variability but minor interannual differences. The Maxent model results indicate that sea surface temperature and chlorophyll a concentration are the key environmental factors influencing the spatial and temporal variability of the high seas trawl fishing grounds for most of the time, with high environmental contribution rates during the fishing season. While the range of suitable habitats with an HSI > 0.6 identified by the Maxent model varies significantly between years, a pattern is observed where the range expands at the start and end of the fishing season and contracts during the peak fishing season. This suggests that a more concentrated range of suitable habitats is conducive to accurate predictions of trawl fishing grounds, enabling efficient fishing operations.

BIOLOGICAL ASPECTS, CATCHING ASPECTS AND FISHING GROUND OF EASTERN LITTLE TUNA OR KAWAKAWA(Euthynnusaffinis (Cantor, 1849)) BASED ON THE FISHING GEAR AT WPP 572

Eastern little tuna ( Euthynnus affinis ) is the main catch in WPP572. The caught E. affinis are still in their infancy. This research aims is to know the biological aspects, the fishing aspects and the distribution of the fishing gear per fishing gear, as a consideration for sustainable fisheries management. The research was carried out during the years 2019-2020. Taking samples for gonad observation was carried out by direct survey to the location in February, May, July and October 2019. The measurement of fish length was carried out in stratified random. Catching data were retrieved by requesting secondary data and interviews with related parties. The distribution of fishing grounds is mapped using the QGIS 3.4, the spatial distribution of catches is mapped. This study showed the size structure of E. affinis on purse seine, troll line and encircling gill netfishing gear from 16-55 cm FL, while on the boat/raft lift net it was 21-50 cmFL. These fish growth's is positive allometric on purse seine and encircling gillnet fishing gear, negative allometric on boat/raft lift net fishing gear, and isomeric on troll line. The sex ratio is in the ratio 1: 1.15 and balanced. Based on the maturity level, the gonads were mature in July and October and immature in February and May. Gonads ripened for the first time at a size of 42.032 cmFL. The distribution of the purse seine catchment areas at 3°-6°N and 93°-96°E, and 3°-6°S and 94°-95°E. Boat/raft lift net at 0°-3°S and 95° -101°E. Troll line 4°-6°N and 94°-95 E. Encircling gillnet 0°-2°S and 99°-101°E.

Spatial and temporal dynamics of the Antarctic krill fishery in fishing hotspots in the Bransfield Strait and South Shetland Islands

Antarctic krill is a vital part of the food web and supports a significant fishery in the Southern Ocean. Shifts in historical fishing grounds and spatial distribution of catches have occurred as a result of recent changes in fishery practices. To understand these shifts, fishery spatial dynamics and fishing fleet behavior evaluated on different spatial and temporal scales are critical. We examine the catch distribution on three spatial-temporal scales. At the Western Antarctic Peninsula (WAP) scale, we assessed the fleet’s southward expansion, identifying the Bransfield Strait (BS) as the main current fishing ground, replacing the historical Drake sector. At the BS scale, we identified fishing hotspots (FHs) that concentrated 48%–57% of the total catch over a period of 2–6 months and had high catch densities (2.2–30.3 ton km−2). At the FH scale, we tracked the spatial distribution of the fleet within FHs, demonstrating a shift of fishing vessels to contiguous zones as a result of a decrease in daily catch rates (CPUE). Such shifts (allowing the fleet to increase CPUE) occurred every 4–17 days. Previously exploited fishing grounds were revisited based on FH persistence and sea ice conditions. This paper concludes with a discussion of the potential impact of fishing fleet behavior and catch concentration, considering the recent spatial shift towards less-exploited areas, the overlap with critical zones for predator feeding, and several implications for fisheries management.

Autumn distribution of Bristol Bay red king crab using fishery logbooks.

