Edward W. Bork

Worldwide evidence of a unimodal relationship between productivity and plant species richness

Grassland diversity and ecosystem productivity The relationship between plant species diversity and ecosystem productivity is controversial. The debate concerns whether diversity peaks at intermediate levels of productivity—the so-called humped-back model—or whether there is no clear predictable relationship. Fraser et al. used a large, standardized, and geographically diverse sample of grasslands from six continents to confirm the validity and generality of the humped-back model. Their findings pave the way for a more mechanistic understanding of the factors controlling species diversity. Science, this issue p. 302 The humped-back model of plant species diversity is confirmed by a global grassland survey. The search for predictions of species diversity across environmental gradients has challenged ecologists for decades. The humped-back model (HBM) suggests that plant diversity peaks at intermediate productivity; at low productivity few species can tolerate the environmental stresses, and at high productivity a few highly competitive species dominate. Over time the HBM has become increasingly controversial, and recent studies claim to have refuted it. Here, by using data from coordinated surveys conducted throughout grasslands worldwide and comprising a wide range of site productivities, we provide evidence in support of the HBM pattern at both global and regional extents. The relationships described here provide a foundation for further research into the local, landscape, and historical factors that maintain biodiversity.

Influence of Vegetation, Slope, and Lidar Sampling Angle on DEM Accuracy

Detailed GIS studies across spatially complex rangeland landscapes, including the Aspen Parkland of western Canada, require accurate digital elevation models (DEM). Following the interpolation of last return lidar (light detection and ranging) data into a DEM, a series of 256 reference plots, stratified by vegetation type, slope and lidar sensor sampling angle, were surveyed using a total laser station, differential GPS and 27 interconnected benchmarks to assess variation in DEM accuracy. Interpolation using Inverse Distance Weighting IDW resulted in lower mean error than other methods. Across the study area, overall signed error and RMSE were � 0.02 m and 0.59 m, respectively. Signed errors indicated elevations were over-estimated in forest but under-estimated within meadow habitats. Increasing slope gradient increased vertical absolute errors and RMSE. In contrast, lidar sampling angle had little impact on measured error. These results have implications for the development and use of high-resolution DEM models derived from lidar data.

Cover components on long-term seasonal sheep grazing treatments in three-tip sagebrush steppe.

The effects of fall and spring sheep use on cover components and recovery following a change in seasonality of grazing practices, were studied within long-term grazing treatments of three-tip sagebrush (Artemisia tripartita Rydb.) steppe on the U.S. Sheep Experiment Station near Dubois, Ida. Few significant differences existed among treatments within the litter, moss, lichen, and soil components, but several differences in vegetational cover categories occurred. More live shrub and annual grass cover were observed in the long-term (since 1924) and new spring (since 1950) treatments than in the long-term fall (since 1924), new fall (since 1950), old exclosure (since 1940), and new exclosure (since 1950) (P < 0.01). More perennial grass and forb cover, and less dead shrub cover existed in fall-grazed treatments (P < 0.01). The new fall- grazed treatment previously grazed in the spring failed to reach a more uniform mixture of perennial growth forms after 46 years such as was evident in the long-term fall, which suggests low resilience following spring grazing. The exclosure which was heavily spring and fall-grazed prior to 1950 had even less perennial forb cover than the new fall treatment, indicating that the cessation of sheep grazing did not promote herb recovery any better than continued fall use. The direct impact of sheep herbivory and its indirect effects on the competitive relationships among major plants appear to have affected the cover of sagebrush steppe components at this study site.

Herbage Yield Losses in Perennial Pasture Due to Canada Thistle (Cirsium arvense)

