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.

     

Follicular Dynamics in Heifers during Pre-pubertal and Pubertal Period Kept under Two Levels of Dietary Energy Intake

The objective of this study was to characterize follicular dynamics in pre-pubertal, pubertal and post-pubertal periods, as well as the effect of high-energy intake on follicular development and age at puberty in heifers. Thirty-one Nelore (Bos indicus) heifers, 6 months old, were randomly assigned to receive two different diets: one of low (GI) and other of high dietary energy intake (GII). Animals were evaluated in relation to body weight gain by being weighed every 21 days. Heifers were evaluated every other day by real-time linear ultrasonography to characterize ovarian structures development from weaning to post-pubertal period. Blood samples were collected to determine plasmatic concentrations of progesterone by RIA method. The ovulation was determined when progesterone concentrations were >1 ng/mL in three consecutive samples, and by ultrasound images of corpus luteum; and oestrous behaviour in some animals. Age at puberty differed among heifers of GII (17.00 +/- 0.46 months) compared with heifers of GI (19.87 +/- 0.47 months; p < or = 0.05). Maximum size of the dominant follicles at pre-pubertal period was greater in GII heifers than in GI (10.52 +/- 0.33 and 9.76 +/- 0.15 mm, respectively; p < or = 0.05). As heifers approached first ovulation time, size of dominant follicle increased (11.75 +/- 0.37 mm for GI and 12.52 +/- 0.91 mm for GII; p < or = 0.05). Body weight at puberty was not different in both groups (302.33 +/- 27.31 kg for GI and 326.19 +/- 27.78 kg for GII heifers; p > 0.05). We conclude that animals receiving high dietary energy intake attained the puberty earlier and the development of follicles were different than in low dietary energy intake.     

Prevalence of antibodies to equine viruses in the Netherlands

Summary The prevalence of antibodies to various viruses was investigated in a series of serum samples collected from horses in the Netherlands between 1963 and 1966 and from 1972 onwards. Neutralizing antibodies to equine rhinopneumonitis virus, equine arteritis virus and to equine rhinovirus types 1 and 2 were detected in respectively 76%, 14%, 66% and 59% of the equine serum samples tested. The observed incidence of serum samples positive to equine adenovirus in the complement fixation test was 39%. Precipitating antibodies to equine infectious anaemia virus were detected only in serum samples from two horses imported from abroad. Haemagglutination inhibiting antibodies to Myxovirus influenzae A / equi-1, M. Influenzae A / equi-2, and Reovirus types 1, 2, and 3 were present in respectively 82%, 50%, 10%, 33% and 3.6% of the serum samples tested. The most frequently observed incidence of antibodies to the various equine respiratory viruses occurred in the groups of horses having repeatedly contact with other horses.     

“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.     

Yield map generation of perennial crops for fresh consumption

Yield mapping technologies can help to increase the quantity and quality of agricultural production. Current systems only focus on the quantification of the harvest, but the quality has equal or greater importance in some perennial crops and impacts directly on the financial profitability. Therefore, a system was developed to quantify and relate the quality obtained in the classification line with the plants of the orchard and for decision-making. The system is comprised of hardware, which obtains the location of the harvester bag during harvesting and unloading at the unloading site, and software that processes the collected data. The cloud of real-time data contributed from the different collectors (bins) allows the construction of yield maps, considering the multi-stage harvesting system. Further, the system enables the creation of a detailed map of the plants and fruits harvested. As the harvest focuses on quality, it takes place in stages, depending on the ripening of the fruits. In addition to the yield maps, the system allows identification of the efficiency of each worker undertaking the harvest by the number of performed discharges and by the time spent. The system was developed in partnership with the Federal Technological University of Paraná and Embrapa Uva & Vinho and was tested in apple orchards in southern Brazil. Although the system was evaluated with only data from apple cultivation, monitoring the quality and quantifying other orchard fruits can positively impact the fruit sector.