Amy J. Symstad

Functional diversity revealed by removal experiments

The dominant protocol to study the effects of plant diversity on ecosystem functioning has involved synthetically assembled communities, in which the experimental design determines species composition. By contrast, the composition of naturally assembled communities is determined by environmental filters, species recruitment and dispersal, and other assembly processes. Consequently, natural communities and ecosystems can differ from synthetic systems in their reaction to changes in diversity. Removal experiments, in which the diversity of naturally assembled communities is manipulated by removing various components, complement synthetic-assemblage experiments in exploring the relationship between diversity and ecosystem functioning. Results of recent removal experiments suggest that they are more useful for understanding the ecosystem effects of local, nonrandom extinctions, changes in the natural abundance of species, and complex interspecific interactions. This makes removal experiments a promising avenue for progress in ecological theory and an important source of information for those involved in making land-use and conservation decisions. Current extinction rates caused by human activities are orders of magnitude higher than natural background levels [1], and it is crucial that we understand the functional consequences of such extinctions. Terrestrial plants provide the basis for many fundamental ecosystem processes and services; therefore, many initiatives have been launched in the past decade to address this issue by documenting the possible effects of terrestrial plant diversity on ecosystem processes. Most of these studies are based on experiments using synthetic communities, in

Long-term and large-scale perspectives on the relationship between biodiversity and ecosystem functioning

Abstract In a growing body of literature from a variety of ecosystems is strong evidence that various components of biodiversity have significant impacts on ecosystem functioning. However, much of this evidence comes from short-term, small-scale experiments in which communities are synthesized from relatively small species pools and conditions are highly controlled. Extrapolation of the results of such experiments to longer time scales and larger spatial scales—those of whole ecosystems—is difficult because the experiments do not incorporate natural processes such as recruitment limitation and colonization of new species. We show how long-term study of planned and accidental changes in species richness and composition suggests that the effects of biodiversity on ecosystem functioning will vary over time and space. More important, we also highlight areas of uncertainty that need to be addressed through coordinated cross-scale and cross-site research.

Climate change and fire effects on a prairie-woodland ecotone: projecting species range shifts with a dynamic global vegetation model

Large shifts in species ranges have been predicted under future climate scenarios based primarily on niche-based species distribution models. However, the mechanisms that would cause such shifts are uncertain. Natural and anthropogenic fires have shaped the distributions of many plant species, but their effects have seldom been included in future projections of species ranges. Here, we examine how the combination of climate and fire influence historical and future distributions of the ponderosa pine–prairie ecotone at the edge of the Black Hills in South Dakota, USA, as simulated by MC1, a dynamic global vegetation model that includes the effects of fire, climate, and atmospheric CO2 concentration on vegetation dynamics. For this purpose, we parameterized MC1 for ponderosa pine in the Black Hills, designating the revised model as MC1-WCNP. Results show that fire frequency, as affected by humidity and temperature, is central to the simulation of historical prairies in the warmer lowlands versus woodlands in the cooler, moister highlands. Based on three downscaled general circulation model climate projections for the 21st century, we simulate greater frequencies of natural fire throughout the area due to substantial warming and, for two of the climate projections, lower relative humidity. However, established ponderosa pine forests are relatively fire resistant, and areas that were initially wooded remained so over the 21st century for most of our future climate x fire management scenarios. This result contrasts with projections for ponderosa pine based on climatic niches, which suggest that its suitable habitat in the Black Hills will be greatly diminished by the middle of the 21st century. We hypothesize that the differences between the future predictions from these two approaches are due in part to the inclusion of fire effects in MC1, and we highlight the importance of accounting for fire as managed by humans in assessing both historical species distributions and future climate change effects.