Although the impact of Canada thistle (CT) on annual crop production is relatively well established, few investigations report on this weeds impact within perennial pastures. This field study assessed herbage yield losses within eight central Alberta pastures from 1999 to 2001. Each pasture was sampled in 1999 to quantify thistle and herbage biomass within 25 permanent plots. CT was controlled in 2000 and the response of vegetation measured in 2000 and 2001. Before removal, significant negative relationships (P < 0.05) between thistle abundance and herbage were noted at six sites. After thistle removal, herbage at several sites displayed positive responses. Both thistle density and biomass adequately predicted herbage yield loss. Yield losses due to CT can be substantial, peaking at 2 kg/ha for each kilogram of standing thistle biomass and 4.3 kg/ha with each additional thistle stem per square meter. Demonstrated yield losses were variable among sites however, likely due to factors such as heterogeneity in soils, available moisture, and variation in disturbance history or pasture vegetation composition. CT management in perennial pastures of western Canada may enhance pasture production, but further research is required to reliably predict the ability of pastures to respond. Nomenclature: Canada thistle, Cirsium arvense (L.) Scop #3 CIRAR. Additional index words: Forage biomass, pasture heterogeneity, precipitation, sward composition, weed density. Abbreviations: CT, Canada thistle; N, nitrogen; OM, organic matter.

Determinants of bacterial communities in Canadian agroforestry systems.

Land-use change is one of the most important factors influencing soil microbial communities, which play a pivotal role in most biogeochemical and ecological processes. Using agroforestry systems as a model, this study examined the effects of land uses and edaphic properties on bacterial communities in three agroforestry types covering a 270 km soil-climate gradient in Alberta, Canada. Our results demonstrate that land-use patterns exert stronger effects on soil bacterial communities than soil zones in these agroforestry systems. Plots with trees in agroforestry systems promoted greater bacterial abundance and to some extent species richness, which was associated with more nutrient-rich soil resources. While Acidobacteria, Actinobacteria and Alphaproteobacteria were the dominant bacterial phyla and subphyla across land uses, Arthrobacter, Acidobacteria_Gp16, Burkholderia, Rhodanobacter and Rhizobium were the keystone taxa in these agroforestry systems. Soil pH and carbon contents emerged as the major determinants of bacterial community characteristics. We found non-random co-occurrence and modular patterns of soil bacterial communities, and these patterns were controlled by edaphic factors and not their taxonomy. Overall, this study highlights the drivers and co-occurrence patterns of soil microbial communities in agroforestry systems.

Soil depth assessment of sagebrush grazing treatments using electromagnetic induction.

Depth to a root restricting layer affects both soil moisture and nutrient availability, resources strongly correlated to plant cover and production. We evaluated the potential of 2 electromagnetic induction meters (EM38 and EM31) for non-destructively assessing soil depth to bedrock in 2 long-term seasonal sagebrush steppe sheep grazing treatments with different vegetational compositions. Apparent conductivity readings, measured with the EM38 and EM31 in both the horizontal (H) and vertical (V) dipole orientations, were positively related to soil depth. Apparent conductivity measured with the EM31H (r2 = 0.78) and EM38V (r2 = 0.75) were the best predictors of depth. Soil depth distributions were similar between grazing treatments based on Kolmogorov-Smirnov (K-S) tests of the EM38H apparent conductivity (P = 0.47) and EM38V apparent conductivity (P = 0.56). In constrast, K-S tests for the EM31H apparent conductivity (P = 0.09) and EM31V apparent conductivity (P < 0.01) indicated the fall-grazed treatment had a larger area in which soil depth exceeded 150 cm. Because less than 2% of each grazing treatment was predicted to have soils deeper than 150 cm, however, overall site differences between the 2 treatments appeared to be minor. Therefore, the vegetational differences between the treatments have probably resulted more from differences in the seasonality of grazing rather than ecological site characteristics as reflected in soil depth. Maps of soil depth indicated both treatments consisted of intermittent shallow and deep soils, created by several parallel basalt pressure ridges. Results suggest electromagnetic induction can effectively assess the spatial variability of soil depth and could aid in selecting sites for rangeland monitoring or manipulation.

Calibration of broad- and narrow-band spectral variables for rangeland cover component quantification

Eight broad-band (BB) and 52 narrow-band (NB) spectral variables collected on single sampling dates in June, July and August of 1996 were used, either individually or over multi-temporal periods (June to July, June to August, and July to August), to evaluate their potential use in estimating key cover components (e.g. bare soil, rock, litter, lichen, moss, total live vegetation, shrubs, herbs, forbs and grasses) within a sagebrush steppe rangeland. Regression correlation coefficients ranged from a low of 0.36 and 0.42 for moss to 0.80 and 0.87 for total live vegetation, for the leading BB and NB spectral variables respectively. In general, more specific plant growth forms (e.g. grass and forb) had a poorer explicability (i.e. lower regression correlation coefficient, r) than the more general components (e.g. herbs and total live vegetation). Several cover components, however, had improved explicability with NB spectral parameters using simple regression, relative to the leading BB variable. The greatest i...

