Emily Kachergis

Predicted responses of arctic and alpine ecosystems to altered seasonality under climate change

Global climate change is already having significant impacts on arctic and alpine ecosystems, and ongoing increases in temperature and altered precipitation patterns will affect the strong seasonal patterns that characterize these temperature-limited systems. The length of the potential growing season in these tundra environments is increasing due to warmer temperatures and earlier spring snow melt. Here, we compare current and projected climate and ecological data from 20 Northern Hemisphere sites to identify how seasonal changes in the physical environment due to climate change will alter the seasonality of arctic and alpine ecosystems. We find that although arctic and alpine ecosystems appear similar under historical climate conditions, climate change will lead to divergent responses, particularly in the spring and fall shoulder seasons. As seasonality changes in the Arctic, plants will advance the timing of spring phenological events, which could increase plant nutrient uptake, production, and ecosystem carbon (C) gain. In alpine regions, photoperiod will constrain spring plant phenology, limiting the extent to which the growing season can lengthen, especially if decreased water availability from earlier snow melt and warmer summer temperatures lead to earlier senescence. The result could be a shorter growing season with decreased production and increased nutrient loss. These contrasting alpine and arctic ecosystem responses will have cascading effects on ecosystems, affecting community structure, biotic interactions, and biogeochemistry.

Using Participatory Workshops to Integrate State-and-Transition Models Created With Local Knowledge and Ecological Data

Abstract State-and-transition models (STMs) depict current understanding of vegetation dynamics and are being created for most ecological sites in the United States. Model creation is challenging due to inadequate long-term data, and most STMs rely on expert knowledge. There has been little systematic documentation of how different types of knowledge have been integrated in STMs, or what these distinct knowledge sources offer. We report on a series of participatory workshops where stakeholders helped to integrate STMs developed for the same region using local knowledge and ecological field data. With this exploratory project, we seek to understand what kinds of information local knowledge and ecological field data can provide to STMs, assess workshops as a method of integrating knowledge and evaluate how different stakeholders perceive models created with different types of knowledge. Our analysis is based on meeting notes, comments on draft models, and workshop evaluation questionnaires. We conclude that local knowledge and ecological data can complement one another, providing different types of information at different spatial and temporal scales. Participants reported that the workshop increased their knowledge of STMs and vegetation dynamics, suggesting that engaging potential model users in developing STMs is an effective outreach and education approach. Agency representatives and ranchers expressed the value of both the local knowledge and data-driven models. Agency participants were likely to critique or add components based on monitoring data or prior research, and ranchers were more likely to add states and transitions based on personal experience. As STM development continues, it is critical that range professionals think systematically about what different forms of data might contribute to model development, how we can best integrate existing knowledge and data to create credible and useful models, and how to validate the resulting STMs.

Conservation Program Participation and Adaptive Rangeland Decision-Making

Abstract This paper analyzes rancher participation in conservation programs in the context of a social-ecological framework for adaptive rangeland decision-making. We argue that conservation programs are best understood as one of many strategies of adaptively managing rangelands in ways that sustain livelihoods and ecosystem services. The framework hypothesizes four categories of variables affecting conservation program participation: operation/operator characteristics, time horizon, social network connections, and social values. Based on a mail survey of California ranchers, multinomial logit models are used to estimate the impact of these variables on different levels of rancher involvement in conservation programs. The findings suggest that ranchers with larger amounts of land, an orientation towards the future, and who are opinion leaders with access to conservation information, are more likely to participate in conservation programs.

Tools for Resilience Management: Multidisciplinary Development of State-and-Transition Models for Northwest Colorado

Building models is an important way of integrating knowledge. Testing and updating models of social-ecological systems can inform management decisions and, ultimately, improve resilience. We report on the outcomes of a six-year, multidisciplinary model development process in the sagebrush steppe, USA. We focused on creating state-and-transition models (STMs), conceptual models of ecosystem change that represent nonlinear dynamics and are being adopted worldwide as tools for managing ecosystems. STM development occurred in four steps with four distinct sets of models: (1) local knowledge elicitation using semistructured interviews; (2) ecological data collection using an observational study; (3) model integration using participatory workshops; and (4) model simplification upon review of the literature by a multidisciplinary team. We found that different knowledge types are ultimately complementary. Many of the benefits of the STM-building process flowed from the knowledge integration steps, including improved communication, identification of uncertainties, and production of more broadly credible STMs that can be applied in diverse situations. The STM development process also generated hypotheses about sagebrush steppe dynamics that could be tested by future adaptive management and research. We conclude that multidisciplinary development of STMs has great potential for producing credible, useful tools for managing resilience of social-ecological systems. Based on this experience, we outline a streamlined, participatory STM development process that integrates multiple types of knowledge and incorporates adaptive management.

