Utilizing a DUALEM‐421 and inversion modelling to map baseline soil salinity along toposequences in the Hunter Valley Wine district

In the oldest commercial wine district of Australia, the Hunter Valley, there is the threat of soil salinization because marine sediments underlie the area. To understand the risk requires information about the spatial distribution of soil properties. Electromagnetic (EM) induction instruments have been used to identify and map the spatial variation of average soil salinity to a certain depth. However, soils vary with depth dependent on soil forming factors. We collected data from a single‐frequency and multiple‐coil DUALEM‐421 along a toposequence. We inverted this data using EM4Soil software and evaluated the resultant 2‐dimensional model of true electrical conductivity (σ – mS/m) with depth against electrical conductivity of saturated soil pastes (EC_p – dS/m). Using a fitted linear regression (LR) model calibration approach and by varying the forward model (cumulative function‐CF and full solution‐FS), inversion algorithm (S1 and S2), damping factor (λ) and number of arrays, we determined a suitable electromagnetic conductivity image (EMCI), which was optimal (R² = 0.82) when using the full solution, S2, λ = 3.6 and all six coil arrays. We conducted an uncertainty analysis of the LR model used to estimate the electrical conductivity of the saturated soil‐paste extract (EC_e – dS/m). Our interpretation based on estimates of EC_e suggests the approach can identify differences in salinity, how these vary with parent material and how topography influences salt distribution. The results provide information leading to insights into how soil forming factors and agricultural practices influence salinity down a toposequence and how this can guide soil management practices.     

Simulating the effects of tax exemptions on fertiliser use in Benin by linking biophysical and economic models

The sluggish increase in the area productivity of staple crops is a major factor causing increased dependence of African countries on food imports. The increased use of mineral fertiliser may dramatically improve the food balance of many countries and result in lower food prices, higher food supply and consumption, and improved food security and nutritional status. In Benin, West Africa, political measures to improve farmers’ access to fertiliser are biased in favour of cotton production. This article simulates the impact of universal tax exemptions for fertiliser use on crop yields, food balances, and the use of land resources for the most important staple crops in Benin using a crop growth model and an agricultural sector model. The simulation results indicate that tax exemptions on fertiliser use could have positive effects on physical productivity and would increase food security until 2025 as compared to a baseline scenario. At the same time, the pressure on land resources would not be aggravated, so that better access to fertiliser may help to curb excessive cropland expansion in Benin.     

Genomic Prediction of Arsenic Tolerance and Grain Yield in Rice: Contribution of Trait-Specific Markers and Multi-Environment Models

Many rice-growing areas are affected by high concentrations of arsenic(As). Rice varieties that prevent As uptake and/or accumulation can mitigate As threats to human health. Genomic selection is known to facilitate rapid selection of superior genotypes for complex traits. We explored the predictive ability(PA) of genomic prediction with single-environment models, accounting or not for trait-specific markers, multi-environment models, and multi-trait and multi-environment models, using the genotypic(1600 K SNPs) and phenotypic(grain As content, grain yield and days to flowering) data of the Bengal and Assam Aus Panel. Under the base-line single-environment model, PA of up to 0.707 and 0.654 was obtained for grain yield and grain As content, respectively; the three prediction methods(Bayesian Lasso, genomic best linear unbiased prediction and reproducing kernel Hilbert spaces) were considered to perform similarly, and marker selection based on linkage disequilibrium allowed to reduce the number of SNP to 17 K, without negative effect on PA of genomic predictions. Single-environment models giving distinct weight to trait-specific markers in the genomic relationship matrix outperformed the base-line models up to 32%. Multi-environment models, accounting for genotype × environment interactions, and multi-trait and multi-environment models outperformed the base-line models by up to 47% and 61%, respectively. Among the multi-trait and multi-environment models, the Bayesian multi-output regressor stacking function obtained the highest predictive ability(0.831 for grain As) with much higher efficiency for computing time. These findings pave the way for breeding for As-tolerance in the progenies of biparental crosses involving members of the Bengal and Assam Aus Panel. Genomic prediction can also be applied to breeding for other complex traits under multiple environments.     

Predicting use of habitat patches by spawning horseshoe crabs (Limulus polyphemus) along a complex coastline with field surveys and geospatial analyses

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A first step towards improving copepod cultivation using modelling: the effects of density,crowding, cannibalism,tank design and strain selection on copepod egg production yields

Copepods are the optimal live feed for hatcheries and improvement of cultivation techniques, to provide a constant food source, is crucial for the expansion of the industry. However, studies based on experimental work and real observations can be labour intensive and expensive. A simple model was developed based on the well‐known life history traits of Acartia tonsa to describe batch cultures and their productivity. Model results were compared to observations from real cultures. For maximizing egg production yields, the optimal stocking density of copepods should be adapted to the design (depth) of the culture tanks. At high densities, stress due to encountering conspecifics, as well as cannibalism of eggs by adults, limits egg production yields. Using this model, the potential selection efficacy of copepod strains was also evaluated in order to increase production yields. Selecting larger copepods increases the egg production per litre of culture, but decreases the optimal stocking density and the range of densities at which egg production yield is high, and vice‐versa. Selecting copepods that are less affected by stress due to conspecifics only affect production yields at very high adult densities. However, selecting copepods with a high Specific Growth Rate (SGR), or improving their SGR, was found to be an alternative which did not affect the optimal cultivation densities but improved egg production yields.     

