Green fescue grassland : 50 years of secondary succession under sheep grazing /

"R6-F16-SO-0591."

Arapaho and Roosevelt National Forests and Pawnee National Grassland, forest plan revision : planning action no. 2, planning criteria.

"June 1992."

Habitat use by Darling Downs population of the grassland earless dragon: implications for conservation.

A population of the grassland earless dragon (Tympanocryptis pinguicolla) on the Darling Downs, Queensland, Australia, had been considered extinct until its recent rediscovery. We determined factors affecting grassland earless dragon abundance and prey availability in 3 habitats. Mean dragon body condition and prey numbers were higher in sorghum than grasslands and grass verges. Poisson regression analyses indicated that the dragon numbers were 10 times higher in sorghum, and that this may result from differences in prey numbers as well as other habitat conditions. Tracking data indicated selection of open versus closed microhabitat. Sorghum planted in rows provided alternating open and closed microhabitats for optimal thermoregulation conditions. Grasslands and grass verges were more uniformly shaded. Of individuals we tracked in the sorghum stubble, 85.7% used litter as overnight refuges. Litter was abundant in sorghum and sparse in grass habitats. The practices of minimum tillage and resting stubble strips possibly mitigate agricultural impacts on dragons and provide continuous access to suitable habitat. Changes in agricultural practices that affect the habitat suitability will potentially have detrimental impacts on the population. Our data suggest that conservation efforts be focused on maintaining suitability of habitats in crop fields. We recommend monitoring dragon abundance at control and trial sites of any new agricultural practices; this will provide opportunity to modify or stop undesirable practices before adoption by farmers. Conservation agencies may use our data as a baseline for monitoring long-term viability of the population.

Change of composition and diversity of species and grassland management between different grazing intensity in Pannonian dry and wet grasslands

Investigations were carried out in wet and dry pasture. Coenological recordings were taken in three zones. The first zone (“A”) located 0-50 m near the stable, second zone (“B”) located 50-150 m from the stable, while the third zone (“C”) located farther than 150 m. We have carried out analyses of ecological and environmental factors and life form types. Based on our results for both dry and wet grasslands, quadrates of “A” zone were well isolated from the rest of the zones. Overgrazing, which involves considerable trampling, vanishes differences among vegetations, thereby promotes weed and disturbance tolerant rich vegetation. The lowest species number and diversity could be found here. Due to the nitrogen enrichment due to the constant presence of livestock, drier and less heat demanding habitat developed in the “A” zones, according to the environmental indicators. Because of the change in management, conservation and diversity values of “C” zone increased, however, according to nature protection values it underperformed compared to “B” zone. According to the sample area, wet grasslands from the sandy areas of Kiskunság, preserve nature protection values and grass composition better moving away from stables, due to less grazing pressure. Drier backgrounds tolerate stronger grazing pressure.

Multi-Scaled Grassland-Woody Plant Dynamics in the Heterogeneous Marl Prairies of the Southern Everglades

The Everglades freshwater marl prairie is a dynamic and spatially heterogeneous landscape, containing thousands of tree islands nested within a marsh matrix. Spatial processes underlie population and community dynamics across the mosaic, especially the balance between woody and graminoid components, and landscape patterns reflect interactions among multiple biotic and abiotic drivers. To better understand these complex, multi-scaled relationships we employed a three-tiered hierarchical design to investigate the effects of seed source, hydrology, and more indirectly fire on the establishment of new woody recruits in the marsh, and to assess current tree island patterning across the landscape. Our analyses were conducted at the ground level at two scales, which we term the micro- and meso-scapes, and results were related to remotely detected tree island distributions assessed in the broader landscape, that is, the macro-scape. Seed source and hydrologic effects on recruitment in the micro- and meso-scapes were analyzed via logistic regression, and spatial aggregation in the macro-scape was evaluated using a grid-based univariate O-ring function. Results varied among regions and scales but several general trends were observed. The patterning of adult populations was the strongest driver of recruitment in the micro- and meso-scape prairies, with recruits frequently aggregating around adults or tree islands. However in the macro-scape biologically associated (second order) aggregation was rare, suggesting that emergent woody patches are heavily controlled by underlying physical and environmental factors such as topography, hydrology, and fire.

Dissolved Black Carbon in Grassland Streams: Is There an Effect of Recent Fire History?