Indicators of ecosystem function identify alternate states in the sagebrush steppe

Models of ecosystem change that incorporate nonlinear dynamics and thresholds, such as state-and-transition models (STMs), are increasingly popular tools for land management decision-making. However, few models are based on systematic collection and documentation of ecological data, and of these, most rely solely on structural indicators (species composition) to identify states and transitions. As STMs are adopted as an assessment framework throughout the United States, finding effective and efficient ways to create data-driven models that integrate ecosystem function and structure is vital. This study aims to (1) evaluate the utility of functional indicators (indicators of rangeland health, IRH) as proxies for more difficult ecosystem function measurements and (2) create a data-driven STM for the sagebrush steppe of Colorado, USA, that incorporates both ecosystem structure and function. We sampled soils, plant communities, and IRH at 41 plots with similar clayey soils but different site histories to identify potential states and infer the effects of management practices and disturbances on transitions. We found that many IRH were correlated with quantitative measures of functional indicators, suggesting that the IRH can be used to approximate ecosystem function. In addition to a reference state that functions as expected for this soil type, we identified four biotically and functionally distinct potential states, consistent with the theoretical concept of alternate states. Three potential states were related to management practices (chemical and mechanical shrub treatments and seeding history) while one was related only to ecosystem processes (erosion). IRH and potential states were also related to environmental variation (slope, soil texture), suggesting that there are environmental factors within areas with similar soils that affect ecosystem dynamics and should be noted within STMs. Our approach generated an objective, data-driven model of ecosystem dynamics for rangeland management. Our findings suggest that the IRH approximate ecosystem processes and can distinguish between alternate states and communities and identify transitions when building data-driven STMs. Functional indicators are a simple, efficient way to create data-driven models that are consistent with alternate state theory. Managers can use them to improve current model-building methods and thus apply state-and-transition models more broadly for land management decision-making.

Differences in Plant Species Composition as Evidence of Alternate States in the Sagebrush Steppe

Abstract State-and-transition models (STMs), conceptual models of vegetation change based on alternate state theory, are increasingly applied as tools for land management decision-making. As STMs are created throughout the United States, it is crucial to ensure that they are supported by ecological evidence. Plant species composition reflects ecosystem processes that are difficult to measure and may be a useful indicator of alternate states. This study aims to create data-driven STMs based on plant species composition for two ecological sites (Claypan and Mountain Loam) in northwestern Colorado sagebrush steppe. We sampled 76 plots with different management and disturbance histories. Drawing on the hierarchical approach currently taken to build STMs, we hypothesized that A) differences in species composition between the two ecological sites would be related to environmental factors and B) differences in species composition within each ecological site would be related to management and disturbance history. Relationships among species composition, site history, and environmental variables were evaluated using multivariate statistics. We found that between ecological sites, species composition was related to differences in soil texture, supporting Hypothesis A and the creation of separate STMs for each site. Within ecological sites, species composition was related to site history and also to environmental variation. This finding partially supports Hypothesis B and the identification of alternate states using species composition, but also suggests that these ecological sites are not uniform physical templates upon which plant community dynamics play out. This data-driven, plant species–based approach created two objective, credible STMs with states and transitions that are consistent with the sagebrush steppe literature. Our findings support the hierarchical view of landscapes currently applied in building STMs. An approach that acknowledges environmental heterogeneity within ecological sites is necessary to help define finer-resolution ecological sites and elucidate cases in which specific abiotic conditions make transitions between states more likely. Resumen Los Modelos de Estado y Transición (MET), que son modelos conceptuales en cambios de la vegetación basados la teoría del estado alternativo, su aplicación está en aumento como herramienta para la tomada de decisiones en el manejo de la tierra. Como los MET se han creado a través de los Estados Unidos, es vital que aseguremos que estos están apoyados por evidencia ecológica. La composición de especies refleja el proceso del ecosistema que es difícil de medir y podría ser un indicador útil de estados alternativos. Este estudio ayuda a crear un MET dirigido por datos basado en las composición de especies de plantas de dos sitios ecológicos (Claypan y Mountain Loam) en la estepa de artemisa al noroeste de de Colorado. Muestramos 76 parcelas con diferente manejo e historias de disturbio. Dibujando el concepto jerárquico actualmente usado para construir los MET, establecimos las siguientes hipótesis A) Las diferencias en la composición de especies entre los dos sitios ecológicos podrían estar relacionadas a factores medioambientales y B) las diferencias en la composición de especies dentro de cada sitio ecológicos podrían estar relacionadas por el manejo y la historia de disturbio. Las relaciones entre la composición de especies, la historia del sitio y las variables medioambientales fueron evaluadas usando estadística multivariada. Encontramos que entre sitios ecológicos, la composición de especies estuvo relacionada con las diferentes texturas del suelo, apoyando la Hipotesis A y la creación de MET separados. Dentro de los sitios ecológicos, la composición de especies estuvo relacionada a la historia del sitio y también a variables medioambientales. Estos resultados apoyan parcialmente la Hipotesis B y la identificación de estados alternativos usando la composición de especies, pero también sugieren que estos sitios ecológicos no son uniformes en la plantilla física que es donde la dinámica de la comunidad vegetal se desenvuelve. Este concepto basado en datos dirigidos en especies de plantas creo dos objetivos, creíbles MET con estados y transiciones que son consistentes con la literatura de la estepa de artemisa. Nuestros resultados apoyan el punto de vista jerárquico de paisajes que se usan actualmente para construir METs. Un enfoque que reconoce la heterogeneidad medioambiental dentro de sitios ecológicos es necesaria para ayudar a definir mejor resolución de sitios ecológicos y aclarar casos donde condiciones abióticas especificas hacen la transición mas probable.

