Risk Factors for Crop Health Under Global Change and Agricultural Shifts: A Framework of Analyses Using Rice in Tropical and Subtropical Asia as a Model

Climate change has a number of observed, anticipated, or possible consequences on crop health worldwide. Global change, on the other hand, incorporates a number of drivers of change, including global population increase, natural resource evolution, and supply demand shifts in markets, from local to global. Global and climate changes interact in their effects on global ecosystems. Identifying and quantifying the impacts of global and climate changes on plant diseases is complex. A number of nonlinear relationships, such as the injury (epidemic) damage (crop loss) relationship, are superimposed on the interplay among the three summits of the disease triangle (host, pathogen, environment). Work on a range of pathosystems involving rice, peanut, wheat, and coffee has shown the direct linkage and feedback between production situations and crop health. Global and climate changes influence the effects of system components on crop health. The combined effects of global and climate changes on diseases vary from one pathosystem to another within the tetrahedron framework (humans, pathogens, crops, environment) where human beings, from individual farmers to consumers to entire societies, interact with hosts, pathogens, and the environment. This article highlights international phytopathological research addressing the effects of global and climate changes on plant diseases in a range of crops and pathosystems.

Global changes in marine systems: A social–ecological approach

Resilience theory has emerged as a holistic concept well suited to analyzing tourism systems and which promises important insights into the sustainability of tourism destinations in the face of accelerating global environmental change (GEC). This article presents empirical research into the social-ecological resilience of tour operators using the case study destination of the Otago Peninsula, Dunedin, New Zealand. It addresses the following research question: How do birdwatching tour operators build resilience to drivers of environmental change, including climatic drivers, into their operations? Qualitative interviews with providers of a specific nature tourism sector activity – birdwatching – were conducted with stakeholders including tour operators, conservation organizations, and local government members. The findings highlight current and possible future challenges to birdwatching tourism on the Otago Peninsula. The paper introduces a conceptual framework which highlights the tour operators’ main coping strategies in response to key perceived social-ecological system (SES) drivers of change. Overall, tour operators perceived their main social-ecological resilience to be the diversity of the species of the Otago Peninsula, their business experience, and the strength of their local stakeholder network to respond to SES crises.

Dry rivers are a type of non-perennial river characterized by extreme dry conditions and dominance of terrestrial habitats. They are present in all continents, being especially abundant in arid and semiarid regions. Recent studies have shown their capacity to provide ecosystem services, although they are often undervalued and altered. This study is a literature review on the ecosystem services provided by dry rivers to human well-being. We apply the conceptual framework for the Millennium Ecosystem Assessment. First, we describe and exemplify the services provided by the natural system and its biodiversity. Second, we present the contributions of the local social system to service provision through co-production processes. Finally, the main drivers of ecosystem change that alter service provision are listed and discussed. We found that dry rivers and their biodiversity contribute to local human well-being. The ecological knowledge and culture of local human communities acquired over generations contribute to service provision maintaining the socio-ecological system’s sustainability and its resilience to disturbances. Among drivers of change, those of a social-cultural (e.g., sedentarization) and economic (e.g., globalization) nature affect dry rivers’ capacity to provide ecosystem services the most. Reconciling people and dry rivers requires a great deal of research and education.

A rice trade crisis occurred at the beginning of 2008, which led to soaring retail prices on markets. This price spike affected foremost the poor, as rice is the staple of roughly half the poor in the world. Such events concern plant pathologists because plant diseases are major yield-reducers. Improving crop health can significantly improve yield, as well as enhance the efficiency of using increasingly scarce and often non-renewable agricultural resources: water, labour, energy and land. With two examples, we illustrate how basic plant pathological research at the gene or population level, has produced responses that led to significant yield gains and improved system performance. We also note that the timeline for research to deliver such responses is about 40 years. A shortage of agricultural resources, in turn, causes unprecedented changes in rice production situations worldwide. The relationships between production situations and crop health are well documented in rice. Changes in cropping practices and systems will inevitably lead to new crop health problems, not only in terms of emerging or re-emerging diseases but also in terms of combinations of yield-reducing factors, including diseases. Thus, in addition to addressing ‘classic’ rice diseases, such as blast, bacterial blight, or tungro, phytopathological research now has to address (1) recurrent diseases that cause regular yield attrition such as rice sheath blight, and (2) disease syndromes, which are brought about by changing patterns of crop management systems. New approaches involving knowledge from the molecular and gene level to the ecosystem level can enable plant pathologists to tackle these new challenges.