Precision, Repeatability, and Efficiency of Two Canopy-Cover Estimate Methods in Northern Great Plains Vegetation

Abstract Government agencies are subject to increasing public scrutiny of land management practices. Consequently, rigorous, yet efficient, monitoring protocols are needed to provide defensible quantitative data on the status and trends of rangeland vegetation. Rigor requires precise, repeatable measures, whereas efficiency requires the greatest possible information content for the amount of resources spent acquiring the information. We compared two methods—point frequency and visual estimate—of measuring canopy cover of individual plant species and groups of species (forbs vs. graminoids, native vs. nonnative) and plant species richness. These methods were compared in a variety of grassland vegetation types of the northern Great Plains for their precision, repeatability, and efficiency. Absolute precision of estimates was similar, but values generally differed between the two sampling methods. The point-frequency method yielded significantly higher values than the visual-estimate method for cover by individual species, graminoid cover, and total cover, and yielded significantly lower values for broadleaf (forb + shrub) cover and species richness. Differences in values derived by different sampling teams using the same method were similar between methods and within precision levels for many variables. Species richness and median species cover were the major exceptions; for these, the point-frequency method was far less repeatable. As performed in this study, the visual-estimate method required approximately twice the time as did the point-frequency method, but the former captured 55% more species. Overall, the visual-estimate method of measuring plant cover was more consistent among observers than anticipated, because of strong training, and captured considerably more species. However, its greater sampling time could reduce the number of samples and, therefore, reduce the statistical power of a sampling design if time is a limiting factor.

Incorporating Biodiversity Into Rangeland Health: Plant Species Richness and Diversity in Great Plains Grasslands

Abstract Indicators of rangeland health generally do not include a measure of biodiversity. Increasing attention to maintaining biodiversity in rangelands suggests that this omission should be reconsidered, and plant species richness and diversity are two metrics that may be useful and appropriate. Ideally, their response to a variety of anthropogenic and natural drivers in the ecosystem of interest would be clearly understood, thereby providing a means to diagnose the cause of decline in an ecosystem. Conceptual ecological models based on ecological principles and hypotheses provide a framework for this understanding, but these models must be supported by empirical evidence if they are to be used for decision making. To that end, we synthesize results from published studies regarding the responses of plant species richness and diversity to drivers that are of management concern in Great Plains grasslands, one of North Americas most imperiled ecosystems. In the published literature, moderate grazing generally has a positive effect on these metrics in tallgrass prairie and a neutral to negative effect in shortgrass prairie. The largest published effects on richness and diversity were caused by moderate grazing in tallgrass prairies and nitrogen fertilization in shortgrass prairies. Although weather is often cited as the reason for considerable annual fluctuations in richness and diversity, little information about the responses of these metrics to weather is available. Responses of the two metrics often diverged, reflecting differences in their sensitivity to different types of changes in the plant community. Although sufficient information has not yet been published for these metrics to meet all the criteria of a good indicator in Great Plains Grasslands, augmenting current methods of evaluating rangeland health with a measure of plant species richness would reduce these shortcomings and provide information critical to managing for biodiversity.

Vulnerability of Rehabilitated Agricultural Production Systems to Invasion by Nontarget Plant Species

Vast areas of arable land have been retired from crop production and “rehabilitated” to improved system states through landowner incentive programs in the United States (e.g., Conservation and Wetland Reserve Programs), as well as Europe (i.e., Agri-Environment Schemes). Our review of studies conducted on invasion of rehabilitated agricultural production systems by nontarget species elucidates several factors that may increase the vulnerability of these systems to invasion. These systems often exist in highly fragmented and agriculturally dominated landscapes, where propagule sources of target species for colonization may be limited, and are established under conditions where legacies of past disturbance persist and prevent target species from persisting. Furthermore, rehabilitation approaches often do not include or successfully attain all target species or historical ecological processes (e.g., hydrology, grazing, and/or fire cycles) key to resisting invasion. Uncertainty surrounds ways in which nontarget species may compromise long term goals of improving biodiversity and ecosystem services through rehabilitation efforts on former agricultural production lands. This review demonstrates that more studies are needed on the extent and ecological impacts of nontarget species as related to the goals of rehabilitation efforts to secure current and future environmental benefits arising from this widespread conservation practice.