Sustaining Working Rangelands: Insights from Rancher Decision Making☆

ABSTRACT Grazed rangeland ecosystems encompass diverse global land resources and are complex social-ecological systems from which society demands both goods (e.g., livestock and forage production) and services (e.g., abundant and high-quality water). Including the ranching communitys perceptions, knowledge, and decision-making is essential to advancing the ongoing dialogue to define sustainable working rangelands. We surveyed 507 (33% response rate) California ranchers to gain insight into key factors shaping their decision-making, perspectives on effective management practices and ranching information sources, as well as their concerns. First, we found that variation in ranch structure, management goals, and decision making across Californias ranching operations aligns with the call from sustainability science to maintain flexibility at multiple scales to support the suite of economic and ecological services they can provide. The diversity in ranching operations highlights why single-policy and management “panaceas” often fail. Second, the information resources ranchers rely on suggest that sustaining working rangelands will require collaborative, trust-based partnerships focused on achieving both economic and ecological goals. Third, ranchers perceive environmental regulations and government policies—rather than environmental drivers—as the major threats to the future of their operations.

Enhancing Wind Erosion Monitoring and Assessment for U.S. Rangelands

On the Ground Wind erosion is a major resource concern for rangeland managers because it can impact soil health, ecosystem structure and function, hydrologic processes, agricultural production, and air quality. Despite its significance, little is known about which landscapes are eroding, by how much, and when. The National Wind Erosion Research Network was established in 2014 to develop tools for monitoring and assessing wind erosion and dust emissions across the United States. The Network, currently consisting of 13 sites, creates opportunities to enhance existing rangeland soil, vegetation, and air quality monitoring programs. Decision-support tools developed by the Network will improve the prediction and management of wind erosion across rangeland ecosystems.

Using State and Transition Models to Show Economic Interdependence of Ecological Sites at the Ranch Level

ABSTRACT US government agencies are adopting state and transition models (STMs) for rangeland evaluation, monitoring, and management. This research demonstrates advantages of combining STMs and ranch economic models. A dynamic optimization framework casts management decisions—stocking rates and brush control—in the context of ranch profitability over a suite of ecological sites. Markov processes characterize the likelihood of state transitions. The ranch model shows economic interdependence of multiple ecological sites. Ecological site combinations producing the most forage are not the most economically advantageous. The state of one ecological site influences the forage value elsewhere and ultimately the intensity at which a ranch is stocked. Likewise, brush control benefits depend importantly on the state of all ecological sites.

Critical Evaluations of Vegetation Cover Measurement Techniques: A Response to Thacker et al. (2015)

On The Ground Method comparison studies are necessary to reconcile monitoring methods that have arisen among disparate programs; however, we find that Thacker et al.s study comparing Daubenmire frame (DF) and line-point intercept (LPI) methods for estimating vegetation cover is not adequate to support their conclusions. Because the DF and LPI methods estimate different aspects of vegetation cover (total canopy vs. foliar cover), there should be no a priori expectation that the two techniques would produce the same results. Thacker et al. omit critical information about their methods (sampling design, training and calibration, indicator calculations) that could have a large impact on their results and how they can be interpreted. Differences in results between different vegetation cover measurement techniques can also be attributable to factors like observer training and calibration, plot heterogeneity and complexity, spatial distribution of vegetation, plant morphology, and plot size; thus it is difficult to draw strong conclusions froma single study. Rather than implementing both DF and LPI techniques in sage-grouse studies as Thacker et al. recommend, effort should instead be invested in ensuring that sampling for one selected method is adequate. Critical evaluations of vegetation measurement methods to advance the science of rangeland monitoring should be conducted and reported in a rigorous manner, provide a thorough review of previous studies, and discuss how new results contribute to existing knowledge.