Contrasting Effects of Cattle Grazing Intensity on Upland-Nesting Duck Production at Nest and Field Scales in the Aspen Parkland, Canada

The Aspen Parkland of Canada is one of the most important breeding areas for temperate nesting ducks in North America. The region is dominated by agricultural land use, with approximately 9.3 million ha in pasture land for cattle grazing. However, the effects of using land for cattle grazing on upland-nesting duck production are poorly understood. The current study was undertaken during 2001 and 2002 to investigate how nest density and nesting success of upland-nesting ducks varied with respect to the intensity of cattle grazing in the Aspen Parkland. We predicted that the removal and trampling of vegetation through cattle grazing would reduce duck nest density. Both positive and negative responses of duck nesting success to grazing have been reported in previous studies, leading us to test competing hypotheses that nesting success would (1) decline linearly with grazing intensity or (2) peak at moderate levels of grazing. Nearly 3300 ha of upland cover were searched during the study. Despite extensive and severe drought, nest searches located 302 duck nests. As predicted, nest density was higher in fields with lower grazing intensity and higher pasture health scores. A lightly grazed field with a pasture score of 85 out of a possible 100 was predicted to have 16.1 nests/100 ha (95% CI = 11.7–22.1), more than five times the predicted nest density of a heavily grazed field with a pasture score of 58 (3.3 nests/100 ha, 95% CI = 2.2–4.5). Nesting success was positively related to nest-site vegetation density across most levels of grazing intensity studied, supporting our hypothesis that reductions in vegetation caused by grazing would negatively affect nesting success. However, nesting success increased with grazing intensity at the field scale. For example, nesting success for a well-concealed nest in a lightly grazed field was 11.6% (95% CI = 3.6–25.0%), whereas nesting success for a nest with the same level of nest-site vegetation in a heavily grazed field was 33.9% (95% CI = 17.0–51.8%). Across the range of residual cover observed in this study, nests with above-average nest-site vegetation density had nesting success rates that exceeded the levels believed necessary to maintain duck populations. Our findings on complex and previously unreported relationships between grazing, nest density, and nesting success provide useful insights into the management and conservation of ground-nesting grassland birds.

Do the Golden-winged Warbler and Blue-winged Warbler Exhibit Species-specific Differences in their Breeding Habitat Use?

We compared habitat features of Golden-winged Warbler (Vermivora chrysoptera) territories in the presence and absence of the Blue-winged Warbler (V. cyanoptera) on reclaimed coal mines in southeastern Kentucky, USA. Our objective was to determine whether there are species specific differences in habitat that can be manipulated to encourage population persistence of the Golden-winged Warbler. When compared with Blue-winged Warblers, Golden-winged Warblers established territories at higher elevations and with greater percentages of grass and canopy cover. Mean territory size (minimum convex polygon) was 1.3 ha (se = 0.1) for Golden-winged Warbler in absence of Blue-winged Warbler, 1.7 ha (se = 0.3) for Golden-winged Warbler coexisting with Blue-winged Warbler, and 2.1 ha (se = 0.3) for Blue-winged Warbler. Territory overlap occurred within and between species (18 of n = 73 territories, 24.7%). All Golden-winged and Blue-winged Warblers established territories that included an edge between reclaimed mine land and mature forest, as opposed to establishing territories in open grassland/shrubland habitat. The mean distance territories extended from a forest edge was 28.0 m (se = 3.8) for Golden-winged Warbler in absence of Blue-winged Warbler, 44.7 m (se = 5.7) for Golden-winged Warbler coexisting with Blue-winged Warbler, and 33.1 m (se = 6.1) for Blue-winged Warbler. Neither territory size nor distances to forest edges differed significantly between Golden-winged Warbler in presence or absence of Blue-winged Warbler. According to Monte Carlo analyses, orchardgrass (Dactylis glomerata), green ash (Fraxinus pennsylvanica) seedlings and saplings, and black locust (Robinia pseudoacacia) saplings were indicative of sites with only Golden-winged Warblers. Sericea lespedeza, goldenrod (Solidago spp.), clematis vine (Clematis spp.), and blackberry (Rubus spp.) were indicative of sites where both species occurred. Our findings complement recent genetic studies and add another factor for examining Golden-winged Warbler population decline. Further, information from our study will aid land managers in manipulating habitat for the Golden-winged Warbler.