While the existence of black carbon as part of dissolved organic matter (DOM) has been confirmed, quantitative determinations of dissolved black carbon (DBC) in freshwater ecosystem and information on factors controlling its concentration are scarce. In this study, stream surface water samples from a series of watersheds subject to different burn frequencies in Konza Prairie (Kansas, USA) were collected in order to determine if recent fire history has a noticeable effect on DBC concentration. The DBC levels detected ranged from 0.04 to 0.11 mg L−1, accounting for ca. 3.32 ± 0.51% of dissolved organic carbon (DOC). No correlation was found between DBC concentration and neither fire frequency nor time since last burn. We suggest that limited DBC flux is related to high burning efficiency, possibly greater export during periods of high discharge and/or the continuous export of DBC over long time scales. A linear correlation between DOC and DBC concentrations was observed, suggesting the export mechanisms determining DOC and DBC concentrations are likely coupled. The potential influence of fire history was less than the influence of other factors controlling the DOC and DBC dynamics in this ecosystem. Assuming similar conditions and processes apply in grasslands elsewhere, extrapolation to a global scale would suggest a global grasslands flux of DBC on the order of 0.14 Mt carbon year−1.

Mobility and toxicity of heavy metal(loid)s arising from contaminated wood ash application to a pasture grassland soil

The authors acknowledge the financial support the Scottish Government’s Rural and Environmental Sciences and Analytical Services (RESAS) in order to complete some of the soil and pore water sample analysis as well as the Czech Ministry of Education, Youth and Sports (COST CZ LD13068), the Czech Science Foundation (GAČR 14-02183P) and EU COST actionFP1407 (‘ModWoodLife’) short term scientific mission grant in order to complete the column leaching test.

Projected responses of North American grassland songbirds to climate change and habitat availability at their northern range limits in Alberta, Canada

Across North America, grassland songbirds have undergone steep population declines over recent decades, commonly attributed to agricultural intensification. Understanding the potential interactions between the impacts of climate change on the future distributions of these species and the availability of suitable vegetation for nesting can support improved risk assessments and conservation planning for this group of species. We used North American bioclimatic niche models to examine future changes in suitable breeding climate for 15 grassland songbird species at their current northern range limits along the boreal forest–prairie ecotone in Alberta, Canada. Our climate suitability projections, combined with the current distribution of native and tame pasture and cropland in Alberta, suggest that some climate-mediated range expansion of grassland songbirds in Alberta is possible. For six of the eight species projected to experience expansions of suitable climate area in Alberta, this suitable climate partly overlaps the current distribution of suitable land cover. Additionally, for more than half of the species examined, most of the area of currently suitable climate was projected to remain suitable to the end of the century, highlighting the importance of Alberta for the long-term persistence of these species. Some northern prairie-endemic species exhibited substantial projected northward shifts of both the northern and southern edges of the area of suitable climate. Baird’s Sparrow (Ammodramus bairdii) and Sprague’s Pipit (Anthus spragueii), both at-risk grassland specialists, are predicted to have limited climate stability within their current ranges, and their expansion into new areas of suitable climate may be limited by the availability of suitable land cover. Our results highlight the importance of the preservation and restoration of remaining suitable grassland habitat within areas of projected climate stability and beyond current northern range limits for the long-term persistence of many grassland songbird species in the face of climate change.

Retrieval of grassland biophysical parameters using multitemporal optical and radar satellite data

