Ecoinformatics Can Reveal Yield Gaps Associated with Crop-Pest Interactions: A Proof-of-Concept

Farmers and private consultants execute a vast, decentralized data collection effort with each cropping cycle, as they gather pest density data to make real-time pest management decisions. Here we present a proof of concept for an ecoinformatics approach to pest management research, which attempts to harness these data to answer questions about pest-crop interactions. The impact of herbivory by Lygus hesperus on cotton is explored as a case study. Consultant-derived data satisfied a ‘positive control’ test for data quality by clearly resolving the expected negative relationship between L. hesperus density and retention of flower buds. The enhanced statistical power afforded by the large ecoinformatics dataset revealed an early-season window of crop sensitivity, during which L. hesperus densities as low as 1-2 per sample were associated with yield loss. In contrast, during the mid-season insecticide use by farmers was often unnecessary, as cotton compensated fully for moderate L. hesperus densities. Because the dataset emerged from the commercial production setting, it also revealed the limited degree to which farmers were willing to delay crop harvest to provide opportunities for compensatory fruiting. Observational approaches to pest management research have strengths and weaknesses that complement those of traditional, experimental approaches; combining these methods can contribute to enhanced agricultural productivity.     

Database design for ecologists: Composing core entities with observations

The ecoinformatics community recognizes that ecological synthesis across studies, space, and time will require new informatics tools and infrastructure. Recent advances have been encouraging, but many problems still face ecologists who manage their own datasets, prepare data for archiving, and search data stores for synthetic research. In this paper, we describe how work by the Canopy Database Project (CDP) might enable use of database technology by field ecologists: increasing the quality of database design, improving data validation, and providing structural and semantic metadata — all of which might improve the quality of data archives and thereby help drive ecological synthesis.The CDP has experimented with conceptual components for database design, templates, to address information technology issues facing ecologists. Templates represent forest structures and observational measurements on these structures. Using our software, researchers select templates to represent their study’s data and can generate normalized relational databases. Information hidden in those databases is used by ancillary tools, including data intake forms and simple data validation, data visualization, and metadata export. The primary question we address in this paper is, which templates are the right templates.We argue for defining simple templates (with relatively few attributes) that describe the domain's major entities, and for coupling those with focused and flexible observation templates. We present a conceptual model for the observation data type, and show how we have implemented the model as an observation entity in the DataBank database designer and generator. We show how our visualization tool CanopyView exploits metadata made explicit by DataBank to help scientists with analysis and synthesis. We conclude by presenting future plans for tools to conduct statistical calculations common to forest ecology and to enhance data mining with DataBank databases.DataBank could be extended to another domain by replacing our forest–ecology-specific templates with those for the new domain. This work extends the basic computer science idea of abstract data types and user-defined types to ecology-specific database design tools for individual users, and applies to ecoinformatics the software engineering innovations of domain-specific languages, software patterns, components, refactoring, and end-user programming.     

Optimizing spatial positioning of traps in the context of integrated pest management

Agricultural research often relies on methods and approaches to represent and explain complex agro-ecosystems processes. In the context of biological control, auto dissemination strategies have been widely embraced for the management of various pests. One such strategy is using traps that attract arthropods into the hub of fungal based entomopathogens. The trapped pests are infected with the entomopathogen, which can then disseminate it among its conspecifics after being released. Despite the potential of the technique, its adoption especially by smallholder farmers has been limited, most likely due to the lack of an efficient trap positioning strategy. In this study, we propose an approach to improve the field application of fungal-based bio-pesticides (entomopathogenic fungi or EPF) by optimizing the spatial distribution of traps. The optimal field distribution of traps can be determined based on the following steps: (i) a field experiment to assess the dispersal ability of the pest infected by an entomopathogenic fungi (EPF) and (ii) the model-based estimation of the optimum traps density and distribution per unit of space (ha, km²). Based on experimental data we applied nonlinear regression and spatial optimization processes to calculate the radius covered by one trap and to estimate the optimum number and spatial positioning of the traps. We applied the method to a case study using the fungal isolate ICIPE 62 to control the invasive fruit fly Bactrocera dorsalis. The research revealed that nine pheromone traps per ha are required with a spacing distance of 37.45 m between the traps. The proposed approach can also be applied to other pest species, to help farmers reduce the number of traps used on a farm and to assist researchers and policymakers to optimize auto dissemination strategies in the context of integrated pest management (IPM).     