Global change is increasing biotic homogenization globally, which modifies the functioning of ecosystems. While tendencies towards taxonomic homogenization in biological communities have been extensively studied, functional homogenization remains an understudied facet of biodiversity. Here, we tested four hypotheses related to long-term changes (1991-2016) in the taxonomic and functional arrangement of freshwater macroinvertebrate assemblages across space and possible drivers of these changes. Using data collected annually at 64 river sites in mainland New Zealand, we related temporal changes in taxonomic and functional spatial β-diversity, and the contribution of individual sites to β-diversity, to a set of global, regional, catchment and reach-scale environmental descriptors. We observed long-term, mostly climate-induced, temporal trends towards taxonomic homogenization but functional differentiation among macroinvertebrate assemblages. These changes were mainly driven by replacements of species and functional traits among assemblages, rather than nested species loss. In addition, there was no difference between the mean rate of change in the taxonomic and functional facets of β-diversity. Climatic processes governed overall population and community changes in these freshwater ecosystems, but were amplified by multiple anthropogenic, topographic and biotic drivers of environmental change, acting widely across the landscape. The functional diversification of communities could potentially provide communities with greater stability, resistance and resilience capacity to environmental change, despite ongoing taxonomic homogenization. Therefore, our study highlights a need to further understand temporal trajectories in both taxonomic and functional components of species communities, which could enable a clearer picture of how biodiversity and ecosystems will respond to future global changes.

Change Drivers across Supply Chains: The Case of Fishery and Aquaculture in France

Flood trends are commonly assessed based on instantaneous peak flows on an hourly timescale, as these are most relevant for flood management. However, when hourly data are missing, it has been suggested to perform flood statistics on daily flood values instead, assuming a scaling relationship that depends on the shape of the flood hydrograph and applies over the entire observation period (e.g. Bartens & Haberlandt, 2021). In an Austria-wide assessment, recent flood trends show diverging spatial patterns that contradict such a stationarity assumption. Interestingly, an aggravation of the flood situation is mainly observed for the peak flow (IPF), while the high values of the mean daily discharge (MDF) show much smaller and, importantly, less significant trends. Rather than applying flood statistics corrections (e.g. Beylich et al. 2021), the aim of this contribution is to use flood divergence at different timescales as a mean of inferring likely drivers of flood trends. To this end, we combine several established and innovative indicators, such as a trend divergence index (peak versus daily flood scale), a seasonal trend index (to infer information about flood generation processes), and a seasonal shift index (to infer changes in the relevance of these processes). We show the extent to which these indices can inform us about likely drivers of change, i.e. climate-related vs. anthropogenic changes in the catchment. We discuss how these indicators perform in the light of existing flood scale indices, such as the flood timescale (Gaál et al., 2012) and the peak-volume ratio (Bartens & Haberlandt, 2021). The results suggest that the conflicting space-time patterns contain a wealth of information that is highly informative about changes in flood controls under global change.

Climate and land-use changes are expected to be the primary drivers of future global biodiversity loss. Although theory suggests that these factors impact species synergistically, past studies have either focused on only one in isolation or have substituted space for time, which often results in confounding between drivers. Tests of synergistic effects require congruent time series on animal populations, climate change and land-use change replicated across landscapes that span the gradient of correlations between the drivers of change. Using a unique time series of high-resolution climate (measured as temperature and precipitation) and land-use change (measured as forest change) data, we show that these drivers of global change act synergistically to influence forest bird population declines over 29years in the Pacific Northwest of the United States. Nearly half of the species examined had declined over this time. Populations declined most in response to loss of early seral and mature forest, with responses to loss of early seral forest amplified in landscapes that had warmed over time. In addition, birds declined more in response to loss of mature forest in areas that had dried over time. Climate change did not appear to impact populations in landscapes with limited habitat loss, except when those landscapes were initially warmer than the average landscape. Our results provide some of the first empirical evidence of synergistic effects of climate and land-use change on animal population dynamics, suggesting accelerated loss of biodiversity in areas under pressure from multiple global change drivers. Furthermore, our findings suggest strong spatial variability in the impacts of climate change and highlight the need for future studies to evaluate multiple drivers simultaneously to avoid potential misattribution of effects.

Time series data on arthropod populations are critical for understanding the magnitude, direction, and drivers of change. However, most arthropod monitoring programs are short-lived and restricted in taxonomic resolution. Monitoring data from the Arctic are especially underrepresented, yet critical to uncovering and understanding some of the earliest biological responses to rapid environmental change. Clear imprints of climate on the behavior and life history of some Arctic arthropods have been demonstrated, but a synthesis of population-level abundance changes across taxa is lacking. We utilized 24 y of abundance data from Zackenberg in High-Arctic Greenland to assess trends in abundance and diversity and identify potential climatic drivers of abundance changes. Unlike findings from temperate systems, we found a nonlinear pattern, with total arthropod abundance gradually declining during 1996 to 2014, followed by a sharp increase. Family-level diversity showed the opposite pattern, suggesting increasing dominance of a small number of taxa. Total abundance masked more complicated trajectories of family-level abundance, which also frequently varied among habitats. Contrary to expectation in this extreme polar environment, winter and fall conditions and positive density-dependent feedbacks were more common determinants of arthropod dynamics than summer temperature. Together, these data highlight the complexity of characterizing climate change responses even in relatively simple Arctic food webs. Our results underscore the need for data reporting beyond overall trends in biomass or abundance and for including basic research on life history and ecology to achieve a more nuanced understanding of the sensitivity of Arctic and other arthropods to global changes.