A new feedback on climate change from the hydrological cycle

An intensification of the hydrological cycle is a likely consequence of global warming. But changes in the hydrological cycle could affect sea-surface temperature by modifying diffusive ocean heat transports. We investigate this mechanism by studying a coupled general circulation model sensitivity experiment in which the hydrological cycle is artificially amplified. We find that the amplified hydrological cycle depresses sea-surface temperature by enhancing ocean heat uptake in low latitudes. We estimate that a 10% increase in the hydrological cycle will contribute a basin-scale sea-surface temperature decrease of around 0.1°C away from high latitudes, with larger decreases locally. We conclude that an intensified hydrological cycle is likely to contribute a weak negative feedback to anthropogenic climate change.

Mechanisms for the land/sea warming contrast exhibited by simulations of climate change

The land/sea warming contrast is a phenomenon of both equilibrium and transient simulations of climate change: large areas of the land surface at most latitudes undergo temperature changes whose amplitude is more than those of the surrounding oceans. Using idealised GCM experiments with perturbed SSTs, we show that the land/sea contrast in equilibrium simulations is associated with local feedbacks and the hydrological cycle over land, rather than with externally imposed radiative forcing. This mechanism also explains a large component of the land/sea contrast in transient simulations as well. We propose a conceptual model with three elements: (1) there is a spatially variable level in the lower troposphere at which temperature change is the same over land and sea; (2) the dependence of lapse rate on moisture and temperature causes different changes in lapse rate upon warming over land and sea, and hence a surface land/sea temperature contrast; (3) moisture convergence over land predominantly takes place at levels significantly colder than the surface; wherever moisture supply over land is limited, the increase of evaporation over land upon warming is limited, reducing the relative humidity in the boundary layer over land, and hence also enhancing the land/sea contrast. The non-linearity of the Clausius–Clapeyron relationship of saturation specific humidity to temperature is critical in (2) and (3). We examine the sensitivity of the land/sea contrast to model representations of different physical processes using a large ensemble of climate model integrations with perturbed parameters, and find that it is most sensitive to representation of large-scale cloud and stomatal closure. We discuss our results in the context of high-resolution and Earth-system modelling of climate change.

Sharing and visualizing environmental data using Virtual Globes

Virtual globe technology holds many exciting possibilities for environmental science. These easy-to-use, intuitive systems provide means for simultaneously visualizing four-dimensional environmental data from many different sources, enabling the generation of new hypotheses and driving greater understanding of the Earth system. Through the use of simple markup languages, scientists can publish and consume data in interoperable formats without the need for technical assistance. In this paper we give, with examples from our own work, a number of scientific uses for virtual globes, demonstrating their particular advantages. We explain how we have used Web Services to connect virtual globes with diverse data sources and enable more sophisticated usage such as data analysis and collaborative visualization. We also discuss the current limitations of the technology, with particular regard to the visualization of subsurface data and vertical sections.

Land/sea warming ratio in response to climate change: IPCC AR4 model results and comparison with observations

Climate model simulations consistently show that in response to greenhouse gas forcing surface temperatures over land increase more rapidly than over sea. The enhanced warming over land is not simply a transient effect, since it is also present in equilibrium conditions. We examine 20 models from the IPCC AR4 database. The global land/sea warming ratio varies in the range 1.36–1.84, independent of global mean temperature change. In the presence of increasing radiative forcing, the warming ratio for a single model is fairly constant in time, implying that the land/sea temperature difference increases with time. The warming ratio varies with latitude, with a minimum in equatorial latitudes, and maxima in the subtropics. A simple explanation for these findings is provided, and comparisons are made with observations. For the low-latitude (40°S–40°N) mean, the models suggest a warming ratio of 1.51 ± 0.13, while recent observations suggest a ratio of 1.54 ± 0.09.