Current developments and future directions of bio-inspired computation and implications for ecoinformatics

Evolutionary and neural computation has been used widely in solving various problems in biological ecosystems. This paper reviews some of the recent work in evolutionary computation and neural network ensembles that could be explored further in the context of ecoinformatics. Although these bio-inspired techniques were not developed specifically for ecoinformatics, their successes in solving complex problems in other fields demonstrate how these techniques could be adapted and used for tackling difficult problems in ecoinformatics. Firstly, we will review our work in modelling and model calibration, which is an important topic in ecoinformatics. Secondly one example will be given to illustrate how coevolutionary algorithms could be used in problem-solving. Thirdly, we will describe our work on neural network ensembles, which can be used for various classification and prediction problems in ecoinformatics. Finally, we will discuss ecosystem-inspired computational models and algorithms that could be explored as directions of future research.     

Exploiting predators for pest management: the need for sound ecological assessment

Most people agree that arthropod natural enemies are good for insect pest management in agriculture. However, the population suppressive effects of predators, which consume their prey and often leave no direct evidence of their activity, are more difficult to study than the effects of parasitoids, which can be sampled from host populations relatively easily. We critically reviewed field studies which investigated the relationship between lepidopteran pests and their associated predatory fauna, published in 11 leading entomology and applied ecology journals between 2003 and 2008. Each study was appraised to determine whether or not it demonstrated that predators had an impact on prey (pest) populations and, if so, whether it was conducted at an ecological scale relevant to pest management. Less than half (43%) of the 54 field studies adopted methodologies that allowed the impact of predators on target pest populations to be measured. Furthermore, 76% of the studies were conducted at the scale of experimental plots rather than at the ecological scale which determines pest and predator population dynamics or at which pest‐management decisions are made. In almost one‐third of the studies, predator abundance and/or diversity was measured, but this metric was not linked with pest suppression or mortality. We conclude that much current research does not provide evidence that predatory arthropods suppress target lepidopteran pest populations and, consequently, that it has little relevance to pest management. Well‐designed ecological experiments combined with recent advances in molecular techniques to identify predator diets and the emergence of organic agriculture provide both the mechanisms and a platform upon which many predator–prey interactions can be investigated at a scale relevant to pest management. However, benefits will only be reaped from this opportunity if current approaches to research are changed and relevant ecological data are collected at appropriate ecological scales.     

Ecoinformatics: supporting ecology as a data-intensive science

Ecology is evolving rapidly and increasingly changing into a more open, accountable, interdisciplinary, collaborative and data-intensive science. Discovering, integrating and analyzing massive amounts of heterogeneous data are central to ecology as researchers address complex questions at scales from the gene to the biosphere. Ecoinformatics offers tools and approaches for managing ecological data and transforming the data into information and knowledge. Here, we review the state-of-the-art and recent advances in ecoinformatics that can benefit ecologists and environmental scientists as they tackle increasingly challenging questions that require voluminous amounts of data across disciplines and scales of space and time. We also highlight the challenges and opportunities that remain.     

