Measuring pollen deposition onto stigmas by insects is one technique used to assess pollinator effectiveness, but it can be unpredictable and time-consuming as insects must visit test flowers. This study examined whether a measurement of pollen grains from flower-visiting insects could be used to predict pollen deposited on stigmas. Individuals were collected from four bee and six fly species as they visited pak choi flowers in commercial and trial seed fields to assess their body pollen. Pollen was removed from insects by pressing their bodies (excluding actively-collected pollen on bees' hind legs) with a cube of gelatine-fuchsin. In this study, there appears to be a strong correlation between mean estimated pollen counts for each insect species and previously published data recording mean number of pollen grains deposited on stigmas for the same species. Therefore, the measurement of pollen grains directly from flower-visiting insects shows potential as a quicker and easier technique to assess pollinator effectiveness as insects can be directly collected from flowers.

1. Recent declines in honeybee populations have focused attention on the potential for unmanaged insects to replace them as pollinators of food crops. The capacity of unmanaged pollinators to replace services currently provided by honeybees depends on the spatial and temporal variability of these services, but few quantitative assessments currently exist. 2. We investigated spatial variation in pollinator importance by comparing pollinator efficiency and effectiveness in stigmatic pollen loads, stigmatic contact and visitation rate between honeybees and the seven most abundant unmanaged taxa in 2007. We assessed temporal variability in pollinator visitation using floral visits recorded three times a day over four consecutive years (2005-2008) in 43 'Pak Choi' Brassica rapa ssp. chinensis mass flowering fields in the Canterbury region of New Zealand. Further, we compared the aggregate effect of the unmanaged pollinator assemblage to the managed honeybee. 3. Pak Choi was visited by many insect species that vary in abundance and effectiveness as pollen transfer agents. There was spatial variation in the four measures of pollinator importance. Pollen deposited on stigmas and flower visits per minute were not significantly different comparing the unmanaged assemblage to honeybees, although stigmatic contact and visitor abundance per number of open flowers were greater in honeybees. 4. Unmanaged taxa were frequent visitors to the crop in all 4 years. The pooled services provided by the unmanaged assemblage did not differ within a day and were equal to or greater than those provided by honeybees in 2 of the 4 years. Pollinator importance changed little irrespective of the spatial and temporal variations among taxa. 5. Synthesis and applications. The results of this study suggest that some unmanaged insect taxa are capable of providing consistent pollination services over a 4-year period in a commercial mass flowering crop. As these taxa already contribute substantially to the pollination of food crops, they offer a safety net in the case of sudden collapse of managed honeybee hives. To optimize pollination services, we recommend pollinator-specific farm management practices that consider the needs of both managed and unmanaged pollinator taxa.

Ecological interactions between crops and wild animals frequently result in increases or declines in crop yield. Yet, positive and negative interactions have mostly been treated independently, owing partly to disciplinary silos in ecological and agricultural sciences. We advocate a new integrated research paradigm that explicitly recognizes cost-benefit trade-offs among animal activities and acknowledges that these activities occur within social-ecological contexts. Support for this paradigm is presented in an evidence-based conceptual model structured around five evidence statements highlighting emerging trends applicable to sustainable agriculture. The full range of benefits and costs associated with animal activities in agroecosystems cannot be quantified by focusing on single species groups, crops, or systems. Management of productive agroecosystems should sustain cycles of ecological interactions between crops and wild animals, not isolate these cycles from the system. Advancing this paradigm will therefore require integrated studies that determine net returns of animal activity in agroecosystems.

Ensuring the sustainability of crop production, whilst simultaneously taking actions to mitigate the environmental impacts of agriculture, is a current global priority. Given around 75% of global food crop yields benefit from pollination services provided by diverse wild and managed insect taxa, management strategies that support diverse communities of pollinator taxa are valuable to ensure ongoing pollination service provisioning and agricultural production. In addition to pollination, realised crop yields are also influenced by other biotic and abiotic factors which vary across different spatial and temporal scales. This thesis addresses three important aspects of crop pollination, namely the need to merge disparate research fields, the degree to which pollinator taxa service multiple crops and regions and how pollination interacts with crop tree physiological factors such as tree vigour.
First, I reviewed the literature to evaluate the knowledge gaps concerning pollinator effectiveness and the utility of using remote sensing in crop pollination research. I conducted surveys and pollen deposition trials to identify pollinators in avocado, mango and macadamia crops in three geographically distinct growing regions in Australia across three years. Using single visit deposition rates, bipartite networks and spatial analyses I also investigated pollinator service provisioning and the land use types that influence pollinator communities in these crop and regions. Using hand pollination trials over two years I investigated the impact of supplemental cross pollination on the yield of avocado trees.
My first review identified important research directions to account for pollination processes occurring at a community level including: plant-pollinator interactions, heterospecific pollen transfer and variation in pollination outcomes. My second review identified the areas in which remote sensing technologies can facilitate our understanding of interactions between pollinators, pollination services, environmental and plant physiological factors which affect final harvest measures.
Using multi-crop, multi-year and multi-region crop-pollinator networks I demonstrated that shared wild pollinator taxa visit multiple crops across several regions. In particular, honey bees (A. mellifera) and two families of wild visitors, Syrphidae and Calliphoridae, are present across all regions and crops. Further, regional comparisons for both avocado and mango crops identified additional shared families that were locally abundant such as Coccinellidae and native Apidae.
I found that the effect of additional cross pollination on trees of different vigour varied between individual orchard blocks and across years. General patterns relating to the impact of interaction between tree vigour and pollination on yield were discernible in this study, with lower and medium vigour trees responding more positively to supplemental pollination than high vigour trees. High variability in results and differences in effect response across orchard blocks highlight the need to investigate further factors at a tree and block scale, in future analyses.
My research indicates that there is significant potential to identify shared pollinators that provide services across multiple crops. Pollination management strategies that are regionally specific and that include bee and non-bee taxa and co-flowering crop species are needed to ensure ongoing effective and resilient pollination services are delivered to crop systems. The merging of different research fields, such as remote sensing, pollinator ecology and precision agriculture offers exciting new approaches to facilitate our understanding of these complex crop-pollinator interactions.

