Geology topics

Jayne L. Jonas

Publications and source records attributed to Jayne L. Jonas.

3 recordsLinked to original sources

USGS2023

Identifying predictors of translocation success in rare plant species

The fundamental goal of a rare plant translocation is to create self-sustaining populations with the evolutionary resilience to persist in the long-term. Yet most plant translocation syntheses focus on a few factors influencing short-term benchmarks of success (e.g., survival and reproduction). Short-term benchmarks can be misleading when trying to infer future growth and viability because the factors that promote establishment may differ from those required for long-term persistence. We assembled a large ( n = 275) and broadly representative dataset of well-documented and monitored (7.9 years on average) at-risk plant translocations to identify the most important site attributes, management techniques, and species traits for six life-cycle benchmarks and population metrics of translocation success. Using the random forest algorithm, we found that drivers of translocation outcomes varied across timeframes and metrics of success. Management techniques had the greatest relative influence on the attainment of life-cycle benchmarks and short-term population trends while site attributes and species traits were more important for population persistence and longer-term trends. Specifically, large founder sizes increased the potential for reproduction and recruitment into the next generation, while declining habitat quality and the outplanting of species with low seed production led to increased extinction risks and a reduction in potential reproductive output in the long-term, respectively. We also detected novel interactions between some of the most important drivers, such as an increased probability of next-generation recruitment in species with greater seed production rates, but only when coupled with large founder sizes. Since most significant barriers to plant translocation success can be overcome by improving techniques or resolving site-level issues through early intervention and management, we suggest that by combining long-term monitoring with adaptive management, translocation programs can enhance the prospects of achieving long-term success.

Conservation Biology↗

USGS2015

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 1) the portion of interannual variability of richness and diversity explained by weather, 2) how relationships between these metrics and weather vary among plant assemblages, and 3) 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 datasets 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. Read More: http://www.esajournals.org/doi/abs/10.1890/14-1989.1

Colorado, Kansas, Minnesota↗

USGS2014

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.

Book chapter↗