Assessing the impact of arthropod natural enemies on crop pests at the field scale

There are many reasons why it is important that we find ways to conserve, and better utilize natural enemies of invertebrate crop pests. Currently, measures of natural enemy impact are rarely incorporated into studies that purport to examine pest control. Most studies examine pest and natural enemy presence and/or abundance and then qualitatively infer impact. While this provides useful data to address a range of ecological questions, a measure of impact is critical for guiding pest management decision‐making. Often some very simple techniques can be used to obtain an estimate of natural enemy impact. We present examples of field‐based studies that have used cages, barriers to restrict natural enemy or prey movement, direct observation of natural enemy attack, and sentinel prey items to estimate mortality. The measure of natural enemy impact used in each study needs to be tailored to the needs of farmers and the specific pest problems they face. For example, the magnitude of mortality attributed to natural enemies may be less important than the timing and consistency of that mortality between seasons. Tailoring impact assessments will lead to research outcomes that do not simply provide general information about how to conserve natural enemies, but how to use these natural enemies as an integral part of decision‐making.     

Role of modelling in improving nutrient efficiency in cropping systems

The applicability of models in addressing resource management issues in agriculture has been widely promoted by the research community, yet examples of real impacts of such modelling efforts on current farming practices are rare. Nevertheless, simulation models can compliment traditional field experimentation in researching alternative management options. The first objective of this paper is, therefore, to provide four case study examples of where models were used to help research issues relating to improved nutrient efficiency in low-input cropping systems. The first two cases addressed strategies of augmenting traditional farming practices with small applications of chemical fertilizer (N and P). The latter two cases explicitly addressed the question of what plant genetic traits can be beneficial in low-nutrient farming systems. In each of these case studies, the APSIM (Agricultural Production Systems Simulator) systems model was used to simulate the impacts of alternative crop management systems.The question of whether simulation models can assist the research community in contributing to purposeful change in farming practice is also addressed. Recent experiences in Australia are reported where simulation models have contributed to practice change by farmers. Finally, current initiatives aimed at testing whether models can also contribute to improving the nutrient efficiency of smallholder farmers in the SAT are discussed.     

Quantitatively Evaluating Restoration Experiments: Research Design, Statistical Analysis, and Data Management Considerations

Conceptual and logistical challenges associated with the design and analysis of ecological restoration experiments are often viewed as being insurmountable, thereby limiting the potential value of restoration experiments as tests of ecological theory. Such research constraints are, however, not unique within the environmental sciences. Numerous natural and anthropogenic disturbances represent unplanned, uncontrollable events that cannot be replicated or studied using traditional experimental approaches and statistical analyses. A broad mix of appropriate research approaches (e.g., long-term studies, large-scale comparative studies, space-for-time substitution, modeling, and focused experimentation) and analytical tools (e.g., observational, spatial, and temporal statistics) are available and required to advance restoration ecology as a scientific discipline. In this article, research design and analytical options are described and assessed in relation to their applicability to restoration ecology. Significant research benefits may be derived from explicitly defining conceptual models and presuppositions, developing multiple working hypotheses, and developing and archiving high-quality data and metadata. Flexibility in research approaches and statistical analyses, high-quality databases, and new sampling approaches that support research at broader spatial and temporal scales are critical for enhancing ecological understanding and supporting further development of restoration ecology as a scientific discipline.     

农业组织与有害生物风险管理研究综述

随着全球气候变暖、农药滥用、外来有害生物入侵等因素,我国农业病虫害逐年呈快速增长之势。而以广大农户家庭、合作组织、农业企业为单元的社会灾害管理系统是生物灾害管理体系中重要的组成部分,但却存在着规模分散、管理混乱等问题。有害生物是公共品,具有外部性的特征,而我国分散化的管理组织形式,不利于对有害生物的统一治理。现阶段我国关于农业组织化对有害生物防控影响的文献较少,为此,通过分别梳理农业组织风险管理和有害生物风险管理的研究进展,探讨不同农业组织风险管理、有害生物风险管理、有害生物造成的经济损失以及有害生物综合治理的方法与模式。在未来的研究中,应进一步加强不同农业组织对有害生物防控效果、有害生物造成经济损失的影响因素、不同农业组织对有害生物"统防统治"参与行为的研究,通过农业组织化防控治理体系的改革,提升有害生物的防控效率,以更好的为政府相关部门决策提供必要的参考依据。     

