Search bioRxiv⌕ Search

Biology subjects

Lopez-Quilez, A.

Publications and source records attributed to Lopez-Quilez, A..

3 recordsLinked to original sources

Designing fisheries restricted areas using standard fishery survey data: a novel multilevel spatio-temporal approach

Marine Protected Areas (MPAs) are a promising management tool for the conservation and recovery of marine ecosystems, as well as fisheries management. MPAs are generally established as permanent closures but marine systems are dynamic, which has generated debate in favour of more dynamic designs. As a consequence, the identification of priority areas should assess their persistence in space and time. Here, we develop a step-by-step approach to assess the spatiotemporal dynamics of fisheries management priority areas using standard fishery-independent survey data. To do so, we fit Bayesian hierarchical spatiotemporal SDM models to different commercially important demersal species and use the resulting maps to fit different spatial prioritisation configurations. We use these results to assess the spatiotemporal dynamics of fisheries priority areas. The proposed method is illustrated through a western Mediterranean case study using fishery-independent trawl survey data on six commercially important species collected over 17 years. We identified two fisheries priority area patterns in the study area, each predominant during a different time-period of the study, asserting the importance of regularly re-assessing MPA designs.

ecology↗

Tracking the outbreak. An optimized delimiting survey strategy for Xylella fastidiosa.

O_LICurrent legislation enforces the implementation of intensive surveillance programs for quarantine plant pathogens. After an outbreak, surveys are implemented to delimit the geographic extent of the pathogen and execute disease control. The feasibility of control programs is highly dependent on budget availability, thus it is necessary to target and optimize surveillance strategies. C_LIO_LIA sequential adaptive delimiting survey involving a three-phase and a two-phase design with increasing spatial resolution was developed and implemented for the Xylella fastidiosa outbreak in Alicante, Spain. Inspection and sampling intensities were optimized using simulation-based methods and results were validated using Bayesian spatial models. C_LIO_LIThis strategy made it possible to sequence inspection and sampling considering different spatial resolutions, and to adapt the inspection and sampling intensity according to the information obtained in the previous, coarser, spatial resolution. C_LIO_LIThe proposed strategy was able to delimit efficiently the extent of Xf improving efficiency of the current in terms of survey efforts. From a methodological perspective, our approach provides new insights of alternative delimiting designs and new reference sampling intensity values. C_LI

pathology↗

Modelling Inoculum Availability of Plurivorosphaerella nawae in Persimmon Leaf Litter with Bayesian Beta Regression

Circular leaf spot (CLS), caused by Plurivorosphaerella nawae, is a serious disease of persimmon (Diospyros kaki) inducing necrotic lesions on leaves, defoliation and fruit drop. Under Mediter-ranean conditions, P. nawae forms pseudothecia in the leaf litter during winter and ascospores are released in spring infecting susceptible leaves. Persimmon growers are advised to apply fungicides for CLS control during the period of inoculum availability, which was defined based on ascospore counts under the microscope. A model of inoculum availability of P. nawae was developed and evaluated as an alternative to ascospore counts. Leaf litter samples were collected weekly in LAlcudia from 2010 to 2015. Leaves were soaked, placed in a wind tunnel, and released ascospores of P. nawae were counted. Hierarchical Bayesian beta regression methods were used to fit the dynamics of ascospore production in the leaf litter. The selected model, having the lowest values of DIC, WAIC and LCPO, included accumulated degree days (ADD) and ADD taking into account the vapor pressure deficit (ADDvpd) as fixed effects, and year as a random effect. This model had a MAE of 0.042 and RMSE of 0.062. The beta regression model was evaluated in four orchards for different years from 2010 to 2015. Higher accuracy was obtained at the beginning and the end of the ascospore production period, which are the events of interest to schedule fungicide sprays for CLS control in Spain. This same modelling framework can be extended to other fungal plant pathogens whose inoculum dynamics are expressed as proportion data.

pathology↗