The Economic Value of Rebuilding Fisheries

The global demand for protein from seafood –- whether wild, caught or cultured, whether for direct consumption or as feed for livestock –- is high and projected to continue growing. However, the ocean's ability to meet this demand is uncertain due to either mismanagement or, in some cases, lack of management of marine fish stocks. Efforts to rebuild and recover the world's fisheries will benefit from an improved understanding of the long-term economic benefits of recovering collapsed stocks, the trajectory and duration of different rebuilding approaches, variation in the value and timing of recovery for fisheries with different economic, biological, and regulatory characteristics, including identifying which fisheries are likely to benefit most from recovery, and the benefits of avoiding collapse in the first place. These questions are addressed in this paper using a dynamic bioeconomic optimisation model that explicitly accounts for economics, management, and ecology of size-structured exploited fish populations. Within this model framework, different management options (effort controls on small-, medium-, and large-sized fish) including management that optimises economic returns over a specified planning horizon are simulated and the consequences compared. The results show considerable economic gains from rebuilding fisheries, with magnitudes varying across fisheries

Survival, movement, and resource selection of male mule deer and white-tailed deer in western Kansas

Master of ScienceDepartment of BiologyDavid A. HaukosAbundance and occupied range of mule deer (Odocoileus hemionus) in Kansas have been declining for 20 years. The two predominant hypotheses for the reduction of mule deer and concurrent expansion of white-tailed deer (O. virginianus) are changes in land use and competitive dominance of white-tailed deer over mule deer. Despite the popularity and income that stem from hunting revenue, there have been no recent studies that provide critical insight on how to improve management and conservation of sympatric populations of either deer species in Kansas. My objectives were to (1) test for differences in annual and weekly survival rates between species, identify temporal mortality patterns, and assess influences of hunting and rut on survival; and (2) examine movement patterns, space use, and population-level resource selection by adult male mule deer and white-tailed deer in western Kansas during three time periods (annually, rut, and 12-day firearm season). I deployed GPS-collared 60 (30 mule; 30 white-tailed deer), 25 (12 mule; 13 white-tailed deer), and 26 (13 mule; 13 white-tailed deer) male mule deer and white-tailed deer at two different study sites (north and south) located in western Kansas in 2018, 2019, and 2020, respectively, maintaining a sample size of 60 at the start of each study year. Each deer was fitted with a high resolution GPS/VHF collar that recorded bi-hourly locations and used an activity sensor to identify mortality events. I assigned each deer to an age class (<3 or ≥3 years old). I analyzed the influence of single variable models (age class, species, study site, year, site and year interaction, and morphological measurements [total body length, chest girth, hind foot, and neck girth]) to identify variables that influenced survival. I calculated average daily and average bi-hourly movement rate for all groups (north mule deer, south mule deer, north white-tailed deer and south white-tailed deer) and analyzed peak movement trends to define the rut periods for each species. I used Biased Random Bridge Movement Models to estimate period home ranges and core use areas by species and sites and tested for species*site interactions. I identified temporal space use of different land cover categories during the annual, rut, and 12-day firearm season periods. I compared used and available proportions of categorical land cover and continuous macro habitat features at second-order resource selection. Annual survival did not differ between species during 2018-2020 (mule deer 0.54 ± 0.05, white-tailed deer 0.58 ± 0.05); pooled survival for combined species was 0.56 ± 0.04. December was the most hazardous time of year for both species. Harvest was the predominant cause of mortality (50% of mortalities [firearm = 42%, archery = 8%]. Other sources of mortality stemmed from natural causes (21%), unknown (25%), and deer-vehicle collisions (4%). Kaplan-Meier cumulative survival results showed that survival of both mule deer and white-tailed deer was affected by harvest season and rut; the two weeks of firearm season heavily reduced survival by 19.6%, and 12.4% for mule deer and white-tailed deer, respectively. Survival was reduced by 10.6% and 9.8% during rut for mule deer and white-tailed deer, respectively. Additionally, site and year interaction (ω = 0.38) was the most parsimonious model for predicting adult male survival, the model site, was also competitive. Localized periods of high mortality occurred; compared to 2018 and 2019, deer survival in the north site during 2020 was drastically lower (0.26 ± 0.09) than other annual species-site combinations. Space use at the landscape scale varied temporally by site and species. Population-level selection of macro habitat differed between species Males reduced both bi-hourly movement rate and daily distance during the 12-day firearm period compared to their rut movements; north mule deer reduced their total daily movement by 35%, south mule deer by 33%, north white-tailed deer by 5% and south white-tailed deer by 32%. Rut (~Nov 5-25 for both species of north deer; ~Oct 29-Nov 18 for south mule deer; ~Oct 29-Nov 25 for south white-tailed deer) begins for both species approximately 3-4 weeks prior to the 12-day firearm period. Peak movement periods occurred during rut simultaneously for both species, with all deer moving at least twice as fast (bi-hourly) and twice as much (in 24 hr. intervals) during their rut seasons compared to their annual movements. Males reduced movement during the 12-day firearm season compared to their rut movements because of the proximity of the successive 12-day firearm season to the post-rut period; a time in which males may move less in an attempt to recover from the physiological demands of rut. Speculatively, hunters on the landscape may have been a contributing factor to the decrease in movement. To combat the current population trajectory of mule deer abundance and augment the management and conservation of mule deer, I suggest decreasing the harvest limit of male mule deer to directly increase annual survival of adult male mule deer

