Investigation of the Influence of Seagrass on Fisheries Catch Level Using Isotonic Regression

The relationship between seagrass area and the commercial catch of some economically important South Australian fish species is not known in any quantitative sense. However, there is evidence in the literature to suggest that seagrass decline will detrimentally impact on species abundance and composition, and consequently that the presence or absence of seagrass will compromise the commercial and recreational fishery. In this paper we describe the construction of models based on order restricted (isotonic) regression and discuss the role of seagrass area, in terms of its influence on the level of commercial catch through modifying the effect of fishing 'effort'.     

Effects of publication bias on conservation planning

Conservation planners need reliable information on spatial patterns of biodiversity. However, existing data sets are skewed because some ecosystems, taxa, and locations are underrepresented. We determined how many articles have been published in recent decades on the biodiversity of different countries and their constituent provinces. We searched the Web of Science catalogues Science Citation Index (SCI) and Social Science Citation Index (SSCI) for biodiversity-related articles published from 1993 to 2016 that included country and province names. We combined data on research publication frequency with other provincial-scale factors hypothesized to affect the likelihood of research activity (i.e., economic development, human presence, infrastructure, and remoteness). Areas that appeared understudied relative to the biodiversity expected based on site climate likely have been inaccessible to researchers for reasons, notably armed conflict. Geographic publication bias is of most concern in the most remote areas of sub-Saharan Africa and South America. Our provincial-scale model may help compensate for publication biases in conservation planning by revealing the spatial extent of research needs and the low cost of redoing this analysis annually.     

Satisfaction with fishing and the desire to leave

Predicting who may leave a fishery is an important consideration when designing capacity reduction programs to enhance both ecological and economic sustainability. In this paper, the relationship between satisfaction and the desire to exit a fishery is examined for the Queensland East Coast Trawl fishery. Income from fishing, and changes in income over the last 5 years, were key factors affecting overall satisfaction. Relative income per se was not a significant factor, counter to most satisfaction studies. Continuing a family tradition of fishing and, for one group, pride in being a fisher was found to be significant. Satisfaction with fishing overall and the challenge of fishing were found to be the primary drivers of the desire to stay or leave the fishery. Surprisingly, public perceptions of fishing, trust in management and perceptions of equity in resource allocation did not significantly affect overall satisfaction or the desire to exit the fishery.     

Restricted adaptive cluster sampling

Adaptive cluster sampling can be a useful design for sampling rare and patchy populations. With this design the initial sample size is fixed but the size of the final sample (and total sampling effort) cannot be predicted prior to sampling. For some populations the final sample size can be quite variable depending on the level of patchiness. Restricted adaptive cluster sampling is a proposed modification where a limit is placed on the sample size prior to sampling and quadrats are selected sequentially for the initial sample size. As a result there is less variation in the final sample size and the total sampling effort can be predicted with some certainty, which is impor- tant for many ecological studies. Estimates of density are biased with the restricted design but under some circumstances the bias can be estimated well by bootstrapping. © Rapid Science 1998     

A framework for understanding the consumptive orientation of recreational fishermen

Fishermen were aggregated into high-, mid-, and low-consumptive groups according to the importance they placed on catching fish. Analysis of variance indicated that each consumptive group was unique in the importance it placed on other fish-related variables. Low-consumptive fishermen rated most other aspects of the fishing experience, such as interacting with nature, relaxation, and escaping the daily routine, more important than did high-consumptive fishermen. Low-consumptive fishermen also fished more frequently and were generally more satisfied with their most recent fishing trip than were high-consumptive-oriented fishermen. The three groups can be viewed as different fishing constituencies. By understanding their characteristics, we can gain additional insights into the impacts of management decisions on recreational fishermen and their experiences.     

Using Participatory Rural Appraisal to explore coastal fishing in Badagry villages,Nigeria

Fish production and marketing are as old as the rural communities involved in the lucrative occupation in Badagry area of Lagos State, Nigeria. A random sampling of 200 fishermen using Participatory Rural Appraisal techniques (PRA) in five Badagry villages was used to explore coastal fishing and socio-economic development in the study area with a view to enhancing local productivity and sustainability. The findings show that an average fisherman in Badagry is aware of the resources available in his environment, and can affect productivity levels positively if given adequate incentives. There are two lessons from this study; one has to do with what PRA tells us about the fishing community, the other is the importance of facilitators that have, amongst other things, good listening skills. The experience also revealed that field workers’ ability to listen and learn from local fishermen was a critical factor in collecting in-depth information that could be used for rural community planning.     

