Effects of experimental nitrogen deposition on soil organic carbon storage in Southern California drylands.

Atmospheric nitrogen (N) deposition is enriching soils with N across biomes. Soil N enrichment can increase plant productivity and affect microbial activity, thereby increasing soil organic carbon (SOC), but such responses vary across biomes. Drylands cover ~45% of Earth's land area and store ~33% of global SOC contained in the top 1 m of soil. Nitrogen fertilization could, therefore, disproportionately impact carbon (C) cycling, yet whether dryland SOC storage increases with N remains unclear. To understand how N enrichment may change SOC storage, we separated SOC into plant-derived, particulate organic C (POC), and largely microbially derived, mineral-associated organic C (MAOC) at four N deposition experimental sites in Southern California. Theory suggests that N enrichment increases the efficiency by which microbes build MAOC (C stabilization efficiency) if soil pH stays constant. But if soils acidify, a common response to N enrichment, then microbial biomass and enzymatic organic matter decay may decrease, increasing POC but not MAOC. We found that N enrichment had no effect on C fractions except for a decrease in MAOC at one site. Specifically, despite reported increases in plant biomass in three sites and decreases in microbial biomass and extracellular enzyme activities in two sites that acidified, POC did not increase. Furthermore, microbial C use and stabilization efficiency increased in a non-acidified site, but without increasing MAOC. Instead, MAOC decreased by 16% at one of the sites that acidified, likely because it lost 47% of the exchangeable calcium (Ca) relative to controls. Indeed, MAOC was strongly and positively affected by Ca, which directly and, through its positive effect on microbial biomass, explained 58% of variation in MAOC. Long-term effects of N fertilization on dryland SOC storage appear abiotic in nature, such that drylands where Ca-stabilization of SOC is prevalent and soils acidify, are most at risk for significant C loss.

Soil Heating in Fire (SheFire): A model and measurement method for estimating soil heating and effects during wildland fires.

Fire has transformative effects on soil biological, chemical, and physical properties in terrestrial ecosystems around the world. While methods for estimating fire characteristics and associated effects aboveground have progressed in recent decades, there remain major challenges in characterizing soil heating and associated effects belowground. Overcoming these challenges is crucial for understanding how fire influences soil carbon storage, biogeochemical cycling, and ecosystem recovery. In this paper, we present a novel framework for characterizing belowground heating and effects. The framework includes (1) an open-source model to estimate fire-driven soil heating, cooling, and the biotic effects of heating across depths and over time (Soil Heating in Fire model; SheFire) and (2) a simple field method for recording soil temperatures at multiple depths using self-contained temperature sensor and data loggers (i.e., iButtons), installed along a wooden stake inserted into the soil (i.e., an iStake). The iStake overcomes many logistical challenges associated with obtaining temperature profiles using thermocouples. Heating measurements provide inputs to the SheFire model, and modeled soil heating can then be used to derive ecosystem response functions, such as heating effects on microorganisms and tissues. To validate SheFire estimates, we conducted a burn table experiment using iStakes to record temperatures that were in turn used to fit the SheFire model. We then compared SheFire predicted temperatures against measured temperatures at other soil depths. To benchmark iStake measurements against those recorded by thermocouples, we co-located both types of sensors in the burn table experiment. We found that SheFire demonstrated skill in interpolating and extrapolating soil temperatures, with the largest errors occurring at the shallowest depths. We also found that iButton sensors are comparable to thermocouples for recording soil temperatures during fires. Finally, we present a case study using iStakes and SheFire to estimate in situ soil heating during a prescribed fire and demonstrate how observed heating regimes would influence seed and tree root vascular cambium survival at different soil depths. This measurement-modeling framework provides a cutting-edge approach for describing soil temperature regimes (i.e., soil heating) through a soil profile and predicting biological responses.

Reimagine fire science for the anthropocene.