The Relationship Between Disperal Ability and Geographic Range Size

There are a variety of proposed evolutionary and ecological explanations for why some species have more extensive geographical ranges than others. One of the most common explanations is variation in species’ dispersal ability. However, the purported relationship between dispersal distance and range size has been subjected to few theoretical investigations, and empirical tests reach conflicting conclusions. We attempt to reconcile the equivocal results of previous studies by reviewing and synthesizing quantitative dispersal data, examining the relationship between average dispersal ability and range size for different spatial scales, regions and taxonomic groups. We use extensive data from marine taxa whose average dispersal varies by seven orders of magnitude. Our results suggest dispersal is not a general determinant of range size, but can play an important role in some circumstances. We also review the mechanistic theories proposed to explain a positive relationship between range size and dispersal and explore their underlying rationales and supporting or refuting evidence. Despite numerous studies assuming a priori that dispersal influences range size, this is the first comprehensive conceptual evaluation of these ideas. Overall, our results indicate that although dispersal can be an important process moderating species’ distributions, increased attention should be paid to other processes responsible for range size variation

Fitting statistical distributions to sea duck count data: Implications for survey design and abundance estimation

Determining appropriate statistical distributions for modeling animal count data is important for accurate estimation of abundance, distribution, and trends. In the case of sea ducks along the U.S. Atlantic coast, managers want to estimate local and regional abundance to detect and track population declines, to define areas of high and low use, and to predict the impact of future habitat change on populations. In this paper, we used a modified marked point process to model survey data that recorded flock sizes of Common eiders, Long-tailed ducks, and Black, Surf, and White-winged scoters. The data come from an experimental aerial survey, conducted by the United States Fish & Wildlife Service (USFWS) Division of Migratory Bird Management, during which east-west transects were flown along the Atlantic Coast from Maine to Florida during the winters of 2009–2011. To model the number of flocks per transect (the points), we compared the fit of four statistical distributions (zero-inflated Poisson, zero-inflated geometric, zero-inflated negative binomial and negative binomial) to data on the number of species-specific sea duck flocks that were recorded for each transect flown. To model the flock sizes (the marks), we compared the fit of flock size data for each species to seven statistical distributions: positive Poisson, positive negative binomial, positive geometric, logarithmic, discretized lognormal, zeta and Yule–Simon. Akaike’s Information Criterion and Vuong’s closeness tests indicated that the negative binomial and discretized lognormal were the best distributions for all species for the points and marks, respectively. These findings have important implications for estimating sea duck abundances as the discretized lognormal is a more skewed distribution than the Poisson and negative binomial, which are frequently used to model avian counts; the lognormal is also less heavy-tailed than the power law distributions (e.g., zeta and Yule–Simon), which are becoming increasingly popular for group size modeling. Choosing appropriate statistical distributions for modeling flock size data is fundamental to accurately estimating population summaries, determining required survey effort, and assessing and propagating uncertainty through decision-making processes

