Climate-ready crops: Intellectual property, agriculture, and climate change

In The Climate Change Review, Ross Garnaut emphasised that ‘Climate change and climate change mitigation will bring about major structural change in the agriculture, forestry and other land use sectors’. He provides this overview of the effects of climate change on food demand and supply: ‘Domestic food production in many developing countries will be at immediate risk of reductions in agricultural productivity due to crop failure, livestock loss, severe weather events and new patterns of pests and diseases.’ He observes that ‘Changes to local climate and water availability will be key determinants of where agricultural production occurs and what is produced.’ Gert Würtenberger has commented that modern plant breeding is particularly concerned with addressing larger issues about nutrition, food security and climate change: ‘Modern plant breeding has an increasing importance with regard to the continuously growing demand for plants for nutritional and feeding purposes as well as with regard to renewal energy sources and the challenges caused by climate changes.’ Moreover, he notes that there is a wide array of scientific and technological means of breeding new plant varieties: ‘Apart from classical breeding, technologies have an important role in the development of plants that satisfy the various requirements that industrial and agricultural challenges expect to be fulfilled.’ He comments: ‘Plant variety rights, as well as patents which protect such results, are of increasingly high importance to the breeders and enterprises involved in plant development programmes.’ There has been larger interest in the intersections between sustainable agriculture, environmental protection and food security. The debate over agricultural intellectual property is a polarised one, particularly between plant breeders, agricultural biotechnology companies and a range of environmentalist groups. Susan Sell comments that there are complex intellectual property battles surrounding agriculture: 'Seeds are at the centre of a complex political dynamic between stakeholders. Access to seeds concerns the balance between private rights and public obligations, private ownership and the public domain, and commercial versus humanitarian objectives.' Part I of this chapter considers debates in respect of plant breeders’ rights, food security and climate change in relation to the UPOV Convention 1991. Part II explores efforts by agricultural biotechnology companies to patent climate-ready crops. Part III considers the report of the Special Rapporteur for Food, Olivier De Schutter. It looks at a variety of options to encourage access to plant varieties with climate adaptive or mitigating properties.

Plant species’ origin predicts dominance and response to nutrient enrichment and herbivores in global grasslands

Exotic species dominate many communities; however the functional significance of species’ biogeographic origin remains highly contentious. This debate is fuelled in part by the lack of globally replicated, systematic data assessing the relationship between species provenance, function and response to perturbations. We examined the abundance of native and exotic plant species at 64 grasslands in 13 countries, and at a subset of the sites we experimentally tested native and exotic species responses to two fundamental drivers of invasion, mineral nutrient supplies and vertebrate herbivory. Exotic species are six times more likely to dominate communities than native species. Furthermore, while experimental nutrient addition increases the cover and richness of exotic species, nutrients decrease native diversity and cover. Native and exotic species also differ in their response to vertebrate consumer exclusion. These results suggest that species origin has functional significance, and that eutrophication will lead to increased exotic dominance in grasslands.

Adoption of alternative habitats by a threatened, "obligate" forest-dwelling bat in a fragmented landscape

While they are among the most ecologically important animals within forest ecosystems, little is known about how bats respond to habitat loss and fragmentation. The threatened lesser short-tailed bat (Mystacina tuberculata), considered to be an obligate deep-forest species, is one of only 2 extant land mammals endemic to New Zealand; it plays a number of important roles within native forests, including pollination and seed dispersal, and rarely occurs in modified forests. We used radiotelemetry to study the movements, roosting behavior, and habitat use of M. tuberculata within a fragmented landscape comprised of 3 main habitat types: open space (harvested forest and pastoral land), native forests, and exotic pine plantations. We found that the bats had smaller home-range areas and travelled shorter nightly distances than populations investigated previously from contiguous native forest. Furthermore, M. tuberculata occupied all 3 habitat types, with native forest being preferred overall. However, individual variation in habitat selection was high, with some bats preferring exotic plantation and open space over native forest. Roosting patterns were similar to those previously observed in contiguous forest; individual bats often switched between communal and solitary roosts. Our findings indicate that M. tuberculata exhibit some degree of behavioral plasticity that allows them to adapt to different landscape mosaics and exploit alternative habitats. To our knowledge, this is the first such documentation of plasticity in habitat use for a bat species believed to be an obligate forest-dweller.

Nanolines on silicon surfaces

Although a wide range of periodic surface nets can be grown on low index silicon surfaces, only a few of these have quasi-one dimensional symmetry. If high index silicon surfaces, such as (553) and (557), are used instead, the surface unit cell contains steps. It is possible to fabricate a number of quasi-one dimensional nanoline systems on the terraces and some of these have nested energy bands near the Fermi level. These nano-scale systems may support exotic many-electron states produced by enhanced electron correlations and a reduction in electron screening in one spatial dimension. In this paper, our groups' experimental and theoretical studies of nanolines phases, grown on both low index and vicinal silicon surfaces are reviewed. These studies give us insight into the electronic properties of artificial nanoline structures.