Fire is an integral component of ecosystems globally and a tool that humans have harnessed for millennia. Altered fire regimes are a fundamental cause and consequence of global change, impacting people and the biophysical systems on which they depend. As part of the newly emerging Anthropocene, marked by human-caused climate change and radical changes to ecosystems, fire danger is increasing, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Increasing fire danger is a vexing problem that requires deep transdisciplinary, trans-sector, and inclusive partnerships to address. Here, we outline barriers and opportunities in the next generation of fire science and provide guidance for investment in future research. We synthesize insights needed to better address the long-standing challenges of innovation across disciplines to (i) promote coordinated research efforts; (ii) embrace different ways of knowing and knowledge generation; (iii) promote exploration of fundamental science; (iv) capitalize on the "firehose" of data for societal benefit; and (v) integrate human and natural systems into models across multiple scales. Fire science is thus at a critical transitional moment. We need to shift from observation and modeled representations of varying components of climate, people, vegetation, and fire to more integrative and predictive approaches that support pathways toward mitigating and adapting to our increasingly flammable world, including the utilization of fire for human safety and benefit. Only through overcoming institutional silos and accessing knowledge across diverse communities can we effectively undertake research that improves outcomes in our more fiery future.

Accounting for disturbance history in models: using remote sensing to constrain carbon and nitrogen pool spin-up.

Disturbances such as wildfire, insect outbreaks, and forest clearing, play an important role in regulating carbon, nitrogen, and hydrologic fluxes in terrestrial watersheds. Evaluating how watersheds respond to disturbance requires understanding mechanisms that interact over multiple spatial and temporal scales. Simulation modeling is a powerful tool for bridging these scales; however, model projections are limited by uncertainties in the initial state of plant carbon and nitrogen stores. Watershed models typically use one of two methods to initialize these stores: spin-up to steady state or remote sensing with allometric relationships. Spin-up involves running a model until vegetation reaches equilibrium based on climate. This approach assumes that vegetation across the watershed has reached maturity and is of uniform age, which fails to account for landscape heterogeneity and non-steady-state conditions. By contrast, remote sensing, can provide data for initializing such conditions. However, methods for assimilating remote sensing into model simulations can also be problematic. They often rely on empirical allometric relationships between a single vegetation variable and modeled carbon and nitrogen stores. Because allometric relationships are species- and region-specific, they do not account for the effects of local resource limitation, which can influence carbon allocation (to leaves, stems, roots, etc.). To address this problem, we developed a new initialization approach using the catchment-scale ecohydrologic model RHESSys. The new approach merges the mechanistic stability of spin-up with the spatial fidelity of remote sensing. It uses remote sensing to define spatially explicit targets for one or several vegetation state variables, such as leaf area index, across a watershed. The model then simulates the growth of carbon and nitrogen stores until the defined targets are met for all locations. We evaluated this approach in a mixed pine-dominated watershed in central Idaho, and a chaparral-dominated watershed in southern California. In the pine-dominated watershed, model estimates of carbon, nitrogen, and water fluxes varied among methods, while the target-driven method increased correspondence between observed and modeled streamflow. In the chaparral watershed, where vegetation was more homogeneously aged, there were no major differences among methods. Thus, in heterogeneous, disturbance-prone watersheds, the target-driven approach shows potential for improving biogeochemical projections.

Perspectives on disconnects between scientific information and management decisions on post-fire recovery in Western US.

Environmental regulations frequently mandate the use of "best available" science, but ensuring that it is used in decisions around the use and protection of natural resources is often challenging. In the Western US, this relationship between science and management is at the forefront of post-fire land management decisions. Recent fires, post-fire threats (e.g. flooding, erosion), and the role of fire in ecosystem health combine to make post-fire management highly visible and often controversial. This paper uses post-fire management to present a framework for understanding why disconnects between science and management decisions may occur. We argue that attributes of agencies, such as their political or financial incentives, can limit how effectively science is incorporated into decision-making. At the other end of the spectrum, the lack of synthesis or limited data in science can result in disconnects between science-based analysis of post-fire effects and agency policy and decisions. Disconnects also occur because of the interaction between the attributes of agencies and the attributes of science, such as their different spatial and temporal scales of interest. After offering examples of these disconnects in post-fire treatment, the paper concludes with recommendations to reduce disconnects by improving monitoring, increasing synthesis of scientific findings, and directing social-science research toward identifying and deepening understanding of these disconnects.