Spatial distributions of fished species must be well characterized to avoid local depletions, identify critical habitat, and predict and mitigate interactions with other fisheries. The Bristol Bay red king crab (Paralithodes camtschaticus) fishery is one of the largest crab fisheries in Alaska. Summer crab distributions have been well documented by decades of bottom trawl surveys. However, crab movement and distribution are poorly understood outside the summer survey period, which creates several management challenges. One important component of fishery management is the existence of no-trawl zones, which are intended to protect crab from bottom trawl fisheries. However, it is difficult to evaluate the placement of no-trawl zones, because most crab bycatch occurs in trawl fisheries during winter when crab distributions are unknown. Daily fishing logs, kept by skippers in the red king crab fleet since 2005, contain detailed information on the spatial distribution of catch and effort of legal sized male crab during the autumn crab fishery. However, data contained in these hand-written logbooks have not been readily accessible. We digitized daily fishing logs from 2005 to 2016 and used spatial information on catch and effort to infer geographic distributions of legal sized male king crab during the crab fishing season. Changes in distribution were tracked across this 12-yr period and comparisons were made between warm and cold temperature regimes. In warm years (2005, 2014–2016), crab aggregated in the center of Bristol Bay, Alaska, while in cold years (2007–2013) they were closer to the Alaska Peninsula. The majority of crab were caught in no-trawl areas (63.4% on average), but variations occurred among years and with temperature regime (40.0–86.8% in no-trawl zones). As temperatures continue to shift in the Bering Sea, it will be important to continue monitoring crab distributions outside the summer survey period.

Analysis of influence on spatial distribution of fishing ground for Antarctic krill fishery in the northern South Shetland Islands based on GWR model

Based on Antarctic krill fishery and marine environmental data collected by scientific observers, using geographically weighted regression (GWR) model, we analyzed the effects of the factors with spatial attributes, i.e., depth of krill swarm (DKS) and distance from fishing position to shore (DTS), and sea surface temperature (SST), on the spatial distribution of fishing ground in the northern South Shetland Islands. The results showed that there was no significant aggregation in spatial distribution of catch per unit fishing effort (CPUE). Spatial autocorrelations (positive) among three factors were observed in 2010 and 2013, but were not in 2012 and 2016. Results from GWR model showed that the extent for the impacts on spatial distribution of CPUEs varied among those three factors, following the order DKS>SST>DTS. Compared to the DKS and DTS, the impact of SST on the spatial distribution of CPUEs presented adverse trend in the eastern and western parts of the South Shetland Islands. Negative correlations occurred for the spatial effects of DKS and DTS on distribution of CPUEs, though with inter-annual and regional variation. Our results provide metho-dological reference for researches on the underlying mechanism for fishing ground formation for Antarctic krill fishery.

Spatial valuation of California marine fisheries as an ecosystem service

Quantifying spatiotemporal dynamics of ecosystem services is an emerging approach for informing and managing trade-offs among cumulative or competing activities in marine environments. As one proxy for ecosystem services and benefits, we quantified and mapped catch and economic value of California commercial fisheries removals using a 75-year spatially explicit time series. From 1931 to 2005, approximately 88% of the catch was attributed to finfish. However, there has been an increasing reliance of proportional value from invertebrates over the last 25 years. The spatial organization of historical catches suggests species composition varies substantially by depth and latitude, and an evaluation of changes in the spatial distribution of catches in three different time periods suggests that spatial shifts in catch locations have occurred for some taxonomic groups over time. A spatial assessment of historical catches and value benefits marine spatial planning, informs stock assessments, provides a quantification of ecosystem services, and facilitates ecosystem-based approaches to marine fisheries management.

The Spanish blackspot seabream (Pagellus bogaraveo) fishery in the Strait of Gibraltar: spatial distribution and fishing effort derived from a small-scale GPRS/GSM based fisheries vessel monitoring system

