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Evaluating sustainability of fisheries bycatch mortality for marine megafauna: a review of conservation reference points for data-limited populations
- J. E. MOORE, K. A. CURTIS, R. L. LEWISON, P. W. DILLINGHAM, J. M. COPE, S. V. FORDHAM, S. S. HEPPELL, S. A. PARDO, C. A. SIMPFENDORFER, G. N. TUCK, S. ZHOU
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- Journal:
- Environmental Conservation / Volume 40 / Issue 4 / December 2013
- Published online by Cambridge University Press:
- 10 May 2013, pp. 329-344
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Fisheries bycatch threatens populations of marine megafauna such as marine mammals, turtles, seabirds, sharks and rays, but fisheries impacts on non-target populations are often difficult to assess due to factors such as data limitation, poorly defined management objectives and lack of quantitative bycatch reduction targets. Limit reference points can be used to address these issues and thereby facilitate adoption and implementation of mitigation efforts. Reference points based on catch data and life history analysis can identify sustainability limits for bycatch with respect to defined population goals even when data are quite limited. This can expedite assessments for large numbers of species and enable prioritization of management actions based on mitigation urgency and efficacy. This paper reviews limit reference point estimators for marine megafauna bycatch, with the aim of highlighting their utility in fisheries management and promoting best practices for use. Different estimators share a common basic structure that can be flexibly applied to different contexts depending on species life history and available data types. Information on demographic vital rates and abundance is required; of these, abundance is the most data-dependent and thus most limiting factor for application. There are different approaches for handling management risk stemming from uncertainty in reference point and bycatch estimates. Risk tolerance can be incorporated explicitly into the reference point estimator itself, or probability distributions may be used to describe uncertainties in bycatch and reference point estimates, and risk tolerance may guide how those are factored into the management process. Either approach requires simulation-based performance testing such as management strategy evaluation to ensure that management objectives can be achieved. Factoring potential sources of bias into such evaluations is critical. This paper reviews the technical, operational, and political challenges to widespread application of reference points for management of marine megafauna bycatch, while emphasizing the importance of developing assessment frameworks that can facilitate sustainable fishing practices.
Ability of the SUNDIAL model to simulate the short-term dynamics of 15N applied to winter wheat and oilseed rape
- B. GABRIELLE, S. RECOUS, G. TUCK, N. J. BRADBURY, B. NICOLARDOT
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- Journal:
- The Journal of Agricultural Science / Volume 137 / Issue 2 / September 2001
- Published online by Cambridge University Press:
- 24 October 2001, pp. 157-168
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Labelling using the stable 15 isotope of nitrogen allows a close monitoring of the fate of the fertilizer applied to arable crops. Because 15N data give direct estimates of nitrogen transformation rates, they also provide more stringent tests for N models than those based on bulk inorganic N dynamics. They may therefore point at flaws in models that had previously gone unnoticed, especially if 15N was monitored on short time steps which capture even rapid processes like nitrification.
Here we tested the simple, process-based model SUNDIAL on two such data sets obtained in Northern France under winter wheat and winter rape crops receiving various doses and forms of fertilizer N. In both experiments, microplots (≈ 1 m2 in size) within larger blocks were dressed with 2·0 atom-% enriched labelled 15N, as urea, or ammonium-nitrate as NH+4–15NO3 or 15NH+4–H–NO3. Replicate micro-plots were subsequently sampled on four occasions after fertilizer application, and 15N enrichment was monitored in plant roots and tops, and at several depths in the soil in inorganic and organic forms.
Comparison between observed and simulated data showed that, shortly after application, SUNDIAL either underestimated (rapeseed) or overestimated (wheat) the rates of crop uptake. Also, the gradual incorporation of 15N into soil organic matter was too quick in autumn and too slow in spring under the rapeseed crop. The simulation of the rapid depletion of the labelled soil inorganic N pool was correct under wheat, whereas under rape, SUNDIAL predicted an accumulation of nitrate which was not observed.
After a longer time interval (1–2 months), the simulated and observed amounts of fertilizer-derived N in the crop and in the soil became more comparable. However, SUNDIAL only accounted for part of the unrecovered labelled N. Additional measurements indicated that denitrification and ammonia volatilization were responsible for most of the losses, with discrepancies occurring because SUNDIAL failed to volatilize ammonia after fertilizer spreading. The other major source of error lay in the simulation of crop demand for nitrogen, which may be improved based on sounder eco-physiological concepts, such as that of a regulation of plant uptake by shoot biomass.