Geographic distribution of plant pathogens in response to climate change

Geographic distributions of pathogens are the outcome of dynamic processes involving host availability, susceptibility and abundance, suitability of climate conditions, and historical contingency including evolutionary change. Distributions have changed fast and are changing fast in response to many factors, including climatic change. The response time of arable agriculture is intrinsically fast, but perennial crops and especially forests are unlikely to adapt easily. Predictions of many of the variables needed to predict changes in pathogen range are still rather uncertain, and their effects will be profoundly modified by changes elsewhere in the agricultural system, including both economic changes affecting growing systems and hosts and evolutionary changes in pathogens and hosts. Tools to predict changes based on environmental correlations depend on good primary data, which is often absent, and need to be checked against the historical record, which remains very poor for almost all pathogens. We argue that at present the uncertainty in predictions of change is so great that the important adaptive response is to monitor changes and to retain the capacity to innovate, both by access to economic capital with reasonably long-term rates of return and by retaining wide scientific expertise, including currently less fashionable specialisms.

Uncertainty in climate change impacts on basin-scale freshwater resources – preface to the special issue: the QUEST-GSI methodology and synthesis of results

This paper presents a preface to this Special Issue on the results of the QUEST-GSI (Global Scale Impacts) project on climate change impacts on catchment-scale water resources. A detailed description of the unified methodology, subsequently used in all studies in this issue, is provided. The project method involved running simulations of catchment-scale hydrology using a unified set of past and future climate scenarios, to enable a consistent analysis of the climate impacts around the globe. These scenarios include "policy-relevant" prescribed warming scenarios. This is followed by a synthesis of the key findings. Overall, the studies indicate that in most basins the models project substantial changes to river flow, beyond that observed in the historical record, but that in many cases there is considerable uncertainty in the magnitude and sign of the projected changes. The implications of this for adaptation activities are discussed.

Impact of the Arctic Ocean Atlantic water layer on Siberian shelf hydrography

This paper examines the role of the Arctic Ocean Atlantic water (AW) in modifying the Laptev Sea shelf bottom hydrography on the basis of historical records from 1932 to 2008, field observations carried out in April–May 2008, and 2002–2009 cross‐slope measurements. A climatology of bottom hydrography demonstrates warming that extends offshore from the 30–50 m depth contour. Bottom layer temperature‐time series constructed from historical records links the Laptev Sea outer shelf to the AW boundary current transporting warm and saline water from the North Atlantic. The AW warming of the mid‐1990s and the mid‐2000s is consistent with outer shelf bottom temperature variability. For April–May 2008 we observed on‐shelf near‐bottom warm and saline water intrusions up to the 20 m isobath. These intrusions are typically about 0.2°C warmer and 1–1.5 practical salinity units saltier than ambient water. The 2002–2009 cross‐slope observations are suggestive for the continental slope upward heat flux from the AW to the overlying low‐halocline water (LHW). The lateral on‐shelf wind‐driven transport of the LHW then results in the bottom layer thermohaline anomalies recorded over the Laptev Sea shelf. We also found that polynya‐induced vertical mixing may act as a drainage of the bottom layer, permitting a relatively small portion of the AW heat to be directly released to the atmosphere. Finally, we see no significant warming (up until now) over the Laptev Sea shelf deeper than 10–15 m in the historical record. Future climate change, however, may bring more intrusions of Atlantic‐modified waters with potentially warmer temperature onto the shelf, which could have a critical impact on the stability of offshore submarine permafrost.

Historical and current machine intelligence

In this article, we provide an initial insight into the study of MI and what it means for a machine to be intelligent. We discuss how MI has progressed to date and consider future scenarios in a realistic and logical way as much as possible. To do this, we unravel one of the major stumbling blocks to the study of MI, which is the field that has become widely known as "artificial intelligence"