A series of experiments was conducted where a range of injuries due to rice pests (pathogens, insects, and weeds) was manipulated simultaneously with a range of production factors (fertilizer input, water supply, crop establishment method, variety) in different seasons and years. These factors were chosen to represent lowland rice production situations characterized in surveys conducted in tropical Asia and their corresponding range of attainable yield. Experiments complemented one another in exploring the response surface of rice yields to yield-limiting and yield-reducing factors. The resulting experimental data base consisted of 445 individual plots and involved 11 manipulated injuries in a range of attainable yields of 2 to 11 t ha-1. A first, nonparametric, multivariate analysis led to a hierarchy of potential injuries, from marginally (e.g., bacterial leaf blight) to extremely harmful (e.g., rice tungro disease). A second, parametric, multivariate approach resulted in a multiple regression model involving factors generated by principal component analysis on injuries that adequately described the variation in actual yield. One major finding was that some (attainable yield × injury factors) interactions significantly contributed to the description of variation in actual yield, indicating that some injuries (or their combinations) had a stronger or weaker yield-reducing effect, depending on the level of attainable yield. For instance, yield losses due to sheath blight, weed infestation, and rice tungro disease tend to increase, remain stable, and decrease, respectively, with increasing attainable yields. Back-computations using the principal component regression model estimated yield losses caused by individual injuries, using the mean injury levels in a population of farmers' fields surveyed across tropical Asia. The results indicate that sheath blight, brown spot, and leaf blast are diseases that cause important losses (between 1 and 10%) regionally. Among the insect injuries, only white heads caused by stem borers appear of relevance (2.3% yield losses). These injuries, however, do not match in importance those caused by weeds, whether outgrowing the rice crop canopy (WA) or not (WB), both types of injuries causing about 20% yield losses when considered individually. When all mean injuries were combined into one mean injury profile occurring at a regional attainable yield of 5.5 t ha-1, a mean yield loss of 37.2% was estimated, indicating that injuries were less than additive in their yield-reducing effects. Scenario analyses were conducted in a set of (production situations × injury profiles) combinations characterized from surveys in farmers' fields in tropical Asia. Depending on the scenario chosen, losses ranging from 24 to 41% were found.

Scenario analysis constitutes a useful approach to synthesize knowledge and derive hypotheses in the case of complex systems that are documented with mainly qualitative or very diverse information. In this article, a framework for scenario analysis is designed and then, applied to global wheat health within a timeframe from today to 2050. Scenario analysis entails the choice of settings, the definition of scenarios of change, and the analysis of outcomes of these scenarios in the chosen settings. Three idealized agrosystems, representing a large fraction of the global diversity of wheat-based agrosystems, are considered, which represent the settings of the analysis. Several components of global changes are considered in their consequences on global wheat health: climate change and climate variability, nitrogen fertilizer use, tillage, crop rotation, pesticide use, and the deployment of host plant resistances. Each idealized agrosystem is associated with a scenario of change that considers first, a production situation and its dynamics, and second, the impacts of the evolving production situation on the evolution of crop health. Crop health is represented by six functional groups of wheat pathogens: the pathogens associated with Fusarium head blight; biotrophic fungi, Septoria-like fungi, necrotrophic fungi, soilborne pathogens, and insect-transmitted viruses. The analysis of scenario outcomes is conducted along a risk-analytical pattern, which involves risk probabilities represented by categorized probability levels of disease epidemics, and risk magnitudes represented by categorized levels of crop losses resulting from these levels of epidemics within each production situation. The results from this scenario analysis suggest an overall increase of risk probabilities and magnitudes in the three idealized agrosystems. Changes in risk probability or magnitude however vary with the agrosystem and the functional groups of pathogens. We discuss the effects of global changes on the six functional groups, in terms of their epidemiology and of the crop losses they cause. Scenario analysis enables qualitative analysis of complex systems, such as plant pathosystems that are evolving in response to global changes, including climate change and technology shifts. It also provides a useful framework for quantitative simulation modeling analysis for plant disease epidemiology.

Spatiotemporal patterns and effects of climate and land use on surface water extent dynamics in a dryland region with three decades of Landsat satellite data

Drought is a stronger driver of soil respiration and microbial communities than nitrogen or phosphorus addition in two Mediterranean tree species

Towards a multidimensional view of biodiversity and ecosystem functioning in a changing world