Monitoring,imperfect detection,and risk optimization of a Tasmanian devil insurance population

Most species are imperfectly detected during biological surveys, which creates uncertainty around their abundance or presence at a given location. Decision makers managing threatened or pest species are regularly faced with this uncertainty. Wildlife diseases can drive species to extinction; thus, managing species with disease is an important part of conservation. Devil facial tumor disease (DFTD) is one such disease that led to the listing of the Tasmanian devil (Sarcophilus harrisii) as endangered. Managers aim to maintain devils in the wild by establishing disease‐free insurance populations at isolated sites. Often a resident DFTD‐affected population must first be removed. In a successful collaboration between decision scientists and wildlife managers, we used an accessible population model to inform monitoring decisions and facilitate the establishment of an insurance population of devils on Forestier Peninsula. We used a Bayesian catch‐effort model to estimate population size of a diseased population from removal and camera trap data. We also analyzed the costs and benefits of declaring the area disease‐free prior to reintroduction and establishment of a healthy insurance population. After the monitoring session in May–June 2015, the probability that all devils had been successfully removed was close to 1, even when we accounted for a possible introduction of a devil to the site. Given this high probability and the baseline cost of declaring population absence prematurely, we found it was not cost‐effective to carry out any additional monitoring before introducing the insurance population. Considering these results within the broader context of Tasmanian devil management, managers ultimately decided to implement an additional monitoring session before the introduction. This was a conservative decision that accounted for uncertainty in model estimates and for the broader nonmonetary costs of mistakenly declaring the area disease‐free.     

Fishing and echolocation behavior of the greater bulldog bat,Noctilio leporinus,in the field

When hunting for fish Noctilio leporinus uses several strategies. In high search flight it flies within 20–50 cm of the water surface and emits groups of two to four echolocation signals, always containing at least one pure constant frequency (CF) pulse and one mixed CF-FM pulse consisting of a CF component which is followed by a frequency-modulated (FM) component. The pure CF signals are the longest, with an average duration of 13.3 ms and a maximum of 17 ms. The CF component of the CF-FM signals averages 8.9 ms, the FM sweeps 3.9 ms. The CF components have frequencies of 52.8–56.2 kHz and the FM components have an average bandwidth of 25.9 kHz. A bat in high search flight reacts to jumping fish with pointed dips at the spot where a fish has broken the surface. As it descends to the water surface the bat shows the typical approach pattern of all bats with decreasing pulse duration and pulse interval. A jumping fish reveals itself by a typical pattern of temporary echo glints, reflected back to the bat from its body and from the water disturbance. In low search flight N. leporinus drops to a height of only 4–10 cm, with body parallel to the water, legs extended straight back and turned slightly downward, and feet cocked somewhat above the line of the legs and poised within 2–4 cm of the water surface. In this situation N. leporinus emits long series of short CF-FM pulses with an average duration of 5.6 ms (CF 3.1 and FM 2.6) and an average pulse interval of 20 ms, indicating that it is looking for targets within a short range. N. leporinus also makes pointed dips during low search flight by rapidly snapping the feet into the water at the spot where it has localized a jumping fish or disturbance. In the random rake mode, N. leporinus drops to the water surface, lowers its feet and drags its claws through the water in relatively straight lines for up to 10m. The echolocation behavior is similar to that of high search flight. This indicates that in this hunting mode N. leporinus is not pursuing specific targets, and that raking is a random or statistical search for surface fishes. When raking, the bat uses two strategies. In directed random rake it rakes through patches of water where fish jumping activity is high. Our interpretation is that the bat detects this activity by echolocation but prefers not to concentrate on a single jumping fish. In the absence of jumping fish, after flying for several minutes without any dips, N. leporinus starts to make very long rakes in areas where it has hunted successfully before (memory-directed random rake). Hunting bats caught a fish approximately once in every 50–200 passes through the hunting area.     

The Botanist Effect Revisited: Plant Species Richness, County Area, and Human Population Size in the United States

Abstract:  The "botanist effect" is thought to be the reason for higher plant species richness in areas where botanists are disproportionately present as an artefactual consequence of a more thorough sampling. We examined whether this was the case for U.S. counties. We collated the number of species of vascular plants, human population size, and the area of U.S. counties. Controlling for spatial autocorrelation and county area, plant species richness increased with human population size and density in counties with and without universities and/or botanical gardens, with no significant differences in the relation between the two subsets. This is consistent with previous findings and further evidence of a broad-scale positive correlation between species richness and human population presence, which has important consequences for the experience of nature by inhabitants of densely populated regions. Combined with the many reports of a negative correlation between the two variables at a local scale, the positive relation between plant species richness in U.S. counties and human population presence stresses the need for the conservation of seminatural areas in urbanized ecosystems and for the containment of urban and suburban sprawl.