Appreciating interconnectivity between habitats is key to blue carbon management

We welcome the recent synthesis by Howard et al. (2017), which drew attention to the role of marine systems and natural carbon sequestration in the oceans as a fundamental aspect of climate-change mitigation. The importance of long-term carbon storage in marine habitats (ie ?blue carbon?) is rapidly gaining recognition (Figure 1a) and is increasingly a focus of national and international attempts to mitigate rising atmospheric emissions of carbon dioxide. However, effectively managing blue carbon requires an appreciation of the inherent connectivity between marine populations and habitats. More so than their terrestrial counterparts, marine ecosystems are ?open?, with high rates of transfer of energy, matter, genetic material, and species across regional seascapes (Kinlan and Gaines 2003). We suggest that policy frameworks, and the science underpinning them, should focus not only on carbon sink habitats but also on carbon source habitats, which play critical roles in marine carbon cycling and natural carbon sequestration in the oceans. Howard et al. (2017) concluded that certain habitats and taxa (eg kelp forests, large vertebrates) are "unimportant? in natural carbon sequestration, which we argue is an oversimplification that fails to account for not only the magnitude of carbon transfer between living components of the cycle but also the interconnectedness of the highly dynamic and open marine environment. Crucially, developing carbon budgets for habitats in isolation ? without considering their connectivity and functioning as carbon ?fixers?, ?donors?, and ?recipients? ? is neither representative of marine ecosystems, nor a useful approach for prioritizing management. Here, we highlight the importance of carbon transfer between habitats, which is not currently recognized within policy frameworks, through two pertinent and widespread processesauthorsversionPeer reviewe

Statistical analyses to support guidelines for marine avian sampling: Final report. [Digital Supplements A-G attached]

Interest in development of offshore renewable energy facilities has led to a need for high-quality, statistically robust information on marine wildlife distributions. A practical approach is described to estimate the amount of sampling effort required to have sufficient statistical power to identify species specific “hotspots” and “coldspots” of marine bird abundance and occurrence in an offshore environment divided into discrete spatial units (e.g., lease blocks), where “hotspots” and “coldspots” are defined relative to a reference (e.g., regional) mean abundance and/or occurrence probability for each species of interest. For example, a location with average abundance or occurrence that is three times larger the mean (3x effect size) could be defined as a “hotspot,” and a location that is three times smaller than the mean (1/3x effect size) as a “coldspot.” The choice of the effect size used to define hot and coldspots will generally depend on a combination of ecological and regulatory considerations. A method is also developed for testing the statistical significance of possible hotspots and coldspots. Both methods are illustrated with historical seabird survey data from the USGS Avian Compendium Database

Chapter 7: Seabirds

This chapter describes an assessment of the at-sea distribution of seabirds around the Main Hawaiian Islands (MHI). We analyzed at-sea visual sighting data collected by the National Oceanic and Atmospheric Administration’s (NOAA) National Marine Fisheries Service (NMFS) Southwest Fisheries Science Center (SWFSC) on shipboard surveys conducted during May and August-December between 1989 and 2012. We present the locations of sightings of 24 species, and for 14 of these species we develop spatial predictive models of relative density throughout the study area. Model predictions are presented with associated measures of precision and statistical fit in terms of a suite of performance metrics. Spatial distributions varied across species, with the majority of sightings occurring relatively close to land, occurring in particular parts of the study area, or occurring more evenly throughout the study area. Predicted spatial distributions for species that were modeled broadly aligned with the distributions of sightings. Some of the most important model predictor variables across species were day of the year, distance to shore or nearest terrestrial site, depth, sea surface height and projected longitude/latitude. Our assessment provides broad-scale spatial information that can aid marine spatial planning around the MHI. Importantly, our assessment also highlights gaps and limitations in the available data, which can guide future data collection efforts. In addition to our assessment, we discuss other studies and available datasets on the at-sea distribution of seabirds around the MHI

New records of the rare deep-water alga Sebdenia monnardiana (Rhodophyta) and the alien Dictyota cyanoloma (Phaeophyceae ) and the unresolved case of deep-water kelp in the Ionian and Aegean Seas (Greece)

Parts of the macroalgal flora of the eastern Mediterranean remain incompletely known. This applies in particular to the circalittoral communities. This study, based upon 2 cruises in the Ionian and Aegean Seas, surveyed benthic communities from 40 to 150 m depth by remotely-operated vehicle (ROV) with a special focus on detecting communities of the Mediterranean deep-water kelp Laminaria rodriguezii. These were complemented by shallow-water surveys on adjacent coastlines by snorkelling and scuba diving. While no kelp could be detected at any of the sites surveyed, ROV surveys of northern Euboia Island revealed the first east Mediterranean record of Sebdenia monnardiana (Sebdeniales, Rhodophyta). Snorkelling surveys on the coast of southeast Kefalonia yielded the first record of the alien alga Dictyota cyanoloma in Greece. This paper reports rbcL and SSU sequences for Sebdenia monnardiana, and COI for Dictyota cyanoloma.Peer reviewe