A multi-method approach to delineate and validate migratory corridors

Context

Managers are faced with numerous methods for delineating wildlife movement corridors, and often must make decisions with limited data. Delineated corridors should be robust to different data and models.

Objectives

We present a multi-method approach for delineating and validating wildlife corridors using multiple data sources, which can be used conserve landscape connectivity. We used this approach to delineate and validate migration corridors for wildebeest (Connochaetes taurinus) in the Tarangire Ecosystem of northern Tanzania.

Methods

We used two types of locational data (distance sampling detections and GPS collar locations), and three modeling methods (negative binomial regression, logistic regression, and Maxent), to generate resource selection functions (RSFs) and define resistance surfaces. We compared two corridor detection algorithms (cost-distance and circuit theory), to delineate corridors. We validated corridors by comparing random and wildebeest locations that fell within corridors, and cross-validated by data type.

Results

Both data types produced similar RSFs. Wildebeest consistently selected migration habitat in flatter terrain farther from human settlements. Validation indicated three of the combinations of data type, modeling, and corridor detection algorithms (detection data with Maxent modeling, GPS collar data with logistic regression modeling, and GPS collar data with Maxent modeling, all using cost-distance) far outperformed the other seven. We merged the predictive corridors from these three data-method combinations to reveal habitat with highest probability of use.

Conclusions

The use of multiple methods ensures that planning is able to prioritize conservation of migration corridors based on all available information.

     

“WaterMan”: an on-farm water management game with heuristic capabilities

A modern computer-based simulation tool (WaterMan) in the form of a game for on-farm water management was developed for application in training events for farmers, students, and irrigators. The WaterMan game utilizes an interactive framework, thereby allowing the user to develop scenarios and test alternatives in a convenient, risk-free environment. It includes a comprehensive soil water and salt balance calculation algorithm. It also employs heuristic capabilities for modeling all of the important aspects of on-farm water management, and to provide quantitative performance evaluations and practical water management advice to the trainees. Random events (both favorable and unfavorable) and different strategic decisions are included in the game for more realism and to provide an appropriate level of challenge according to player performance. Thus, the ability to anticipate the player skill level, and to reply with random events appropriate to the anticipated level, is provided by the heuristic capabilities used in the software. These heuristic features were developed based on a combination of two artificial intelligence approaches: (1) a pattern recognition approach and (2) reinforcement learning based on a Markov decision processes approach, specifically the Q-learning method. These two approaches were combined in a new way to account for the difference in the effect of actions taken by the player and action taken by the system in the game world. The reward function for the Q-learning method was modified to reflect the suggested classification of the WaterMan game as what is referred to as a partially competitive and partially cooperative game.     

Promoting sustainable intensification in precision agriculture: review of decision support systems development and strategies

Precision agriculture provides important issues toward a more sustainable agriculture. Many farmers have the necessary technology to operate site-specifically, but they do not use it in practice, and thus available information and communications technology (ICT) systems are not used to their full potential. This paper addresses how to reduce the so-called “problem of implementation”, based on the knowledge that participatory approaches during the design and development process is one of the most important factors to frame technology adoption. The development of sustainable ICT systems through theories and methodologies from the fields of human computer interaction and user-centered design (UCD) is presented and an ongoing Swedish project for development of an agricultural decision support system (AgriDSS) for nitrogen fertilization is used as an example to frame the issue. The overreaching aim is to develop AgriDSSs that are sustainable in design as well as through design by stressing the importance of participatory approaches for the successful development of AgriDSSs. The Swedish project has the intention to apply a UCD approach, and some pitfalls on starting to use this way of working is identified as well as some suggestions on how to reduce them through co-learning processes. Despite the challenges presented in this paper, ICT can contribute significantly to long-term sustainable development. Thus, several competences and scientific disciplines need to act in concert to help develop a sustainable development of agriculture via a transdisciplinary approach that can make an impact on society at many levels.     