This paper aims to investigate the potential interest of using a Vessel Monitoring System (VMS) based on GPRS/GSM (Global System for Mobile Communications) technology to obtain a better estimation of fishing activity and distribution of a small-scale artisanal fleet, for which the European satellite-based system is not available. Since the early 1980s, the artisanal fishery targeting blackspot seabream (Pagellus bogaraveo), commonly known as “voraz”, has been developing along the Strait of Gibraltar area. Up to now the fishing effort was estimated using the number of sales, a proxy for the number of fishing days. This measure does not, however, capture the “missing effort”, i.e., fishing days resulting in no catch or not enough catch to be sold at public auction. The European satellite-based VMS provides information about the dynamics of different fishing fleets, but is not installed on small vessels (<15 m), such as those used by the artisanal “voracera” fleet targeting blackspot seabream in the Strait of Gibraltar. The Andalucia Regional Government installed its own vessel monitoring system on several artisanal fleets using GPRS/GSM cellular network technology that sends data on vessel positions and speed every three minutes. Data collected from 2009 to 2011 using this system were filtered and analysed to estimate fishing effort, catch rates and the spatial distribution of the blackspot seabream fishery. The estimates obtained seem to provide a good representation of fishery reality. As expected, the missing effort increases as the resource levels decrease. Additionally, expert knowledge of the fishery allowed application of an algorithm for splitting these daily trips into estimated fishing hauls. Afterwards the spatial distribution of catches and Catch per Unit Effort (CPUE) could be obtained linking VMS locations with landings information. This study provides a considerably finer spatial scale view of the fishery than data available in the past.

The Scotia Sea krill fishery and its possible impacts on dependent predators: modeling localized depletion of prey

The nature and impact of fishing on predators that share a fished resource is an important consideration in ecosystem-based fisheries management. Krill (Euphausia superba) is a keystone species in the Antarctic, serving as a fundamental forage source for predators and simultaneously being subject to fishing. We developed a spatial multispecies operating model (SMOM) of krill-predator fishery dynamics to help advise on allocation of the total krill catch among 15 small-scale management units (SSMUs) in the Scotia Sea, with a goal to reduce the potential impact of fishing on krill predators. The operating model describes the underlying population dynamics and is used in simulations to compare different management options for adjusting fishing activities (e.g., a different spatial distribution of catches). The numerous uncertainties regarding the choice of parameter values pose a major impediment to constructing reliable ecosystem models. The pragmatic solution proposed here involves the use of operating models that are composed of alternative combinations of parameters that essentially try to bound the uncertainty in, for example, the choice of survival rate estimates as well as the functional relationships between predators and prey. Despite the large uncertainties, it is possible to discriminate the ecosystem impacts of different spatial fishing allocations. The spatial structure of the model is fundamental to addressing concerns of localized depletion of prey in the vicinity of land-based predator breeding colonies. Results of the model have been considered in recent management deliberations for spatial allocations of krill catches in the Scotia Sea and their associated impacts on dependent predator species.