Bridging factorial and gradient concepts of resource co‐limitation: towards a general framework applied to consumers

Organism growth can be limited either by a single resource or by multiple resources simultaneously (co‐limitation). Efforts to characterise co‐limitation have generated two influential approaches. One approach uses limitation scenarios of factorial growth assays to distinguish specific types of co‐limitation; the other uses growth responses spanned over a continuous, multi‐dimensional resource space to characterise different types of response surfaces. Both approaches have been useful in investigating particular aspects of co‐limitation, but a synthesis is needed to stimulate development of this recent research area. We address this gap by integrating the two approaches, thereby presenting a more general framework of co‐limitation. We found that various factorial (co‐)limitation scenarios can emerge in different response surface types based on continuous availabilities of essential or substitutable resources. We tested our conceptual co‐limitation framework on data sets of published and unpublished studies examining the limitation of two herbivorous consumers in a two‐dimensional resource space. The experimental data corroborate the predictions, suggesting a general applicability of our co‐limitation framework to generalist consumers and potentially also to other organisms. The presented framework might give insight into mechanisms that underlie co‐limitation responses and thus can be a seminal starting point for evaluating co‐limitation patterns in experiments and nature.     

Why we need observational studies to evaluate the effectiveness of health care.

The view is widely held that experimental methods (randomised controlled trials) are the "gold standard" for evaluation and that observational methods (cohort and case control studies) have little or no value. This ignores the limitations of randomised trials, which may prove unnecessary, inappropriate, impossible, or inadequate. Many of the problems of conducting randomised trials could often, in theory, be overcome, but the practical implications for researchers and funding bodies mean that this is often not possible. The false conflict between those who advocate randomised trials in all situations and those who believe observational data provide sufficient evidence needs to be replaced with mutual recognition of the complementary roles of the two approaches. Researchers should be united in their quest for scientific rigour in evaluation, regardless of the method used.     

Experimental field exclosure of birds and bats in agricultural systems — Methodological insights,potential improvements,and cost-benefit trade-offs

Experimental exclosure of birds and bats constitutes a powerful tool to study the impacts of wildlife on pests and crop yields in agricultural systems. Though widely utilized, exclosure experiments are not standardized across studies. Indeed, key differences surrounding the design, materials, and protocols for implementing field-based exclosure experiments of flying vertebrates increase heterogeneity across studies, and limit our understanding of biodiversity-friendly land use management. We reviewed the available literature on studies in which bird and bat exclosures were applied to study pest control in agricultural settings, and isolated 30 studies from both tropical and temperate land use systems, involving 12 crop types across 14 countries. Focusing on exclosure effects on crop yield, we analyzed effect detectability for a subset of suitable data. We then analyzed the potential of exclosure methods and possible extensions to improve our understanding of complex food webs and ecosystem services affecting the productivity of agricultural systems. While preferences exist in materials (e.g., nylon nets and bamboo frames), experimental exclosure studies of birds and bats differed greatly in their respective design, related costs, and effort — limiting the generalization and transferability of results at larger spatial scales. Most studies were based on experiments conducted in the United States and the Neotropics, mainly in coffee and cacao farms. A lack of preliminary or long-term data with repeated measurements makes it impossible to apply power analysis in most studies. Common constraints include, among other things, the choice of material and experimental duration, as well as the consideration of local versus landscape factors. We discuss such limitations, related common pitfalls, and options for optimization to inform improved planning, design, and execution of exclosure studies. By doing so, we aim to promote more comparable and transferable approaches in future field research on biodiversity-mediated ecosystem services.     

