General reversal of N-decomposition relationship during long-term decomposition in boreal and temperate forests.

Decomposition of dead organic matter is fundamental to carbon (C) and nutrient cycling in terrestrial ecosystems, influencing C fluxes from the biosphere to the atmosphere. Theory predicts and evidence strongly supports that the availability of nitrogen (N) limits litter decomposition. Positive relationships between substrate N concentrations and decomposition have been embedded into ecosystem models. This decomposition paradigm, however, relies on data mostly from short-term studies analyzing controls on early-stage decomposition. We present evidence from three independent long-term decomposition investigations demonstrating that the positive N-decomposition relationship is reversed and becomes negative during later stages of decomposition. First, in a 10-y decomposition experiment across 62 woody species in a temperate forest, leaf litter with higher N concentrations exhibited faster initial decomposition rates but ended up a larger recalcitrant fraction decomposing at a near-zero rate. Second, in a 5-y N-enrichment experiment of two tree species, leaves with experimentally enriched N concentrations had faster decomposition initial rates but ultimately accumulated large slowly decomposing fractions. Measures of amino sugars on harvested litter in two experiments indicated that greater accumulation of microbial residues in N-rich substrates likely contributed to larger slowly decomposing fractions. Finally, a database of 437 measurements from 120 species in 45 boreal and temperate forest sites confirmed that higher N concentrations were associated with a larger slowly decomposing fraction. These results challenge the current treatment of interactions between N and decomposition in many ecosystems and Earth system models and suggest that even the best-supported short-term controls of biogeochemical processes might not predict long-term controls.

Frequent and strong cold-air pooling drives temperate forest composition.

Cold-air pooling is an important topoclimatic process that creates temperature inversions with the coldest air at the lowest elevations. Incomplete understanding of sub-canopy spatiotemporal cold-air pooling dynamics and associated ecological impacts hinders predictions and conservation actions related to climate change and cold-dependent species and functions. To determine if and how cold-air pooling influences forest composition, we characterized the frequency, strength, and temporal dynamics of cold-air pooling in the sub-canopy at local to regional scales in New England, USA. We established a network of 48 plots along elevational transects and continuously measured sub-canopy air temperatures for 6-10 months (depending on site). We then estimated overstory and understory community temperature preferences by surveying tree composition in each plot and combining these data with known species temperature preferences. We found that cold-air pooling was frequent (19-43% seasonal occurrences) and that sites with the most frequent inversions displayed inverted forest composition patterns across slopes with more cold-adapted species, namely conifers, at low instead of high elevations. We also observed both local and regional variability in cold-air pooling dynamics, revealing that while cold-air pooling is common, it is also spatially complex. Our study, which uniquely focused on broad spatial and temporal scales, has revealed some rarely reported cold-air pooling dynamics. For instance, we discovered frequent and strong temperature inversions that occurred across seasons and in some locations were most frequent during the daytime, likely affecting forest composition. Together, our results show that cold-air pooling is a fundamental ecological process that requires integration into modeling efforts predicting future forest vegetation patterns under climate change, as well as greater consideration for conservation strategies identifying potential climate refugia for cold-adapted species.

Nitrous oxide emissions are driven by environmental conditions rather than nitrogen application methods in a perennial hayfield.

Agricultural best management practices (BMPs) intended to solve one environmental challenge may have unintended climate impacts. For example, manure injection is often promoted for its potential to reduce runoff and nitrogen (N) loss as NH3 , but the practice has been shown to increase N2 O, a powerful greenhouse gas, compared to surface application. Urease inhibitor application with N fertilizer is another BMP that can enhance N retention by reducing NH3 emissions, but its impact on N2 O emissions is mixed. Thus, we measured N2 O, CO2 , soil mineral N availability, soil moisture, soil temperature, and yield in a 2-year perennial hayfield trial with four fertilization treatments (manure injection, manure broadcast, synthetic urea, and control) applied with or without a urease inhibitor in Alburgh, VT. We used linear models to examine treatment effects on daily and cumulative N2 O emissions and a boosted regression tree (BRT) model to identify the most important drivers of daily N2 O fluxes in our trial. While fertilization type had a significant impact on N2 O fluxes (p < 0.05), our treatments explained an unexpectedly small amount of the variation in emissions (R2  = 0.042), and urease inhibitor had no effect. Instead, soil moisture was the most important predictor of daily N2 O fluxes (39.7% relative influence in BRT model), followed by CO2 fluxes, soil inorganic N, and soil temperature. Soil moisture and temperature interacted to produce the largest daily N2 O fluxes when both were relatively high, suggesting that injecting manure during dry periods or during wet but cool periods could reduce its climate impacts.