Detection of Parkinson’s disease tremor-onset with a frequency analysing artificial neural network

Deep Brain Stimulator devices are becoming widely used for therapeutic benefits in movement disorders such as Parkinson's disease. Prolonging the battery life span of such devices could dramatically reduce the risks and accumulative costs associated with surgical replacement. This paper demonstrates how an artificial neural network can be trained using pre-processing frequency analysis of deep brain electrode recordings to detect the onset of tremor in Parkinsonian patients. Implementing this solution into an 'intelligent' neurostimulator device will remove the need for continuous stimulation currently used, and open up the possibility of demand-driven stimulation. Such a methodology could potentially decrease the power consumption of a deep brain pulse generator.

Tripleclouds: an efficient method for representing horizontal cloud inhomogeneity in 1D radiation schemes by using three regions at each height

Radiation schemes in general circulation models currently make a number of simplifications when accounting for clouds, one of the most important being the removal of horizontal inhomogeneity. A new scheme is presented that attempts to account for the neglected inhomogeneity by using two regions of cloud in each vertical level of the model as opposed to one. One of these regions is used to represent the optically thinner cloud in the level, and the other represents the optically thicker cloud. So, along with the clear-sky region, the scheme has three regions in each model level and is referred to as “Tripleclouds.” In addition, the scheme has the capability to represent arbitrary vertical overlap between the three regions in pairs of adjacent levels. This scheme is implemented in the Edwards–Slingo radiation code and tested on 250 h of data from 12 different days. The data are derived from cloud retrievals using radar, lidar, and a microwave radiometer at Chilbolton, southern United Kingdom. When the data are grouped into periods equivalent in size to general circulation model grid boxes, the shortwave plane-parallel albedo bias is found to be 8%, while the corresponding bias is found to be less than 1% using Tripleclouds. Similar results are found for the longwave biases. Tripleclouds is then compared to a more conventional method of accounting for inhomogeneity that multiplies optical depths by a constant scaling factor, and Tripleclouds is seen to improve on this method both in terms of top-of-atmosphere radiative flux biases and internal heating rates.

Influence of south Atlantic sea surface temperatures on rainfall variability and extremes over southern Africa

It is generally agreed that changing climate variability, and the associated change in climate extremes, may have a greater impact on environmentally vulnerable regions than a changing mean. This research investigates rainfall variability, rainfall extremes, and their associations with atmospheric and oceanic circulations over southern Africa, a region that is considered particularly vulnerable to extreme events because of numerous environmental, social, and economic pressures. Because rainfall variability is a function of scale, high-resolution data are needed to identify extreme events. Thus, this research uses remotely sensed rainfall data and climate model experiments at high spatial and temporal resolution, with the overall aim being to investigate the ways in which sea surface temperature (SST) anomalies influence rainfall extremes over southern Africa. Extreme rainfall identification is achieved by the high-resolution microwave/infrared rainfall algorithm dataset. This comprises satellite-derived daily rainfall from 1993 to 2002 and covers southern Africa at a spatial resolution of 0.1° latitude–longitude. Extremes are extracted and used with reanalysis data to study possible circulation anomalies associated with extreme rainfall. Anomalously cold SSTs in the central South Atlantic and warm SSTs off the coast of southwestern Africa seem to be statistically related to rainfall extremes. Further, through a number of idealized climate model experiments, it would appear that both decreasing SSTs in the central South Atlantic and increasing SSTs off the coast of southwestern Africa lead to a demonstrable increase in daily rainfall and rainfall extremes over southern Africa, via local effects such as increased convection and remote effects such as an adjustment of the Walker-type circulation.

Validation of ocean model syntheses against hydrography using a new web application

Results are presented from a new web application called OceanDIVA - Ocean Data Intercomparison and Visualization Application. This tool reads hydrographic profiles and ocean model output and presents the data on either depth levels or isotherms for viewing in Google Earth, or as probability density functions (PDFs) of regional model-data misfits. As part of the CLIVAR Global Synthesis and Observations Panel, an intercomparison of water mass properties of various ocean syntheses has been undertaken using OceanDIVA. Analysis of model-data misfits reveals significant differences between the water mass properties of the syntheses, such as the ability to capture mode water properties.