Predictive mapping for management and conservation of seagrass beds in North Carolina

An Erratum has been published for this article in Aquatic Conservation: Marine and Freshwater Ecosystems 12(2), 2002 577

• 1. This research extends techniques of predictive mapping from their application in terrestrial environments to marine landscapes by investigating the relationship between seagrass and hydrodynamics in Core Sound, North Carolina, USA.
• 2. An empirically derived logistic multiple regression model and a Boolean logic suitability model were used to produce several predictive map products, including: susceptibility of seagrasses to storms, probability of seagrass cover, and suitability of areas for restoration of seagrasses. A visual comparison between these maps and conventional seagrass polygon maps allows for a discussion of ‘field’ versus ‘object’ mapping, and the ramifications for management based on different cartographic techniques.
• 3. The predictive method used here showed that only a small portion (19%) of the seagrass bed in the study area would be expected to have a high probability of seagrass coverage. The majority of the seagrass habitat in the study area was predicted to have less than 50% probability of seagrass cover. In addition, 16% of the nearly 2000 ha of seagrass within the study area were predicted to be highly susceptible to acute storm events. Moreover, using a conservative set of site selection criteria, only 7% of the study area encompassed by seagrass habitat was predicted to have a high probability of successful restoration if injured.
• 4. This method provides for an inexpensive way to scale‐up from high‐resolution data to a coarser scale that is often required for conservation and management.

Copyright © 2001 John Wiley & Sons, Ltd.     

Modelling agroforestry systems of cacao (Theobroma cacao) with laurel (Cordia alliodora) and poro (Erythrina poeppigiana) in Costa Rica

The agroforestry systems of cacao (Theobroma cacao) under laurel (Cordia alliodora) and cacao under poro (Erythrina poeppigiana) were studied at CATIE, Turrialba, Costa Rica. An inventory was taken of the organic matter and nutrients (N, P, K, Ca, and Mg) separating the species into their compartments (leaves, branches, trunks and roots). Studies of the litter and of the mineral soil (0–45 cm) yielded these results: Patterns of nutrient accumulation are discussed in relation to the characteristics of these agroforestry systems.     

Modelling agroforestry systems of cacao (Theobroma cacao) with laurel (Cordia alliodora) and poro (Erythrina poeppigiana) in Costa Rica III. Cycles of organic matter and nutrients

Models for cycles for organic matter and nutrients element (N, P, K, Ca and Mg) are presented for the agroforestry systems of cacao (Theobroma cacao) withCordia alliodora orErythrina poeppigiana in Turrialba, Costa Rica. For the models, system reserves (soil, humus, vegetation divided into leaves, branches, stems, fine roots, fruits) and transference between compartments (production and decomposition of litter residues) inputs (fertilizer, rainfall) and outputs (harvests) of the system are considered. The implications of the models are discussed in detail. Aspects of net primary production in the systems studied are considered. N fixation is calculated on the basis of balances. Analysis of soil water showed high variations that coincided with rainfall patterns and pruning of theE. poeppigiana. For part I see Vol. 4, No. 3, 1986 For part II see this issue Agroforestry Project, CATIE/GTZ (Tropical Agricultural Research and Training Center/Gesellschaft für Technische Zusammenarbeit), Turrialba, Costa Rica     

Trawl fishing impacts on the status of seabed fauna in diverse regions of the globe

Bottom trawl fishing is a controversial activity. It yields about a quarter of the world's wild seafood, but also has impacts on the marine environment. Recent advances have quantified and improved understanding of large‐scale impacts of trawling on the seabed. However, such information needs to be coupled with distributions of benthic invertebrates (benthos) to assess whether these populations are being sustained under current trawling regimes. This study collated data from 13 diverse regions of the globe spanning four continents. Within each region, we combined trawl intensity distributions and predicted abundance distributions of benthos groups with impact and recovery parameters for taxonomic classes in a risk assessment model to estimate benthos status. The exposure of 220 predicted benthos‐group distributions to trawling intensity (as swept area ratio) ranged between 0% and 210% (mean = 37%) of abundance. However, benthos status, an indicator of the depleted abundance under chronic trawling pressure as a proportion of untrawled state, ranged between 0.86 and 1 (mean = 0.99), with 78% of benthos groups > 0.95. Mean benthos status was lowest in regions of Europe and Africa, and for taxonomic classes Bivalvia and Gastropoda. Our results demonstrate that while spatial overlap studies can help infer general patterns of potential risk, actual risks cannot be evaluated without using an assessment model that incorporates trawl impact and recovery metrics. These quantitative outputs are essential for sustainability assessments, and together with reference points and thresholds, can help managers ensure use of the marine environment is sustainable under the ecosystem approach to management.     

Where do you think you’re going? Accounting for ontogenetic and climate‐induced movement in spatially stratified integrated population assessment models

Understanding spatial population structure and biocomplexity is critical for determining a species’ resilience to environmental and anthropogenic perturbations. However, integrated population models (IPMs) used to develop management advice for harvested populations have been slow to incorporate spatial dynamics. Therefore, limited research has been devoted to understanding the reliability of movement parameter estimation in spatial population models, especially for spatially dynamic marine fish populations. We implemented a spatial simulation–estimation framework that emulated a generic marine fish metapopulation to explore the impact of ontogenetic movement and climate‐induced distributional shifts between two populations. The robustness of spatially stratified IPMs was explored across a range of movement parametrizations, including ignoring connectivity or estimating movement with various levels of complexity. Ignoring connectivity was detrimental to accurate estimation of population‐specific biomass, while implementing spatial IPMs with intermediate levels of complexity (e.g. estimating movement in two‐year and two‐age blocks) performed best when no a priori information about underlying movement was available. One‐way distributional shifts mimicking climate‐induced poleward migrations presented the greatest estimation difficulties, but the incorporation of auxiliary information on connectivity (e.g. tag‐recapture data) reduced bias. The continued development of spatially stratified modelling approaches should allow harvested resources to be better utilized without increased risk. Additionally, expanded collection and incorporation of unique spatially explicit data will enhance the robustness of IPMs in the future.