基于地统计分析西印度洋黄鳍金枪鱼围网渔获量的空间异质性

PDF HTML阅读 XML下载 导出引用 引用提醒 基于地统计分析西印度洋黄鳍金枪鱼围网渔获量的空间异质性 DOI: 10.5846/stxb201112011840 作者: 作者单位: 上海海洋大学,上海海洋大学,上海海洋大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家"863"计划项目(2007AA092202); 国家自然科学基金项目(41006106); 教育部高等学校博士学科点专项科研基金新教师基金项目(20093104120005); 上海市青年科技启明星计划项目(11QA1403000); 上海市重点学科建设项目(S30702); 上海市教委创新项目(09YZ275)共同资助 Geostatistical analysis of spatial heterogeneity of yellowfin tuna (Thunnus albacares) purse seine catch in the western Indian Ocean Author: Affiliation: The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries ResourcesShanghai Ocean University,Ministry of Education,Shanghai,The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries ResourcesShanghai Ocean University,Ministry of Education,Shanghai,;P R China;;Scientific Observing and Experimental Station of Oceanic Fishery Resources,Ministry of Agriculture,Shanghai Ocean University,Shanghai,;P R China;;College of Marine Sciences,Shanghai Ocean University,Shanghai,;P R China,The Key Laboratory of Sustainable Exploitation of Oceanic Fisheries ResourcesShanghai Ocean University,Ministry of Education,Shanghai Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:西印度洋公海海域是世界上围网黄鳍金枪鱼渔业的主要作业海域之一,根据印度洋金枪鱼委员会1999-2004年的1°×1°的各月黄鳍金枪鱼围网渔获量统计数据,采用地统计方法探索该海域黄鳍金枪鱼渔获量的空间异质性特征及其相关生态动力过程。进行了如下分析:(1)利用GIS制图观察渔获量的时空分布特征,发现其空间格局的变异受到的季节变化和年际变化共同影响,且前者明显强于后者。(2)采用地统计方法计算各月渔获量的空间异质性参数,并按照年际和季节情况分别进行了统计分析,发现渔获量的地统计参数值和变异函数模型有明显的季节和年际差异;渔获量的空间相关距离(变程)平均在1000nm左右,冬季要小于夏季;渔获量的空间变异函数模型主要为相关距离较大且空间依赖性较弱的指数模型;渔获量的空间结构方差比例(平均为65.82%)远大于随机性方差比例(平均为34.18%);渔获量在1°×1°尺度下具有明显的空间自相关性。(3)对地统计参数值和渔获量的相关关系研究,并探讨季节变化下渔获量的空间异质性特征与相关生态动力过程关系,发现各月渔获量随着空间总变异(基台值)增加而增加,两者存在强相关性;各月渔获量和南北和西北-东南向分维数值有一定相关性,意味着海洋动力过程在南北和西北-东南向过程越强,渔获量越低。西印度洋黄鳍金枪鱼围网渔获量的空间变异原因在于季风气候和ENSO循环过程引起的海洋流场、营养盐和温跃层等变化外在因素,以及围网捕捞方式和鱼类的行为方式的内在因素共同导致的。 Abstract:Our objective was to assess which environmental factors explain the variation in the distribution and abundance of fishery stocks. We used a novel approach, applying geostatistical tools to explain the spatial heterogeneity of purse seine yellowfin tuna (Thunnus albacares) catch in the western Indian Ocean. Geostatistical tools enable researchers to develop a more thorough understanding of the mechanisms controlling the spatial variation in fishery stocks. In addition, this tool is able to deal with complex correlations between spatial patterns and fishery harvest. The western Indian Ocean is one of the most productive purse seine yellowfin tuna (Thunnus albacares) fisheries in the world. We evaluated the variation in the spatial distribution of catch using geostatistical methods. In addition, we discuss the dynamic ecological processes influencing the spatial heterogeneity of catch. We used records of purse seine harvest of yellowfin tuna (Thunnus albacares) collected by the Indian Ocean Tuna Commission (IOTC). The data were summarized by month for 1°×1° areas between 1999-2004. We found that the spatial distribution of catch varied both between seasons and inter-annuals, but was largest between seasons. We obtained the semivariograms parameters and best-fitting semivariogram models from seine yellowfin tuna catch using geostatistical methods. We observed significant seasonal and inter-annual differences in the semivariogram parameters and the semivariogram models of spatial distribution of catch. The average spatial correlation distance (the ranges in geostatistical) was 1000 nautical miles and the values were smaller in winter than in summer. The best-fitting semivariogram models were primarily exponential and had a longer spatial corresponding distance and lower spatial dependence than other models. The spatial structural variance (mean value was 65.82% of total variance) was significantly higher than the random variance (mean value was 34.18% of total variance). We found that the spatial structure of catch had high spatial autocorrelation at 1°×1° areas scale. We investigated the relationship between the semivariogram parameter values and the catch of purse seine yellowfin tuna and attempted to explain the ecological dynamic processes explaining the spatial heterogeneity in catch. We found a strong, positive linear correlation between monthly catch and the sum of spatial variances (sill values), with a correlation coefficient of 0.930 (P<0.001). The monthly catch was also correlated to the south-northward (correlation coefficient=0.5055, P<0.1) and northwest-southeastward fractal dimension values, suggesting that catch was positively correlated with marine dynamic processes oriented in these two directions. Thus, catch decreased when the environmental process components intensified in these two directions. In summary, a number of external factors contribute to the spatial variation in yellowfin tuna catch in the western Indian Ocean, including marine currents, nutrients, and the thickness of the thermocline, which are influenced by the monsoonal climate and ENSO episodes. In addition, we identified internal factors such as the purse seine fishing methods and fish behavior that also affected the spatial distribution of harvest. Our results suggest that several environmental factors can be used to predict changes in the catch of purse seine yellowfin tuna in the western Indian Ocean. These included seasonal indices, which had a significant influence in the spatial distribution model; ENSO episodes; and the optimal semivariogram model. The selection of environmental factors for the yellowfin tuna stock assessment model should include consideration of vector meridian variables that influence marine environmental processes, such as ocean currents or wind fields. 参考文献 相似文献 引证文献