Termite sensitivity to temperature affects global wood decay rates.

Deadwood is a large global carbon store with its store size partially determined by biotic decay. Microbial wood decay rates are known to respond to changing temperature and precipitation. Termites are also important decomposers in the tropics but are less well studied. An understanding of their climate sensitivities is needed to estimate climate change effects on wood carbon pools. Using data from 133 sites spanning six continents, we found that termite wood discovery and consumption were highly sensitive to temperature (with decay increasing >6.8 times per 10°C increase in temperature)-even more so than microbes. Termite decay effects were greatest in tropical seasonal forests, tropical savannas, and subtropical deserts. With tropicalization (i.e., warming shifts to tropical climates), termite wood decay will likely increase as termites access more of Earth's surface.

Cold-air pools as microrefugia for ecosystem functions in the face of climate change.

Cold-air pooling is a global phenomenon that frequently sustains low temperatures in sheltered, low-lying depressions and valleys and drives other key environmental conditions, such as soil temperature, soil moisture, vapor pressure deficit, frost frequency, and winter dynamics. Local climate patterns in areas prone to cold-air pooling are partly decoupled from regional climates and thus may be buffered from macroscale climate change. There is compelling evidence from studies across the globe that cold-air pooling impacts plant communities and species distributions, making these decoupled microclimate areas potentially important microrefugia for species under climate warming. Despite interest in the potential for cold-air pools to enable species persistence under warming, studies investigating the effects of cold-air pooling on ecosystem processes are scarce. Because local temperatures and vegetation composition are critical drivers of ecosystem processes like carbon cycling and storage, cold-air pooling may also act to preserve ecosystem functions. We review research exploring the ecological impacts of cold-air pooling with a focus on vegetation, and then present a new conceptual framework in which cold-air pooling creates feedbacks between species and ecosystem properties that generate unique hotspots for carbon accrual in some systems relative to areas more vulnerable to regional climate change impacts. Finally, we describe key steps to motivate future research investigating the potential for cold-air pools to serve as microrefugia for ecosystem functions under climate change.

Benefits and tradeoffs of reduced tillage and manure application methods in a Zea mays silage system.

A critical question is whether there are agricultural management practices that can attain the multiple management goals of increasing yields, preventing nutrient losses, and suppressing greenhouse gas (GHG) emissions. No-till and manure application methods, such as manure injection, can enhance nutrient retention, but both may also enhance emissions of nitrous oxide (N2 O), a powerful GHG. We assessed differences in soil N2 O and carbon dioxide (CO2 ) emissions, nitrate and ammonium retention, and crop yield and protein content under combinations of vertical-till, no-till, manure injection, and manure broadcast without incorporation in a corn (Zea mays L.) silage system. During the growing seasons of 2015-2017, GHG emissions and soil mineral nitrogen (N) were measured every other week or more frequently after management events. Crop yield and protein content were measured annually at harvest. No-till reduced CO2 emissions but had no impact on N2 O emissions relative to vertical-till. Manure injection increased N2 O and CO2 emissions, with the magnitude of this effect being greatest for 1 mo post-application. Manure injection also increased soil ammonium and nitrate but did not increase yield or crop quality relative to broadcast application. Similarly, tillage did not affect crop yield or protein content. Despite the tradeoffs between mineral N retention and elevated GHG emissions, manure injection in no-till systems benefits farmers by reducing soil carbon losses as CO2 , retaining mineral N, and maintaining crop yields and quality.

Estimating litter decomposition rate in single-pool models using nonlinear beta regression.

Litter decomposition rate (k) is typically estimated from proportional litter mass loss data using models that assume constant, normally distributed errors. However, such data often show non-normal errors with reduced variance near bounds (0 or 1), potentially leading to biased k estimates. We compared the performance of nonlinear regression using the beta distribution, which is well-suited to bounded data and this type of heteroscedasticity, to standard nonlinear regression (normal errors) on simulated and real litter decomposition data. Although the beta model often provided better fits to the simulated data (based on the corrected Akaike Information Criterion, AIC(c)), standard nonlinear regression was robust to violation of homoscedasticity and gave equally or more accurate k estimates as nonlinear beta regression. Our simulation results also suggest that k estimates will be most accurate when study length captures mid to late stage decomposition (50-80% mass loss) and the number of measurements through time is ≥ 5. Regression method and data transformation choices had the smallest impact on k estimates during mid and late stage decomposition. Estimates of k were more variable among methods and generally less accurate during early and end stage decomposition. With real data, neither model was predominately best; in most cases the models were indistinguishable based on AIC(c), and gave similar k estimates. However, when decomposition rates were high, normal and beta model k estimates often diverged substantially. Therefore, we recommend a pragmatic approach where both models are compared and the best is selected for a given data set. Alternatively, both models may be used via model averaging to develop weighted parameter estimates. We provide code to perform nonlinear beta regression with freely available software.