Inconspicuous restraint of rice seedling growth by root-infecting fungi in soil of a rice paddy field

 Rice seedling growth, estimated by plant height and root development and discoloration, was better in pasteurized soil than in unpasteurized soil obtained from a flooded rice field. Rice seedlings also grew better in sterilized soil modified by adding roots harvested from the pasteurized soil than in soil modified by adding roots harvested from the unpasteurized soil. The results demonstrate that seedling growth in the rice field soil was inhibited by soil microorganisms, even though no typical symptoms such as seedling blight or damping-off appeared. Pythium aristosporum is suggested to be involved in the inhibition. Thus, it appears that inconspicuous restraint of rice seedling growth could occur in soils of rice paddy fields. Received: May 20, 2002 / Accepted: October 16, 2002 Acknowledgments The authors thank Dr. T. Ichitani, former professor at Osaka Prefectural University, for providing an isolate of Pythium aristosporum for comparison, and Mr. Mitsuaki Sato of Akita Prefectural College of Agriculture for technical assistance.     

Soybean oil content QTL mapping and integrating with meta-analysis method for mining genes

Oil content of soybean was a valuable quantitative trait controlled by multiple genes. Eleven QTLs were detected by both CIM and MIM method with the population crossed between Charleston and Dong nong594 in recent 3 years (2007, 2008, 2009). Combining the QTLs collected over the past 20 years, an integrated map of oil-content major QTLs in soybean was established using soymap2, which was published in 2004, as a reference. Using the software BioMercator ver.2.1, QTLs were projected from their own maps onto the reference map. In total, ninety-eight QTLs were integrated into soymap2. A meta-analysis method was used to narrow down the confidence interval, and 20 consensus QTLs and their corresponding markers were obtained. Using a local version of GENSCAN, 10,137 sequences in the consensus QTL intervals were predicted. With BLAST, these predicted genes were compared to the International Protein Index database to mine the related genes. The results offer a basis for gene mining and molecular breeding in soybean.     

Heterosis,molecular diversity,combining ability and their interrelationships in short duration maize (<Emphasis Type="Italic">Zea mays</Emphasis> L.) across the environments

Five inbred lines, 10 single cross maize (Zea mays L.) hybrids and two standard cultivars as check were used to study the combining abilities and heterosis under three environmental conditions. Random amplified polymorphic DNAs (RAPDs) markers were used to study the genetic diversity (GD) and further to analyze relationship of RAPDs based GD with combining ability and heterosis in short duration maize. Spearman’s rank correlation coefficients and linear regressions were analyzed to identify the most important factor determining heterosis and per se performance of the hybrids. Variances due to general combining ability (GCA), specific combining ability (SCA) and their interactions with environment were found to be significant. Twenty random primers generated 179 RAPD fragments. Of these, 102 RAPD fragments were polymorphic. GD was determined using Jaccard’s similarity coefficient, and a dendogram was constructed by UPGMA cluster analysis. The RAPDs based GD exhibited non-significant negative or positive association, non-significant linear regression along with very low coefficient of determination (R ²) with SCA, high and mid parent heterosis (HP and MP) and per se performance of the hybrids. Significant positive correlations and regressions along with high coefficients of determination were recorded for SCA with HP, MP and per se performance of the hybrids. The HP and MP also established significant positive association and linear regression along with high coefficient of determination with per se performance of hybrids whereas the parental mean did not establish any significant correlations with the GD, HPH, MPH and grain yield of F₁s. The present investigation, therefore, did not find any role of RAPDs based GD in determining hybrid heterosis and hybrid performance in short duration sub-tropical maize. The SCA, however, has emerged as the most important factor in determination of heterosis as well as per se performance of the hybrids in short duration maize.     