The amount and quality of available biomass is a key factor for the sustainable livestock industry and agricultural management related decision making. Globally 31.5% of land cover is grassland while 80% of Ireland’s agricultural land is grassland. In Ireland, grasslands are intensively managed and provide the cheapest feed source for animals. This dissertation presents a detailed state of the art review of satellite remote sensing of grasslands, and the potential application of optical (Moderate–resolution Imaging Spectroradiometer (MODIS)) and radar (TerraSAR-X) time series imagery to estimate the grassland biomass at two study sites (Moorepark and Grange) in the Republic of Ireland using both statistical and state of the art machine learning algorithms. High quality weather data available from the on-site weather station was also used to calculate the Growing Degree Days (GDD) for Grange to determine the impact of ancillary data on biomass estimation. In situ and satellite data covering 12 years for the Moorepark and 6 years for the Grange study sites were used to predict grassland biomass using multiple linear regression, Neuro Fuzzy Inference Systems (ANFIS) models. The results demonstrate that a dense (8-day composite) MODIS image time series, along with high quality in situ data, can be used to retrieve grassland biomass with high performance (R2 = 0:86; p < 0:05, RMSE = 11.07 for Moorepark). The model for Grange was modified to evaluate the synergistic use of vegetation indices derived from remote sensing time series and accumulated GDD information. As GDD is strongly linked to the plant development, or phonological stage, an improvement in biomass estimation would be expected. It was observed that using the ANFIS model the biomass estimation accuracy increased from R2 = 0:76 (p < 0:05) to R2 = 0:81 (p < 0:05) and the root mean square error was reduced by 2.72%. The work on the application of optical remote sensing was further developed using a TerraSAR-X Staring Spotlight mode time series over the Moorepark study site to explore the extent to which very high resolution Synthetic Aperture Radar (SAR) data of interferometrically coherent paddocks can be exploited to retrieve grassland biophysical parameters. After filtering out the non-coherent plots it is demonstrated that interferometric coherence can be used to retrieve grassland biophysical parameters (i. e., height, biomass), and that it is possible to detect changes due to the grass growth, and grazing and mowing events, when the temporal baseline is short (11 days). However, it not possible to automatically uniquely identify the cause of these changes based only on the SAR backscatter and coherence, due to the ambiguity caused by tall grass laid down due to the wind. Overall, the work presented in this dissertation has demonstrated the potential of dense remote sensing and weather data time series to predict grassland biomass using machine-learning algorithms, where high quality ground data were used for training. At present a major limitation for national scale biomass retrieval is the lack of spatial and temporal ground samples, which can be partially resolved by minor modifications in the existing PastureBaseIreland database by adding the location and extent ofeach grassland paddock in the database. As far as remote sensing data requirements are concerned, MODIS is useful for large scale evaluation but due to its coarse resolution it is not possible to detect the variations within the fields and between the fields at the farm scale. However, this issue will be resolved in terms of spatial resolution by the Sentinel-2 mission, and when both satellites (Sentinel-2A and Sentinel-2B) are operational the revisit time will reduce to 5 days, which together with Landsat-8, should enable sufficient cloud-free data for operational biomass estimation at a national scale. The Synthetic Aperture Radar Interferometry (InSAR) approach is feasible if there are enough coherent interferometric pairs available, however this is difficult to achieve due to the temporal decorrelation of the signal. For repeat-pass InSAR over a vegetated area even an 11 days temporal baseline is too large. In order to achieve better coherence a very high resolution is required at the cost of spatial coverage, which limits its scope for use in an operational context at a national scale. Future InSAR missions with pair acquisition in Tandem mode will minimize the temporal decorrelation over vegetation areas for more focused studies. The proposed approach complements the current paradigm of Big Data in Earth Observation, and illustrates the feasibility of integrating data from multiple sources. In future, this framework can be used to build an operational decision support system for retrieval of grassland biophysical parameters based on data from long term planned optical missions (e. g., Landsat, Sentinel) that will ensure the continuity of data acquisition. Similarly, Spanish X-band PAZ and TerraSAR-X2 missions will ensure the continuity of TerraSAR-X and COSMO-SkyMed.

Biomass, quality traits and methane production of extensive grassland: biodiversity effects and sensor approaches