Farmers' perceptions, knowledge, and management of coffee pests and diseases and their natural enemies in Chiapas, Mexico

Small farmers' perceptions of coffee Coffea arabica L. herbivores and their natural enemies, how those perceptions relate to field infestation levels, and pest management practices being implemented by members from two organic and nonorganic coffee grower organizations in the Soconusco region, southeastern Mexico, were analyzed through an interview survey, diagnostic workshops, and field sampling. The terms pest, disease, and damage were commonly used as synonyms. The major phytophagous species, as perceived by the interviewees, were Hypothenemus hampei (Ferrari), and to a lesser extent the fungi Corticium koleroga Cooke (H?hnel) and Hemileia vastatrix Berkeley & Broome. Among the nonorganic farmers, other nonpest-related constraints were regarded as more important. Awareness of the existence of natural enemies was low, despite more organic farmers have used the ectoparasitoid bethylid Cephalonomia stephanoderis Betrem against H. hampei. Labor supplied by household members was most frequent for pest control; only organic farmers exchanged labor for this purpose. The levels of infestation by H. hampei, Leucoptera coffeella Guérin-Méneville, and C. koleroga were lower within the organic coffee stands. However, a low effectiveness for pest control was commonly perceived, probably due to a feeling, among the organic farmers, of a low impact of their pest management extension service, whereas a lack of motivation was prevalent among the nonorganic farmers, shown by a concern with their low coffee yields and the emigration of youth. The importance of understanding farmers' perceptions and knowledge of pests and their natural enemies and the need for participatory pest management approaches, are discussed.     

昆虫的RNA干扰

RNA干扰(RNAi)是一种强有力的分子生物学技术, 在昆虫研究中得到了较多的应用。目前, RNAi技术主要应用于昆虫功能基因和功能基因组研究, 已在多个目的19种昆虫上实现了RNAi。在昆虫上实现RNAi的方法主要有注射、浸泡、喂食、转基因和病毒介导等方法, 这些方法各有特点, 其中喂食法因其简单而最有应用前景。昆虫RNAi的系统性较为复杂, 只有部分昆虫具有RNAi的系统性。昆虫中RNAi信号传导的基因可能是sid-1, 但昆虫RNAi的系统性机理还不是很清楚。转基因植物产生的dsRNA实现了对作物的保护, 证实了RNAi技术可用于害虫控制, 为害虫控制开辟了新领域。昆虫的RNAi研究处在起步阶段, 研究昆虫RNAi的机理, 特别是RNAi在昆虫体内的系统性扩散机理, 改进实现RNAi的方法, 提高RNAi技术在昆虫研究中的应用, 有利于昆虫基因功能鉴定和害虫控制, 促进昆虫学科的发展。     

Coupled information diffusion--pest dynamics models predict delayed benefits of farmer cooperation in pest management programs

Worldwide, the theory and practice of agricultural extension system have been dominated for almost half a century by Rogers' "diffusion of innovation theory". In particular, the success of integrated pest management (IPM) extension programs depends on the effectiveness of IPM information diffusion from trained farmers to other farmers, an important assumption which underpins funding from development organizations. Here we developed an innovative approach through an agent-based model (ABM) combining social (diffusion theory) and biological (pest population dynamics) models to study the role of cooperation among small-scale farmers to share IPM information for controlling an invasive pest. The model was implemented with field data, including learning processes and control efficiency, from large scale surveys in the Ecuadorian Andes. Our results predict that although cooperation had short-term costs for individual farmers, it paid in the long run as it decreased pest infestation at the community scale. However, the slow learning process placed restrictions on the knowledge that could be generated within farmer communities over time, giving rise to natural lags in IPM diffusion and applications. We further showed that if individuals learn from others about the benefits of early prevention of new pests, then educational effort may have a sustainable long-run impact. Consistent with models of information diffusion theory, our results demonstrate how an integrated approach combining ecological and social systems would help better predict the success of IPM programs. This approach has potential beyond pest management as it could be applied to any resource management program seeking to spread innovations across populations.     