Range contraction in large pelagic predators.

Large reductions in the abundance of exploited land predators have led to significant range contractions for those species. This pattern can be formalized as the range-abundance relationship, a general macroecological pattern that has important implications for the conservation of threatened species. Here we ask whether similar responses may have occurred in highly mobile pelagic predators, specifically 13 species of tuna and billfish. We analyzed two multidecadal global data sets on the spatial distribution of catches and fishing effort targeting these species and compared these with available abundance time series from stock assessments. We calculated the effort needed to reliably detect the presence of a species and then computed observed range sizes in each decade from 1960 to 2000. Results suggest significant range contractions in 9 of the 13 species considered here (between 2% and 46% loss of observed range) and significant range expansions in two species (11-29% increase). Species that have undergone the largest declines in abundance and are of particular conservation concern tended to show the largest range contractions. These include all three species of bluefin tuna and several marlin species. In contrast, skipjack tuna, which may have increased its abundance in the Pacific, has also expanded its range size. These results mirror patterns described for many land predators, despite considerable differences in habitat, mobility, and dispersal, and imply ecological extirpation of heavily exploited species across parts of their range.

Spatial distribution of catch and effort in a fishery for snow crab (Chionoecetes opilio): tests of predictions of the ideal free distribution

The ideal free distribution (IFD), a hypothesis from behavioural ecology, predicts that fishery effort should map resource distribution better than catch-per-unit-effort (CPUE) when interference competition occurs in the fishery. We tested this prediction using data from the fishery and annual research survey for snow crab (Chionoecetes opilio) in the southern Gulf of St. Lawrence. Effort was positively correlated with the local abundance of crabs in all years. Correlations between CPUE and local crab abundance were also positive in some years, but negative in others. In the latter cases, CPUE and effort were also negatively correlated, suggesting intense competition in the fishery. In most years, CPUE tended to be equalized among areas compared with the distributions of effort and local crab abundance, as predicted by the IFD. In most years, differences in spatial distribution were more significant between CPUE and crab abundance than between effort and crab abundance. Although effort was the more reliable indicator of resource distribution, even it provided a distorted view of this distribution, as predicted given expected violations of IFD assumptions. For example, effort tended to be higher than expected on fishing grounds near home ports and lower than expected on distant grounds.

Monitoring the recreational gamefish fishery off south-eastern Australia

The east coast Australian gamefish fishery is a diverse, multi-species fishery that targets billfish, sharks, tuna and other pelagic fish along the east Australian seaboard. A Gamefish Tournament Monitoring Program (GTMP) was undertaken, and 39021 angler trips from 1996 to 2000 were analysed. The program reports on trends in fishing effort, catch rates, catch composition, proportions of captures tagged and released and spatial distribution of catches for the principal recreational billfish species: black marlin (Makaira indica), striped marlin (Tetrapterus audax) and blue marlin (Makiara nigricans).The GTMP was principally designed as part of an integrated program to monitor the recreational gamefish fishery. The spatial and temporal design of the program restricted statistical analyses however, there were trends in fishing effort, directed effort, catch rates, catch composition, proportions of fish tagged and spatial distribution of catches for the principal recreational billfish species over seven successive years (1994–2000). Analysis of catch data, stratified by directed effort, indicated significant differences in catches of target species, demonstrating the importance of calculating catch rate estimates according to the main target preference. Analysis of tournament based tagging information indicated that while overall tournament tagging rates remained high (88%) there were significant differences in the number of fish tagged between species groups highlighting the impact that angler attitude and the competition point score structure has on the harvest of gamefish target species.