Habitat connectivity is vital for species population persistence but habitat loss and fragmentation is driving species decline across the globe. In order to respond to this challenge, conservation planners need ecologically relevant information to enable restoration of habitat and connectivity. The aim of this research was to use metapopulation theory and landscape ecology to provide biologically relevant guidance on how to improve landscape connectivity in a fragmented agricultural landscape, through an on-ground revegetation programme. In realising this aim, recently developed but not yet widely utilised methodologies were applied to a real-world conservation investment programme. These methodologies integrated concepts from metapopulation theory and landscape ecology to assess landscapes for their capacity to sustain viable metapopulations of a species of interest. A theoretical advance arising from this research was to develop the dispersal linkages as a stand-alone modelling component, hitherto a feature retained within the metapopulation model. New frameworks and syntheses of methodologies were developed in response to specific investment agency requirements but will have general application elsewhere. The study was conducted in the Border Rivers – Gwydir catchment in northern New South Wales, eastern Australia, as part of the Brigalow–Nandewar Biolinks revegetation project. The regional economy of the study region is based around agriculture (grazing and dryland and irrigated cropping), and native vegetation has been extensively cleared and modified for this purpose, resulting in relictual, fragmented and variegated landscapes.

How many dimensions (trait-axes) are required to predict whether two species interact? This unanswered question originated with the idea of ecological niches, and yet bears relevance today for understanding what determines network structure. Here, we analyse a set of 200 ecological networks, including food webs, antagonistic and mutualistic networks, and find that the number of dimensions needed to completely explain all interactions is small ( < 10), with model selection favouring less than five. Using 18 high-quality webs including several species traits, we identify which traits contribute the most to explaining network structure. We show that accounting for a few traits dramatically improves our understanding of the structure of ecological networks. Matching traits for resources and consumers, for example, fruit size and bill gape, are the most successful combinations. These results link ecologically important species attributes to large-scale community structure.

Agriculture in the United States produces approximately $300 billion a year in commodities with livestock accounting for roughly half the value. Production of these commodities is vulnerable to climate change through the direct (i.e., abiotic) effects of changing climate conditions on crop and livestock development and yield (e.g., changes in temperature or precipitation), as well as through the indirect (i.e., biotic) effects arising from changes in the severity of pest pressures, availability of pollination services, and performance of other ecosystem services that affect agricultural productivity. Thus, U.S. agriculture exists as a complex web of interactions between agricultural productivity, ecosystem services, and climate change.
Climate change poses unprecedented challenges to U.S. agriculture because of the sensitivity of agricultural productivity and costs to changing climate conditions. Adaptive action offers the potential to manage the effects of climate change by altering patterns of agricultural activity to capitalize on emerging opportunities while minimizing the costs associated with negative effects. The aggregate effects of climate change will ultimately depend on a complex web of adaptive responses to local climate stressors. These adaptive responses may range from farmers adjusting planting patterns and soil management practices in response to more variable weather patterns, to seed producers investing in the development of drought-tolerant varieties, to increased demand for Federal risk management programs, to adjustments in international trade as nations respond to food security concerns. Potential adaptive behavior can occur at multiple levels in a highly diverse international agricultural system including production, consumption, education, research, services, and governance. Understanding the complexity of such interactions is critical for developing effective adaptive strategies.

Body size is an integral functional trait that underlies pollination-related ecological processes, yet it is often impractical to measure directly. Allometric scaling laws have been used to overcome this problem. However, most existing models rely upon small sample sizes, geographically restricted sampling and have limited applicability for non-bee taxa. Allometric models that consider biogeography, phylogenetic relatedness, and intraspecific variation are urgently required to ensure greater accuracy. We measured body size as dry weight and intertegular distance (ITD) of 391 bee species (4,035 specimens) and 103 hoverfly species (399 specimens) across four biogeographic regions: Australia, Europe, North America, and South America. We updated existing models within a Bayesian mixed-model framework to test the power of ITD to predict interspecific variation in pollinator dry weight in interaction with different co-variates: phylogeny or taxonomy, sexual dimorphism, and biogeographic region. In addition, we used ordinary least squares regression to assess intraspecific dry weight ~ ITD relationships for ten bees and five hoverfly species. Including co-variates led to more robust interspecific body size predictions for both bees and hoverflies relative to models with the ITD alone. In contrast, at the intraspecific level, our results demonstrate that the ITD is an inconsistent predictor of body size for bees and hoverflies. The use of allometric scaling laws to estimate body size is more suitable for interspecific comparative analyses than assessing intraspecific variation. Collectively, these models form the basis of the dynamic R package, "pollimetry," which provides a comprehensive resource for allometric pollination research worldwide.