Effects of carbon and nitrogen amendment on soil carbon and nitrogen mineralization in volcanic immature soil in southern Kyushu,Japan

Soil N mineralization is affected by microbial biomass and respiration, which are limited by available C and N. To examine the relationship between C and N for soil microbial dynamics and N dynamics, we conducted long-term laboratory incubation (150 days) after C and N amendment and measured changes in C and N mineralization, microbial biomass C, and dissolved C and N throughout the incubation period. The study soil was volcanic immature soil from the southern part of Japan, which contains lower C and N compared with other Japanese forest soils. Despite this, the area is covered by well-developed natural and plantation forests. Carbon amendment resulted in an increase in both microbial biomass and respiration, and net N mineralization decreased, probably due to increasing microbial immobilization. In contrast, N amendment resulted in a decrease in microbial respiration and an increase in net N mineralization, possibly due to decreased immobilization by microbes. Amendment of both C and N simultaneously did not affect microbial biomass and respiration, although net N mineralization was slightly increased. The results suggested that inhibitory effect on microbial respiration by N amendment should be reduced if carbon availability is higher. Thus, soil available C may limit microbial biomass and respiration in this volcanic immature soil. Even in immature soil where C and N substrate is low, soil C, such as plant root exudates and materials from above- and belowground dead organisms, might help to maintain microbial activity and N mineralization in this study site.     

Simulating the Production of Rice Genotypes by Flood Management and End-Season Water Stress Conditions Using AquaCrop Model

ABSTRACT

The present study was conducted to assess the ability of AquaCrop model in predicting of grain and biological yield of rice genotypes in water management. A two-year field experiment was conducted at the experimental farm of the Iranian Rice Research Institute in Rasht, Iran from 2016 to 2017. The experiment was established in a split-plot design with two irrigation management (continuous submergence and end season water stress) as the main plot, fourth rice genotypes as the sub-plot and three replications. The goodness-of-fit between observed and simulated grain yield and final biomass was assessed by means of the coefficient of determination (R ²), the absolute and normalized root mean square errors (RMSE). The RMSE_n of predicting grain yield at calibration and evaluation stages was in the range of 6–12% and 6–8% for biological yield. The results indicated that AquaCrop model is suitable to predict grain yield and biological yield of rice genotypes in northern Iran. AquaCrop model can be used to determine optimization strategies to improve the water consumption of rice genotypes.     

Handling missingness when modeling the force of infection from clustered seroprevalence data

Modeling infectious diseases data is a relatively young research area in which clustering and stratification are key features. It is not unlikely for these data to have missing values. If values are missing completely at random, the analysis on the complete cases is valid. However, in practice this assumption is usually not fulfilled. This article shows the effect of ignoring missing data in modeling the force of infection of the bovine herpesvirus-1 in Belgian cattle and proposes the use of weighted generalized estimating equations with constrained fractional polynomials as a flexible modeling tool.     

Effects of Different Soil Treatments on the Development of <Emphasis Type="Italic">Spongospora subterranea</Emphasis> f. sp. <Emphasis Type="Italic">subterranea</Emphasis> in Potato Roots and Tubers in the Greenhouse

Powdery scab caused by Spongospora subterranea f. sp. subterranea (Sss) causes extensive losses in potato production systems globally. Two pot experiments were established in the greenhouse in summer 2013 and winter 2014 to evaluate the effectiveness of different soil chemicals, fumigant, amendments and biological control agents (BCAs) against Sss in the rhizospheric soil, potato roots and tubers. The study used visual assessment methods to assess the effect of treatments on root galling and zoosporangia production, and qPCR to measure Sss concentration in the soil and in the potato roots and tubers. All six soil treatments, namely metam sodium, fluazinam, ZincMax, calcium cyanamide, Biocult and a combination of Bacillus subtilis and Trichoderma asperellum recorded significantly (P < 0.05) lower numbers of zoosporangia in the roots compared to the untreated control. The same effect was observed on the concentration of Sss DNA in the roots at tuber initiation. A more diverse picture was obtained when root gall scores at tuber initiation and Sss DNA in the rhizospheric soil at tuber initiation and harvesting were compared. Significant differences (P < 0.05) were also noted in disease severity, disease incidence, and tuber yield between metam sodium, fluazinam, ZincMax, calcium cyanamide and the untreated control. Calcium cyanamide gave the highest tuber yield. The study demonstrated the potential of soil treatments such as metam sodium, fluazinam, ZincMax and calcium cyanamide in managing Sss in potatoes by reducing the pathogen both in the rhizospheric soil and the roots of the potato plant.