Energy policies around the world are mandating for a progressive increase in renewable energy production. Extensive grassland areas with low productivity and land use limitations have become target areas for sustainable energy production to avoid competition with food production on the limited available arable land resources and minimize further conversion of grassland into intensively managed energy cropping systems or abandonment. However, the high spatio-temporal variability in botanical composition and biochemical parameters is detrimental to reliable assessment of biomass yield and quality regarding anaerobic digestion. In an approach to assess the performance for predicting biomass using a multi-sensor combination including NIRS, ultra-sonic distance measurements and LAI-2000, biweekly sensor measurements were taken on a pure stand of reed canary grass (Phalaris aruninacea), a legume grass mixture and a diversity mixture with thirty-six species in an experimental extensive two cut management system. Different combinations of the sensor response values were used in multiple regression analysis to improve biomass predictions compared to exclusive sensors. Wavelength bands for sensor specific NDVI-type vegetation indices were selected from the hyperspectral data and evaluated for the biomass prediction as exclusive indices and in combination with LAI and ultra-sonic distance measurements. Ultrasonic sward height was the best to predict biomass in single sensor approaches (R² 0.73 – 0.76). The addition of LAI-2000 improved the prediction performance by up to 30% while NIRS barely improved the prediction performance. In an approach to evaluate broad based prediction of biochemical parameters relevant for anaerobic digestion using hyperspectral NIRS, spectroscopic measurements were taken on biomass from the Jena-Experiment plots in 2008 and 2009. Measurements were conducted on different conditions of the biomass including standing sward, hay and silage and different spectroscopic devices to simulate different preparation and measurement conditions along the process chain for biogas production. Best prediction results were acquired for all constituents at laboratory measurement conditions with dried and ground samples on a bench-top NIRS system (RPD > 3) with a coefficient of determination R2 < 0.9. The same biomass was further used in batch fermentation to analyse the impact of species richness and functional group composition on methane yields using whole crop digestion and pressfluid derived by the Integrated generation of solid Fuel and Biogas from Biomass (IFBB) procedure. Although species richness and functional group composition were largely insignificant, the presence of grasses and legumes in the mixtures were most determining factors influencing methane yields in whole crop digestion. High lignocellulose content and a high C/N ratio in grasses may have reduced the digestibility in the first cut material, excess nitrogen may have inhibited methane production in second cut legumes, while batch experiments proved superior specific methane yields of IFBB press fluids and showed that detrimental effects of the parent material were reduced by the technical treatment

Rainfall infiltration and soil hydrological characteristics below ancient forest, planted forest and grassland in a temperate northern climate

How rainfall infiltration rate and soil hydrological characteristics develop over time under forests of different ages in temperate regions is poorly understood. In this study, infiltration rate and soil hydrological characteristics were investigated under forests of different ages and under grassland. Soil hydraulic characteristics were measured at different scales under a 250-year-old grazed grassland (GL), 6-year-old (6yr) and 48-year-old (48yr) Scots pine (Pinus sylvestris) plantations, remnant 300-year-old individual Scots pine (OT) and a 4000-year-old Caledonian Forest (AF). In situ field-saturated hydraulic conductivity (Kfs) was measured, and visible root:soil area was estimated from soil pits. Macroporosity, pore structure and macropore connectivity were estimated from X-ray tomography of soil cores, and from water-release characteristics. At all scales, the median values for Kfs, root fraction, macroporosity and connectivity values tended to AF>OT>48yr>GL>6yr, indicating that infiltration rates and water storage increased with forest age. The remnant Caledonian Forest had a huge range of Kfs (12 to >4922mmh-1), with maximum Kfs values 7 to 15 times larger than those of 48-year-old Scots pine plantation, suggesting that undisturbed old forests, with high rainfall and minimal evapotranspiration in winter, may act as important areas for water storage and sinks for storm rainfall to infiltrate and transport to deeper soil layers via preferential flow. The importance of the development of soil hydrological characteristics under different aged forests is discussed.

Exploring nest destruction and bird mortality in mown Mediterranean dry grasslands: an increasing threat to grassland bird conservation

In recent years, haying has extended to Iberian Mediterranean dry grasslands potentially impacting on grassland bird ecology. We evaluated the impact of haying on a grassland bird community of South Portugal. Our main goals were: (1) to investigate the exposure of different species to haying, (2) to investigate potential removal of nests and dead birds from hayed fields by haying machinery using the ratio (REC) between the expected number of records and the number of records collected and (3) to link clutch destruction and bird mortality with haying management practices. Hayed fields were surveyed for signs of breeding and birds censused prior to mowing. Linear models were computed, linking the REC with haying machinery and sward properties. GLMs and model averaging were used to obtain models linking clutch destruction, bird mortality and haying management variables. Only 4 % of records evidenced successful nesting attempts (N = 177). REC evaluation suggested high nest or dead bird removal by the machinery, particularly in fields with lower vegetation biomass prior to cutting. Sickle bar mowers and one-rotor rotary rakes returned higher REC but lower probability of found nests removed from the original nesting sites comparatively to discs mowers and wheel rakes. Higher probabilities of mortality events were found in fields mown earlier (but not in all years). On the other hand, lower mortality was found in fields raked with two-rotor rotary rakes. Delayed haying, silage production in temporary crops and the use haying machinery enabling simultaneously mowing and gathering hay in lines are discussed as management alternatives.