Implications of interference among fishing vessels and the ideal free distribution to the interpretation of CPUE

Despite recognized biases, catch per unit effort (CPUE) statistics remain widely used for the estimation of fish abundance. Previous workers have shown that CPUE can be a misleading index of abundance due to fish behavior, the nominal effort units used, and increases through time in efficiency of fishing (catchability). We examine the theoretical implications of a different factor, interactions among fishing vessels, for the relationship between abundance and CPUE. Our model simulates a fishery that occurs in several adjacent fishing grounds. The spatial distribution of catch and effort is based on a simplification of the Baranov catch equation, the relationship between fishing efficiency and local fishing effort (interference), and the assumptions of the ideal free distribution. Our results indicate that (i) even low levels of interference among fishing vessels can cause a breakdown in the correlation between CPUE and local abundance and (ii) the influence of interference on this relationship is dependent on the correlation of abundances among adjacent areas. Our model suggests an alternative index of abundance, based on the proportion of fishing effort on a ground, that would be appropriate for cases where interference occurs among fishing gear.

Attraction of bark beetles (Coleoptera: Scolytidae) to a pheromone trap

The movement of bark beetles near an attractive pheromone source is described in terms of mathematical models of the diffusion type. To test the models, two release experiments involving 47,000 marked spruce bark beetles [Ips typographus (L.)] were performed. The attractive source was a pheromone trap, surrounded by eight concentric rings with eight passive trap stations on each ring. Captures were recorded every 2–10 minutes for the pheromone trap and once for the passive traps. The models were fitted to the distribution in time of the central pheromone trap catch and to the spatial distribution of catch among the passive traps. The first model that gives a reasonable fit consists of two phases: Phase one—After release the beetles move according to a diffusion process with drift towards the pheromone trap. The strength of the drift is inversely proportional to the distance from the traps. Phase two—those beetles attracted to, but not caught by, the pheromone trap are no longer influenced by the pheromone, and their movement is described by a diffusion process without drift. In phase two we work with a loss of beetles, whereas the experiment seems to indicate that the loss of beetles in phase one is negligible. As a second model, the following modification of phase one is considered: After release the beetles move according to a diffusion process without drift, until they start responding to the pheromone (with constant probability per unit time), whereafter they start moving according to a diffusion process with drift. This study, like other release experiments, shows that the efficiency of the pheromone trap is rather low. What is specific for the present investigation is that we try to explain this low efficiency in terms of dynamic models for insect movement. Two factors seem to contribute: Some beetles do not respond to pheromone at all, and some beetles disappear again after having been close to the pheromone trap. It also seems that the motility of the beetles decreased after they ceased responding to the pheromone. Furthermore, the data lend some support to the hypothesis that flight exercise increases the response of the beetles to pheromone.

Flight activity of female black-flies (Diptera: Simuliidae) studied with a vehicle-mounted net in northern England

Summary Studies on black-fly females using a net mounted on the roof of a motor vehicle showed the following: (1) Simulium reptans and S. ornatum showed a diel rhythm of flight activity with a peak in early morning (sometimes omitted), low activity during the day and a peak in late evening that was of longer duration in S. ornatum than in S. reptans. S. equinum showed a different diel rhythm with more prolonged activity from late morning to early evening, usually without peaks. (2) Woodland adjoining the road traversed by the vehicle led to increased catch of S. reptans but had no effect on numbers of S. equinum, suggesting the former species sought conditions associated with woodland. (3) Spatial distribution of catches on roads up to 7 km distant from the river producing the flies showed that S. reptans dispersed more vigorously than S. equinum. In both species large changes occurred in the spatial pattern within periods of one week. (4) In S. reptans and S. ornatum activity peaks particularly that in t...