Upland plant community classification in Elk Island national park, Alberta, Canada, using disturbance history and physical site factors

Our objective was to classify upland sites sampled from an area in and around Elk Island National Park, Alberta, Canada, into community types and interpret them in terms of variation in environmental factors, including fire and wild ungulate herbivory. The vegetation from 36 sites was classified into 6 community types using TWINSPAN. These types could be effectively interpreted and explained with canonical correspondence analysis ordination procedures. Based on a forward regression, topography, ungulate use and prescribed burning related closely to the first two canonical axes, accounting for 47.2 and 21.1% of the species-environment relation among sites, respectively. Unique and meaningful combinations of environmental variables influenced community-type understory composition and structure, as well as the characteristics of the tree overstory. This information provided the basis for a preliminary state and transition model of vegetation dynamics for these rangelands, which could be used to assist Park managers in manipulating plant communities within the landscape using ungulate removal and prescribed burning programs.

Asymmetric responses of primary productivity to precipitation extremes: A synthesis of grassland precipitation manipulation experiments

Climatic changes are altering Earths hydrological cycle, resulting in altered precipitation amounts, increased interannual variability of precipitation, and more frequent extreme precipitation events. These trends will likely continue into the future, having substantial impacts on net primary productivity (NPP) and associated ecosystem services such as food production and carbon sequestration. Frequently, experimental manipulations of precipitation have linked altered precipitation regimes to changes in NPP. Yet, findings have been diverse and substantial uncertainty still surrounds generalities describing patterns of ecosystem sensitivity to altered precipitation. Additionally, we do not know whether previously observed correlations between NPP and precipitation remain accurate when precipitation changes become extreme. We synthesized results from 83 case studies of experimental precipitation manipulations in grasslands worldwide. We used meta-analytical techniques to search for generalities and asymmetries of aboveground NPP (ANPP) and belowground NPP (BNPP) responses to both the direction and magnitude of precipitation change. Sensitivity (i.e., productivity response standardized by the amount of precipitation change) of BNPP was similar under precipitation additions and reductions, but ANPP was more sensitive to precipitation additions than reductions; this was especially evident in drier ecosystems. Additionally, overall relationships between the magnitude of productivity responses and the magnitude of precipitation change were saturating in form. The saturating form of this relationship was likely driven by ANPP responses to very extreme precipitation increases, although there were limited studies imposing extreme precipitation change, and there was considerable variation among experiments. This highlights the importance of incorporating gradients of manipulations, ranging from extreme drought to extreme precipitation increases into future climate change experiments. Additionally, policy and land management decisions related to global change scenarios should consider how ANPP and BNPP responses may differ, and that ecosystem responses to extreme events might not be predicted from relationships found under moderate environmental changes.

Separation of grassland litter and ecosite influences on seasonal soil moisture and plant growth dynamics

While plant litter is known to regulate soil moisture, little is known about the extent to which litter impacts moisture over and above the physical environment (i.e., ecosite) throughout the growing season, particularly in cool-temperate grasslands where moisture is considered less limiting for plant growth. In this study, we examined the relative impact of litter and ecosite on growing season soil moisture in a northern rough fescue (Festuca hallii) grassland. We also examined the relationship between litter and plant biomass throughout the growing season, including linkages between litter, plant growth, and the effects of litter on microclimate. During May, only ecosite was found to be associated with soil moisture, with a similar finding for plant biomass. Litter became important in maintaining greater soil moisture in June and July, however, likely through its corresponding negative impact on soil temperature and associated evaporation. In general, litter had a stronger and more consistent influence on soil moisture than ecosite. Finally, litter had a positive relationship with above-ground biomass, but only during June and July, the same months when litter exhibited the strongest relationship with soil moisture. Litter therefore appears to promote mid-season plant growth in these temperate grasslands, presumably through its ability to reduce evaporation and maintain greater soil water during seasonal moisture limitations.