Trapping to monitor tephritid movement: Results, best practice, and assessment of alternatives

Movement of tephritid flies underpins their survival, reproduction, and ability to establish in new areas and is thus of importance when designing effective management strategies. Much of the knowledge currently available on tephritid movement throughout landscapes comes from the use of direct or indirect methods that rely on the trapping of individuals. Here, we review published experimental designs and methods from mark-release-recapture (MRR) studies, as well as other methods, that have been used to estimate movement of the four major tephritid pest genera (Bactrocera, Ceratitis, Anastrepha, and Rhagoletis). In doing so, we aim to illustrate the theoretical and practical considerations needed to study tephritid movement. MRR studies make use of traps to directly estimate the distance that tephritid species can move within a generation and to evaluate the ecological and physiological factors that influence dispersal patterns. MRR studies, however, require careful planning to ensure that the results obtained are not biased by the methods employed, including marking methods, trap properties, trap spacing, and spatial extent of the trapping array. Despite these obstacles, MRR remains a powerful tool for determining tephritid movement, with data particularly required for understudied species that affect developing countries. To ensure that future MRR studies are successful, we suggest that site selection be carefully considered and sufficient resources be allocated to achieve optimal spacing and placement of traps in line with the stated aims of each study. An alternative to MRR is to make use of indirect methods for determining movement, or more correctly, gene flow, which have become widely available with the development of molecular tools. Key to these methods is the trapping and sequencing of a suitable number of individuals to represent the genetic diversity of the sampled population and investigate population structuring using nuclear genomic markers or non-recombinant mitochondrial DNA markers. Microsatellites are currently the preferred marker for detecting recent population displacement and provide genetic information that may be used in assignment tests for the direct determination of contemporary movement. Neither MRR nor molecular methods, however, are able to monitor fine-scale movements of individual flies. Recent developments in the miniaturization of electronics offer the tantalising possibility to track individual movements of insects using harmonic radar. Computer vision and radio frequency identification tags may also permit the tracking of fine-scale movements by tephritid flies by automated resampling, although these methods come with the same problems as traditional traps used in MRR studies. Although all methods described in this chapter have limitations, a better understanding of tephritid movement far outweighs the drawbacks of the individual methods because of the need for this information to manage tephritid populations.

The complexities of knowing what it is you are trapping

The effectiveness of any trapping system is highly dependent on the ability to accurately identify the specimens collected. For many fruit fly species, accurate identification (= diagnostics) using morphological or molecular techniques is relatively straightforward and poses few technical challenges. However, nearly all genera of pest tephritids also contain groups of species where single, stand-alone tools are not sufficient for accurate identification: such groups include the Bactrocera dorsalis complex, the Anastrepha fraterculus complex and the Ceratitis FAR complex. Misidentification of high-impact species from such groups can have dramatic consequences and negate the benefits of an otherwise effective trapping program. To help prevent such problems, this chapter defines what is meant by a species complex and describes in detail how the correct identification of species within a complex requires the use of an integrative taxonomic approach. Integrative taxonomy uses multiple, independent lines of evidence to delimit species boundaries, and the underpinnings of this approach from both the theoretical speciation literature and the systematics/taxonomy literature are described. The strength of the integrative approach lies in the explicit testing of hypotheses and the use of multiple, independent species delimitation tools. A case is made for a core set of species delimitation tools (pre- and post-zygotic compatibility tests, multi-locus phylogenetic analysis, chemoecological studies, and morphometric and geometric morphometric analyses) to be adopted as standards by tephritologists aiming to resolve economically important species complexes. In discussing the integrative approach, emphasis is placed on the subtle but important differences between integrative and iterative taxonomy. The chapter finishes with a case study that illustrates how iterative taxonomy applied to the B. dorsalis species complex led to incorrect taxonomic conclusions, which has had major implications for quarantine, trade, and horticultural pest management. In contrast, an integrative approach to the problem has resolved species limits in this taxonomically difficult group, meaning that robust diagnostics are now available.

A digital beehive could warn beekeepers when their hives are under attack

Honey bees are in decline, and the current method of keeping them can be disruptive to a colony. But new designs allow beekeepers to monitor a hive remotely, even sniff out disease and pests.

