Carbon stock assessment and soil carbon management in agricultural land‐uses in Thailand

The organic carbon pool in agricultural land‐uses is capable of enhancing agricultural sustainability and serving as a potential sink of atmospheric carbon dioxide. A study was carried out to estimate and map carbon stock of different agricultural land‐uses in a sub‐watershed of Thailand and to assess the land‐use sustainability with respect to carbon management. A quadrat sampling methodology was adopted to estimate the biomass and its carbon content of 11 different land‐uses in the study area. Existing soil data were used to calculate the soil carbon. GIS was used for integrating biomass carbon, soil carbon and carbon stock mapping. Roth carbon model was used to project the soil carbon of present land‐uses in the coming 10 years and based on which the sustainability of land‐uses was predicted. The total carbon stock of agricultural land‐uses was estimated to be 20·5 Tg, of which 41·49 per cent was biomass carbon and 58·51 per cent was soil carbon. Among the land‐uses, para rubber had the highest average biomass C (136·34 Mg C ha⁻¹) while paddy had the lowest (7·08 Mg C ha⁻¹). About four‐fifths of agricultural land‐uses in the watershed are sustainable in maintaining the desired level of soil carbon in coming 10 years while one‐fifths are unstable. Such information on carbon stock could be valuable to develop viable land‐use options for agricultural sustainability and carbon sequestration. Copyright © 2007 John Wiley & Sons, Ltd.     

Erosion modelling approach to simulate the effect of land management options on soil loss by considering catenary soil development and farmers perception

The prevention of soil erosion is one of the most essential requirements for sustainable agriculture in developing countries. In recent years it is widely recognized that more site‐specific approaches are needed to assess variations in erosion susceptibility in order to select the most suitable land management methods for individual hillslope sections. This study quantifies the influence of different land management methods on soil erosion by modelling soil loss for individual soil‐landscape units on a hillslope in Southern Uganda. The research combines a soil erosion modelling approach using the physically based Water Erosion Prediction Project (WEPP)‐model with catenary soil development along hillslopes. Additionally, farmers' perceptions of soil erosion and sedimentation are considered in a hillslope mapping approach. The detailed soil survey confirmed a well‐developed catenary soil sequence along the hillslope and the participatory hillslope mapping exercise proved that farmers can distinguish natural soil property changes using their local knowledge. WEPP‐model simulations show that differences in soil properties, related to the topography along the hillslope, have a significant impact on total soil loss. Shoulder and backslope positions with steeper slope gradients were most sensitive to changes in land management. Furthermore, soil conservation techniques such as residue management and contouring could reduce soil erosion by up to 70 percent on erosion‐sensitive slope sections compared to that under tillage practices presently used at the study site. The calibrated model may be used as a tool to provide quantitative information to farmers regarding more site‐specific land management options. Copyright © 2008 John Wiley & Sons, Ltd.     

A pragmatic approach to modelling soil and water conservation measures with a catchment scale erosion model

To reduce soil erosion, soil and water conservation (SWC) methods are often used. However, no method exists to model beforehand how implementing such measures will affect erosion at catchment scale. A method was developed to simulate the effects of SWC measures with catchment scale erosion models. The method was implemented by applying the LISEM model to an agricultural catchment on the slopes of Mt. Kenya. The method consisted of a field scale calibration based on P-factors, followed by application at catchment scale. This calibration included factors such as saturated conductivity, Manning's n, roughness and slope angle. It was found that using data on P-factors, such models can be calibrated to give acceptable predictions at pixel scale. However, P-factors were also found to vary with land use type and storm size. Besides, more data on the physical effectiveness of SWC measures are needed. At catchment scale, the effect of SWC was found to be different from that at pixel scale. Most SWC were simulated to be more effective at catchment scale, indicating additional infiltration during transport through the catchment to the outlet. However, slope corrections in case of terraces were found to be less effective at this scale. Nevertheless, a simulation for current land use with current SWC measures indicated that these SWC measures decrease runoff by 28% and erosion by 60%.     

Groundwater modelling to assess the effect of interceptor drainage and lining

Recharge to the aquifer through seepage from irrigation canals is often quoted as one of the main causes for waterlogging in Pakistan. In the design of drainage systems to control this waterlogging, rules-of-thumb are often used to quantify the seepage from canals. This paper presents the option to use a groundwater model for a more detailed assessment. Groundwater models may assist in evaluating the effect of recharge reducing measures such as interceptor drains along irrigation canals and lining. These measures are commonly aimed at reducing the drainage requirement of adjacent agricultural lands. In this paper an example is given of the application of a numerical groundwater model, aimed at assessing the effect of interceptor drainage and canal lining in the Fordwah Eastern Sadiqia project, being a typical and well-monitored location in Pakistan. The paper also presents references to other conditions. The model was used to obtain a better insight in the key hydraulic parameters, such as the infiltration resistance of the bed and slopes of irrigation canals, the drain entry resistance of interceptor drains and the hydraulic conductivity of soil layers. The model was applied to assess the effectiveness and efficiency of interceptor drains under various conditions. The results of the study show that the net percentage of intercepted seepage is too low to have a significant effect on the drainage requirement of the adjacent agricultural lands. Besides, the operation of the system, with pumping required, is often an added headache for the institution responsible for operation of the system. The marginal effect of interceptor drains and lining on the drainage requirement of adjacent agricultural land does not always justify the large investments involved. It can be concluded that:

Ecosystem‐based forecasts of recruitment in two menhaden species

Gulf (Brevoortia patronus, Clupeidae) and Atlantic menhaden (Brevoortia tyrannus, Clupeidae) support large fisheries that have shown substantial variability over several decades, in part, due to dependence on annual recruitment. Nevertheless, traditional stock–recruitment relationships lack predictive power for these stocks. Current management of Atlantic menhaden explicitly treats recruitment as a random process. However, traditional methods for understanding recruitment variability carry the very specific hypothesis that the effect of adult biomass on subsequent recruitment occurs independently of other ecosystem factors such as food availability and predation. Here, we evaluate the predictability of menhaden recruitment using a model‐free approach that is not restricted by these strong assumptions. We find that menhaden recruitment is predictable, but only when allowing for interdependence of stock with other ecological factors. Moreover, while the analysis confirms the presence of environmental effects, the environment alone does not readily account for the complexity of menhaden recruitment dynamics. The findings set the stage for revisiting recruitment prediction in management and serve as an instructive example in the ongoing debate about how to best treat and understand recruitment variability across species and fisheries.     

Assessing the population transmission dynamics of tilapia lake virus in farmed tilapia

A novel virus, tilapia lake virus (TiLV), has been identified as a key pathogen responsible for disease outbreak and mass mortality of farmed tilapia. We used a deterministic susceptible‐infectious‐mortality (SIM) model to derive key disease information appraised with published TiLV‐induced cumulative mortality data. The relationship between tilapia mortality and TiLV exposure dosages was described by the Hill model. Furthermore, a disease control model was proposed to determine the status of controlled TiLV infection using a parsimonious control reproduction number (R_C)‐control line criterion. Results showed that the key disease determinants of transmission rate and basic reproduction number (R₀) could be derived. The median R₀ estimate was 2.59 in a cohabitation setting with 2.6 × 10⁵ TCID50 fish^?1 TiLV. The present R_C‐control model can be employed to determine whether TiLV containment is feasible in an outbreak farm by quantifying the current level of transmission. The SIM model can then be applied to predict what additional control is required to manage R_C < 1. We offer valuable tools for aquaculture engineers and public health scientists the mechanistic‐based assessment that allows a more rigorous evaluation of different control strategies to reduce waterborne diseases in aquaculture farming systems.     

Population viability and perturbation analyses to support recovery of imperilled Eastern Sand Darter (Ammocrypta pellucida)

Small‐bodied freshwater fishes are often understudied, with the result that data gaps create uncertainties that can complicate and constrain conservation strategies aimed at species recovery. Use of matrix models and perturbation population viability analyses (PVA) are ideally suited for use in studying the consequences of life‐history parameter variation and environmental stochasticity to better understand the fate of threatened small‐bodied fishes. We use data for Eastern Sand Darter (Ammocrypta pellucida) populations from the Thames River, Canada, to explore the consequences of life‐history uncertainties such as age at maturation, multiple clutch sizes and age‐specific fertility for population recovery in this species. Environmental stochasticity acting on all life‐history parameters was found to pose significant risks for the continued viability of lower Thames River populations, with significant chances of local extinction predicted under current conditions. The intrinsic rate of population increase was most sensitive to 0+ survival rates, clutch size and clutch number. As demonstrated here, population models can successfully provide a means of exploring the population dynamics of small‐bodied fishes and can inform managers of risks posed by factors acting on life‐history parameters to affect continued population viability. Management actions for Eastern Sand Darter should focus on strategies designed to ensure successful spawning and improvement of 0+ survival rates, through programmes aimed at the protection, enhancement or recovery of additional spawning and juvenile rearing habitats.     

Identification of Visceral Leishmaniasis‐Susceptible Areas using Spatial Modelling in Southern Caucasus

This study explores the application of spatial modelling techniques to generate susceptibility maps for a neglected zoonotic disease, visceral leishmaniasis (VL), in an endemic area in southern Caucasus that includes Iran, Armenia and Azerbaijan. The social and physical environment of southern Caucasus has been mainly characterized by the presence of several factors that are strongly associated with VL, which has caused a significant number of infections during the past decade. Three popular spatial modelling techniques, consisting of the weights of evidence, logistic regression and fuzzy logic methods, were evaluated and trained using a study area in north‐western Iran where an inventory of highly infected areas and high‐quality evidential factors was available. Model performance was assessed using the receiver‐operating characteristic (ROC) approach. According to the results of these assessments, the fuzzy logic method with γ = 0.5 was chosen for the prediction of VL incidence in southern Caucasus. The susceptibility map generated using the fuzzy logic method indicated that VL followed a spatial pattern at the conjunction of the three countries, which suggests that the prevalence of VL in southern Caucasus is socio‐ecologically dependent.     

Predicting weed distribution at the regional scale in the native range: environmental determinants and biocontrol implications of Phyla nodiflora (Verbenaceae)

Alien plants produce severe environmental and economic losses in the territories they invade. Modelling the spatial distribution of alien species as a function of the environment in the native range has therefore become an essential first step in the struggle against invasions. Phyla nodiflora var. minor is a fast‐growing perennial herb native to South America that has spread through three continents, where it poses a major threat to biodiversity and significantly impacts on conservation and grazing systems, mainly in riparian areas. To assess the distribution of native Argentine populations of P. nodiflora as a function of the environment, we conducted long‐term roadside surveys and associated the occurrence of the plant with climatic, geographical, demographical and vegetation cover variables in a generalised linear mixed model. The plant was recorded in 230 of 431 sites, mostly east of 66°W and north of 39°S. According to the best model, which predicted the data 58% better than random assignment, its occurrence was associated with temperature variables (mean annual values and daytime range) and relative humidity. Based on these associations, we generated a presence probability map for the occurrence of P. nodiflora in southern South America. Understanding the environmental determinants of the distribution of weeds in their native range provides valuable baseline data to further manage the spread of alien species.