Insect pest management in African agriculture: Challenges in the current millenium

Pest management on a global scale experienced a total revolution after World War II when synthetic organic compounds were in agriculture and public health. However, it soon became apparent that there were many limitations in the use of chemicals for pest management. In agriculture, problems of pest resurgence, secondary pest outbreaks, pest resistance and adverse effects of pesticides on the environment, including human poisoning and toxicity to other non-target organisms, led to the search for alternative approaches to the pest outbreak problem. The 1960s produced new ideas on integrated pest management (IPM) strategies, followed by intensification of the search for biological control agents, which could be incorporated into IPM programmes. New application technologies were developed in the 1970s and 1980s and ecological approaches to the pest problem were spearheaded in the developed world in the 1990s, with extensive studies focused on the whole ecosystem. Important advances in crop production have also taken place in Africa in this century, involving adoption of high yielding varieties, fertilizer application, intensification of crop protection approaches, less shifting cultivation and more mono-cropping systems. However, these advances have led to increasing pest problems which unless tackled imaginatively and intelligently, they could become the most important constraint in crop production in the present millennium. Africa has entered the current millennium with relatively underdeveloped agriculture on a global scale and little investment in research on new pest management technologies that could be used to reduce crop losses. We are still highly dependent on pesticides for pest management. Therefore, the greatest challenges in agriculture in Africa will be the switch from a pesticide based mode of reducing losses due to pests to one that is ecosystem based, making use of insect management techniques which are ecologically and economically sound. Specifically, some of the major challenges in pest management in agriculture in Africa include; (i) reducing the dependence on pesticides, thus avoiding the limitations observed in the past 50 years; (ii) overcoming ignorance of the pest species and their associated community of parasites and predators which has dire consequences on the whole ecosystem; (iii) keeping out exotic pests, which in this millennium have had a devastating blow on the production of some crops and (iv) developing indigenous technologies for pest management (IPM, biocontrol, etc.) and making available to farmers materials for pest management which are affordable, safe, effective and environmentally friendly (e.g. microbial, botanicals, pheromones, genetically engineered products etc.). Both legislative and quarantine measures will have a significant role to play in pest management in the next millennium, but only when practised on a wider geographical area. Information technology (IT) will affect the way we acquire and make use of pest management strategies. Africa is therefore faced with the challenge of building up and improving its infrastructure and expertise on IT if it is to benefit pest management on the continent.     

Plant–pollinator interactions and phenological change: what can we learn about climate impacts from experiments and observations?

Climate change can affect plant–pollinator interactions in a variety of ways, but much of the research attention has focused on whether independent shifts in phenology will alter temporal overlap between plants and pollinators. Here I review the research on plant–pollinator mismatch, assessing the potential for observational and experimental approaches to address particular aspects of the problem. Recent, primarily observational studies suggest that phenologies of co‐occurring plants and pollinators tend to respond similarly to environmental cues, but that nevertheless, certain pairs of interacting species are showing independent shifts in phenology. Only in a few cases, however, have these independent shifts been shown to affect population vital rates (specifically, seed production by plants) but this largely reflects a lack of research. Compared to the few long‐term studies of pollination in natural plant populations, experimental manipulations of phenology have yielded relatively optimistic conclusions about effects of phenological shifts on plant reproduction, and I discuss how issues of scale and frequency‐dependence in pollinator behaviour affect the interpretation of these ‘temporal transplant’ experiments. Comparable research on the impacts of mismatch on pollinator populations is so far lacking, but both observational studies and focused experiments have the potential to improve our forecasts of pollinator responses to changing phenologies. Finally, while there is now evidence that plant–pollinator mismatch can affect seed production by plants, it is still unclear whether this phenological impact will be the primary way in which climate change affects plant–pollinator interactions. It would be useful to test the direct effects of changing climate on pollinator population persistence, and to compare the importance of phenological mismatch with other threats to pollination.