Quarantine and surveillance strategies for plant pathogen detection and control

Incursions of plant pests and diseases pose serious threats to food security, agricultural productivity and the natural environment. One of the challenges in confidently delimiting and eradicating incursions is how to choose from an arsenal of surveillance and quarantine approaches in order to best control multiple dispersal pathways. Anthropogenic spread (propagules carried on humans or transported on produce or equipment) can be controlled with quarantine measures, which in turn can vary in intensity. In contrast, environmental spread processes are more difficult to control, but often have a temporal signal (e.g. seasonality) which can introduce both challenges and opportunities for surveillance and control. This leads to complex decisions regarding when, where and how to search. Recent modelling investigations of surveillance performance have optimised the output of simulation models, and found that a risk-weighted randomised search can perform close to optimally. However, exactly how quarantine and surveillance strategies should change to reflect different dispersal modes remains largely unaddressed. Here we develop a spatial simulation model of a plant fungal-pathogen incursion into an agricultural region, and its subsequent surveillance and control. We include structural differences in dispersal via the interplay of biological, environmental and anthropogenic connectivity between host sites (farms). Our objective was to gain broad insights into the relative roles played by different spread modes in propagating an invasion, and how incorporating knowledge of these spread risks may improve approaches to quarantine restrictions and surveillance. We find that broad heuristic rules for quarantine restrictions fail to contain the pathogen due to residual connectivity between sites, but surveillance measures enable early detection and successfully lead to suppression of the pathogen in all farms. Alternative surveillance strategies attain similar levels of performance by incorporating environmental or anthropogenic dispersal risk in the prioritisation of sites. Our model provides the basis to develop essential insights into the effectiveness of different surveillance and quarantine decisions for fungal pathogen control. Parameterised for authentic settings it will aid our understanding of how the extent and resolution of interventions should suitably reflect the spatial structure of dispersal processes.

Natural variation and Biogeography of the melon fruit fly, Zeugodacus cucurbitae (Diptera : Tephritidae), in Southeast-Asia and the west-pacific

This thesis used multidisciplinary approaches which greatly enhance our understanding of population structure and can be particularly powerful tools for resolving variation of melon fly over geographic and temporal scales, and for determining invasive pathways. The results from this thesis reinforce the value of integrating multiple data sets to better understand and resolve natural variation within an important pest to determine whether there are cryptic species, discrete lineages or host races, and to identify dispersal pathways in an invasive pest. These results are instructive for regional biosecurity, trade and quarantine, and provide important background for future area-wide management programmes. The integrative methodology adopted in this thesis is applicable to a variety of other insect pests.

Molecular modeling of Bt Cry1Ac (DI–DII)–ASAL (Allium sativum lectin)–fusion protein and its interaction with aminopeptidase N (APN) receptor of Manduca sexta

Genetic engineering of Bacillus thuringiensis (Bt) Cry proteins has resulted in the synthesis of various novel toxin proteins with enhanced insecticidal activity and specificity towards different insect pests. In this study, a fusion protein consisting of the DI–DII domains of Cry1Ac and garlic lectin (ASAL) has been designed in silico by replacing the DIII domain of Cry1Ac with ASAL. The binding interface between the DI–DII domains of Cry1Ac and lectin has been identified using protein–protein docking studies. Free energy of binding calculations and interaction profiles between the Cry1Ac and lectin domains confirmed the stability of fusion protein. A total of 18 hydrogen bonds was observed in the DI–DII–lectin fusion protein compared to 11 hydrogen bonds in the Cry1Ac (DI–DII–DIII) protein. Molecular mechanics/Poisson–Boltzmann (generalized-Born) surface area [MM/PB (GB) SA] methods were used for predicting free energy of interactions of the fusion proteins. Protein–protein docking studies based on the number of hydrogen bonds, hydrophobic interactions, aromatic–aromatic, aromatic–sulphur, cation–pi interactions and binding energy of Cry1Ac/fusion proteins with the aminopeptidase N (APN) of Manduca sexta rationalised the higher binding affinity of the fusion protein with the APN receptor compared to that of the Cry1Ac–APN complex, as predicted by ZDOCK, Rosetta and ClusPro analysis. The molecular binding interface between the fusion protein and the APN receptor is well packed, analogously to that of the Cry1Ac–APN complex. These findings offer scope for the design and development of customized fusion molecules for improved pest management in crop plants.

Using Bayesian networks to model surveillance in complex plant and animal health systems

In this chapter we consider biosecurity surveillance as part of a complex system comprising many different biological, environmental and human factors and their interactions. Modelling and analysis of surveillance strategies should take into account these complexities, and also facilitate the use and integration of the many types of different information that can provide insight into the system as a whole. After a brief discussion of a range of options, we focus on Bayesian networks for representing such complex systems. We summarize the features of Bayesian networks and describe these in the context of surveillance.

Generalized self-assembly of scalable two-dimensional transition metal oxide nanosheets

Two-dimensional (2D) transition metal oxide systems present exotic electronic properties and high specific surface areas, and also demonstrate promising applications ranging from electronics to energy storage. Yet, in contrast to other types of nanostructures, the question as to whether we could assemble 2D nanomaterials with an atomic thickness from molecules in a general way, which may give them some interesting properties such as those of graphene, still remains unresolved. Herein, we report a generalized and fundamental approach to molecular self-assembly synthesis of ultrathin 2D nanosheets of transition metal oxides by rationally employing lamellar reverse micelles. It is worth emphasizing that the synthesized crystallized ultrathin transition metal oxide nanosheets possess confined thickness, high specific surface area and chemically reactive facets, so that they could have promising applications in nanostructured electronics, photonics, sensors, and energy conversion and storage devices.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.