State changes: insights from the U.S. Long Term Ecological Research Network

Abstract

Understanding the complex and unpredictable ways ecosystems are changing and predicting the state of ecosystems and the services they will provide in the future requires coordinated, long-term research. This paper is a product of a U.S. National Science Foundation funded Long Term Ecological Research (LTER) network synthesis effort that addressed anticipated changes in future populations and communities. Each LTER site described what their site would look like in 50 or 100 yr based on long-term patterns and responses to global change drivers in each ecosystem. Common themes emerged and predictions were grouped into state change, connectivity, resilience, time lags, and cascading effects. Here, we report on the "state change" theme, which includes examples from the Georgia Coastal (coastal marsh), Konza Prairie (mesic grassland), Luquillo (tropical forest), Sevilleta (arid grassland), and Virginia Coastal (coastal grassland) sites. Ecological thresholds (the point at which small changes in an environmental driver can produce an abrupt and persistent state change in an ecosystem quality, property, or phenomenon) were most commonly predicted. For example, in coastal ecosystems, sea-level rise and climate change could convert salt marsh to mangroves and coastal barrier dunes to shrub thicket. Reduced fire frequency has converted grassland to shrubland in mesic prairie, whereas overgrazing combined with drought drive shrub encroachment in arid grasslands. Lastly, tropical cloud forests are susceptible to climate-induced changes in cloud base altitude leading to shifts in species distributions. Overall, these examples reveal that state change is a likely outcome of global environmental change across a diverse range of ecosystems and highlight the need for long-term studies to sort out the causes and consequences of state change. The diversity of sites within the LTER network facilitates the emergence of overarching concepts about state changes as an important driver of ecosystem structure, function, services, and futures.

Persistent decadal differences in plant communities assembled under contrasting climate conditions

“…The small change in plant community structure after 6 years of establishment suggests that differences in plant communities due to initial precipitation are not transient and may persist for longer than a decade. In native grasslands, changes in ecological drivers (e.g., reduced fire frequency) can result in state changes that take decades to emerge (Baer et al, 2020; Gaiser et al, 2020; Ratajczak et al, 2014; Zinnert et al, 2021). This study suggests that state changes may emerge faster in response to variations in ecological drivers that occur at the onset of community development.…”

Infrastructure to factorially manipulate the mean and variance of precipitation in the field

“…First, increasing climate variance can magnify the influence of environmental stochasticity, i.e., the aspects of climate events that are randomly determined and cannot be predicted precisely (Ridolfi et al, 2011). Second, greater variance can increase the frequency, magnitude, and/or duration of climate extremes that cause ecological tipping points, force transitions to new ecological states, slow the rate of recovery from disturbance, or alternatively, promote community or ecotone stability (Chesson, 2000; Doak & Morris, 2010; Lynch et al, 2014; Peters et al, 2006; Scheffer et al, 2015; Zinnert et al, 2021). Third, as climate variance increases, differences in climate between consecutive years become more dramatic, increasing the potential for antecedent effects, in which current biological responses depend on responses to past perturbations (Liu et al, 2019; Ogle et al, 2015; Wood et al, 2022).…”

Harnessing NEON to evaluate ecological tipping points: Opportunities, challenges, and approaches

“…At the time of this paper, a Web of Science search for “NEON” and ecological terms related to tipping points (e.g., “stable state” and “threshold”) did not return any results, indicating this opportunity to use NEON in relation to tipping points’ literature has yet to be fully realized. We believe this is largely due to the relatively recent establishment of NEON, and to a lesser degree the lack of explicit research agenda, as the NSF long‐term ecological research program (NSF‐LTER) has shown how other long‐term monitoring efforts can yield important insights about tipping points (Zinnert et al, 2021). In the hope of motivating research focused on tipping points and regime shifts using the resources of NEON, we briefly review several types of ecological transitions and then discuss the capacity, challenges, and strengths of NEON and NEON data to investigate such transitions.…”

“…Most critically, a number of synthesis studies (Bestelmeyer et al, 2011; Filbee‐Dexter et al, 2018; Ratajczak et al, 2018; Zinnert et al, 2021) have identified long‐term observational studies as a key need for identifying and exploring regime shifts and tipping point dynamics in ecosystems. With certain notable exceptions (including fast cycling planktonic communities or other microbial communities), many of the systems of greatest concern for having tipping points undergo shifts over month, year, or decadal timescales (Figure 2), and long‐term monitoring is the only way to capture major transitions and to assess their persistence (Zinnert et al, 2021). Tipping points also occur in complex systems with many connected components and potential drivers of shifts.…”