A Two-Part Measure of Degree of Invasion for Cross-Community Comparisons

Invasibility is a critical feature of ecological communities, especially for management decisions. To date, invasibility has been measured in numerous ways. Although most researchers have used the richness (or number) of exotic species as a direct or indirect measure of community invasibility, others have used alternative measures such as the survival, density, or biomass of either a single or all exotic species. These different measures, even when obtained from the same communities, have produced inconsistent results and have made comparisons among communities difficult. Here, we propose a measure of the degree of invasion (DI) of a community as a surrogate for community invasibility. The measure is expressed as 2 independent components: exotic proportion of total species richness and exotic proportion of total species abundance (biomass or cover). By including richness and abundance, the measure reflects that the factors that control invasibility affect both of these components. Expressing exotic richness and abundance relative to the richness and abundance of all species in a community makes comparisons across communities of different sizes and resource availability possible and illustrates the importance of dominance of exotic species relative to natives, which is a primary management concern associated with exotic species.

Impacts of weather on long-term patterns of plant richness and diversity vary with location and management

Better understanding the influence of precipitation and temperature on plant assemblages is needed to predict the effects of climate change. Many studies have examined the relationship between plant productivity and weather (primarily precipitation), but few have directly assessed the relationship between plant richness or diversity and weather despite their increased use as metrics of ecosystem condition. We focus on the grasslands of central North America, which are characterized by high temporal climatic variability. Over the next 100 years, these grasslands are predicted to experience further increased variability in growing season precipitation, as well as increased temperatures, due to global climate change. We assess the portion of interannual variability of richness and diversity explained by weather, how relationships between these metrics and weather vary among plant assemblages, and which aspects of weather best explain temporal variability. We used an information-theoretic approach to assess relationships between long-term plant richness and diversity patterns and a priori weather covariates using six data sets from four grasslands. Weather explained up to 49% and 63% of interannual variability in total plant species richness and diversity, respectively. However, richness and diversity responses to specific weather variables varied both among sites and among experimental treatments within sites. In general, we found many instances in which temperature was of equal or greater importance as precipitation, as well as evidence of the importance of lagged effects and precipitation or temperature variability. Although precipitation has been shown to be a key driver of productivity in grasslands, our results indicate that increasing temperatures alone, without substantial changes in precipitation patterns, could have measurable effects on Great Plains grassland plant assemblages and biodiversity metrics. Our results also suggest that richness and diversity will respond in unique ways to changing climate and management can affect these responses; additional research and monitoring will be essential for further understanding of these complex relationships.

Using natural range of variation to set decision thresholds: a case study for great plains grasslands

Natural range of variation (NRV) may be used to establish decision thresholds or action assessment points when ecological thresholds are either unknown or do not exist for attributes of interest in a managed ecosystem. The process for estimating NRV involves identifying spatial and temporal scales that adequately capture the heterogeneity of the ecosystem; compiling data for the attributes of interest via study of historic records, analysis and interpretation of proxy records, modeling, space-for-time substitutions, or analysis of long-term monitoring data; and quantifying the NRV from those data. At least 19 National Park Service (NPS) units in North America’s Great Plains are monitoring plant species richness and evenness as indicators of vegetation integrity in native grasslands, but little information on natural, temporal variability of these indicators is available. In this case study, we use six long-term vegetation monitoring datasets to quantify the temporal variability of these attributes in reference conditions for a variety of Great Plains grassland types, and then illustrate the implications of using different NRVs based on these quantities for setting management decision thresholds. Temporal variability of richness (as measured by the coefficient of variation, CV) is fairly consistent across the wide variety of conditions occurring in Colorado shortgrass prairie to Minnesota tallgrass sand savanna (CV 0.20–0.45) and generally less than that of production at the same sites. Temporal variability of evenness spans a greater range of CV than richness, and it is greater than that of production in some sites but less in other sites. This natural temporal variability may mask undesirable changes in Great Plains grasslands vegetation. Consequently, we suggest that managers consider using a relatively narrow NRV (interquartile range of all richness or evenness values observed in reference conditions) for designating a surveillance threshold, at which greater attention to the situation would be paid, and a broader NRV for designating management thresholds, at which action would be instigated.