A global synthesis reveals biodiversity loss as a major driver of ecosystem change.

Evidence is mounting that extinctions are altering key processes important to the productivity and sustainability of Earth's ecosystems. Further species loss will accelerate change in ecosystem processes, but it is unclear how these effects compare to the direct effects of other forms of environmental change that are both driving diversity loss and altering ecosystem function. Here we use a suite of meta-analyses of published data to show that the effects of species loss on productivity and decomposition--two processes important in all ecosystems--are of comparable magnitude to the effects of many other global environmental changes. In experiments, intermediate levels of species loss (21-40%) reduced plant production by 5-10%, comparable to previously documented effects of ultraviolet radiation and climate warming. Higher levels of extinction (41-60%) had effects rivalling those of ozone, acidification, elevated CO(2) and nutrient pollution. At intermediate levels, species loss generally had equal or greater effects on decomposition than did elevated CO(2) and nitrogen addition. The identity of species lost also had a large effect on changes in productivity and decomposition, generating a wide range of plausible outcomes for extinction. Despite the need for more studies on interactive effects of diversity loss and environmental changes, our analyses clearly show that the ecosystem consequences of local species loss are as quantitatively significant as the direct effects of several global change stressors that have mobilized major international concern and remediation efforts.

Single-pool exponential decomposition models: potential pitfalls in their use in ecological studies.

The importance of litter decomposition to carbon and nutrient cycling has motivated substantial research. Commonly, researchers fit a single-pool negative exponential model to data to estimate a decomposition rate (k). We review recent decomposition research, use data simulations, and analyze real data to show that this practice has several potential pitfalls. Specifically, two common decisions regarding model form (how to model initial mass) and data transformation (log-transformed vs. untransformed data) can lead to erroneous estimates of k. Allowing initial mass to differ from its true, measured value resulted in substantial over- or underestimation of k. Log-transforming data to estimate k using linear regression led to inaccurate estimates unless errors were lognormally distributed, while nonlinear regression of untransformed data accurately estimated k regardless of error structure. Therefore, we recommend fixing initial mass at the measured value and estimating k with nonlinear regression (untransformed data) unless errors are demonstrably lognormal. If data are log-transformed for linear regression, zero values should be treated as missing data; replacing zero values with an arbitrarily small value yielded poor k estimates. These recommendations will lead to more accurate k estimates and allow cross-study comparison of k values, increasing understanding of this important ecosystem process.

Global-scale similarities in nitrogen release patterns during long-term decomposition.

Litter decomposition provides the primary source of mineral nitrogen (N) for biological activity in most terrestrial ecosystems. A 10-year decomposition experiment in 21 sites from seven biomes found that net N release from leaf litter is dominantly driven by the initial tissue N concentration and mass remaining regardless of climate, edaphic conditions, or biota. Arid grasslands exposed to high ultraviolet radiation were an exception, where net N release was insensitive to initial N. Roots released N linearly with decomposition and exhibited little net N immobilization. We suggest that fundamental constraints on decomposer physiologies lead to predictable global-scale patterns in net N release during decomposition.

Patterns of nitrogen accumulation and cycling in riparian floodplain ecosystems along the Green and Yampa rivers.

Patterns of nitrogen (N) accumulation and turnover in riparian systems in semi-arid regions are poorly understood, particularly in those ecosystems that lack substantial inputs from nitrogen fixing vegetation. We investigated sources and fluxes of N in chronosequences of riparian forests along the regulated Green River and the free-flowing Yampa River in semi-arid northwestern Colorado. Both rivers lack significant inputs from N-fixing vegetation. Total soil nitrogen increased through time along both rivers, at a rate of about 7.8 g N m(-2) year(-1) for years 10-70, and 2.7 g N m(-2)year(-1) from years 70-170. We found that the concentration of N in freshly deposited sediments could account for most of the soil N that accumulated in these floodplain soils. Available N (measured by ion exchange resin bags) increased with age along both rivers, more than doubling in 150 years. In contrast to the similar levels of total soil N along these rivers, N turnover rates, annual N mineralization, net nitrification rates, resin-N, and foliar N were all 2-4 times higher along the Green River than the Yampa River. N mineralization and net nitrification rates generally increased through time to steady or slightly declining rates along the Yampa River. Along the Green River, rates of mineralization and nitrification were highest in the youngest age class. The high levels of available N and N turnover in young sites are not characteristic of riparian chronosequences and could be related to changes in hydrology or plant community composition associated with the regulation of the Green River.