Understanding the relationship between precipitation (PPT) and aboveground net primary productivity (ANPP) is essential for modeling the global carbon cycle. Across grassland to forest gradients, the PPT-ANPP relationship is well defined and nonlinear. Temporal patterns within a site over time are more variable and nearly always linear. Linear relationships, however, are inconsistent with positive asymmetry, where increases in ANPP during wet years exceed declines in dry years. The double asymmetry model predicts that concave-down nonlinearities will occur when extreme high and low PPT years are included in a time series. We tested this prediction using long-term observational ANPP data along with rainfall manipulation experiments. By combining observational records with experimental treatments, including drought, water addition, and nitrogen addition, we found some support for the double asymmetry model. However, the response under high precipitation coupled with nitrogen addition was concave-up, not down. By experimentally extending the range of monsoon precipitation, we found a weak but significant, nonlinear PPT-ANPP relationship, but only when nutrient limitation was alleviated. Our results demonstrate that multiple interacting factors govern the PPT-ANPP relationship within a site over time, challenging our ability to predict how ANPP will respond to changes in precipitation in the future.

Dryland productivity is highly sensitive to precipitation variability, and models predict that rainfall variability will increase in the future. Numerous studies have documented the relationship between productivity and precipitation, but most focus on aboveground production (ANPP), while the effects on belowground production (BNPP) remain poorly understood. Furthermore, previous research suggests that ANPP and BNPP are uncoupled within ecosystems, but the degree to which rainfall variability affects the interplay between aboveground and belowground production is unknown. We conducted a long-term rainfall manipulation experiment in Chihuahuan Desert grassland to investigate how the size and frequency of growing season rain events affected BNPP and its relationship to ANPP. Experimental plots received either 12 small-frequent rain events or 3 large-infrequent events during the monsoon season for a total of 60 mm of added rainfall per treatment per year. All plots, including three controls, received ambient rainfall throughout the year. Total BNPP ranged from a low of 94.7 ± 38.2 g m2 year-1 under ambient conditions to a high of 183.7 ± 44.6 g m2 year-1 under the small-frequent rainfall treatment. Total BNPP was highest under small-frequent rain events, and there was no difference in BNPP between 0-15 and 15-30 cm soil depths in either rainfall treatment. ANPP and BNPP were uncorrelated within rainfall treatments, but weakly positively correlated across all plots and years. Our results contribute to a growing body of research on the importance of small rain events in drylands and provide further evidence regarding the weak coupling between aboveground and belowground processes.

Antarctic ecosystems are among the most vulnerable to climate change, which is increasing the frequency and intensity of extreme climate events. In the McMurdo Dry Valleys (MDVs), three decades of high-resolution meteorological monitoring offer a rare opportunity to characterize climate baselines and detect anomalous conditions that may signal extreme events capable of triggering hydrological and ecological responses. However, identifying and assessing such anomalies from long-term records can be challenging without appropriate visualization tools and analytical frameworks. Here, we introduce MDV ClimEx, an open-source, interactive web application designed for user-driven exploration of long-term meteorological records from the MDVs. Specifically, this tool enables users to examine common meteorological variables at specific locations across multiple timescales to identify potential anomalies, combining dynamic visualizations with built-in functionality that quantifies the magnitude of user-identified anomalies as the number of standard deviations (sigma) from the historical average. Through three use cases involving both known and previously unreported air temperature anomalies in Taylor Valley, we demonstrate how MDV ClimEx serves as a valuable resource for researchers, educators, and the public to identify anomalies and support investigations of climate-driven hydrological and ecological changes in this polar desert ecosystem.

The predicted intensification of the North American Monsoon is expected to alter growing season rainfall patterns in the southwestern United States. These patterns, which have historically been characterized by frequent small rain events, are anticipated to shift towards a more extreme precipitation regime consisting of fewer, but larger rain events. Furthermore, human activities are contributing to increased atmospheric nitrogen deposition throughout this dryland region.Alterations in rainfall size and frequency, along with changes in nitrogen availability, are likely to have significant consequences for above-ground net primary production (ANPP) and plant community dynamics in drylands. The conceptual bucket model predicts that a shift towards fewer, but larger rain events could promote greater rates of ANPP in these regions by maintaining soil moisture availability above drought stress thresholds for longer periods during the growing season. However, only a few short-term studies have tested this hypothesis, and none have explored the interaction between altered rainfall patterns and nitrogen enrichment.To address this knowledge gap, we conducted a 14-year rainfall addition and nitrogen fertilization experiment in a northern Chihuahuan Desert grassland to explore the long-term impacts of changes in monsoon rainfall size and frequency, along with chronic nitrogen enrichment, on ANPP (measured as peak biomass) and plant community dynamics.Contrary to bucket model predictions, small frequent rain events promoted comparable rates of ANPP to large infrequent rain events in the absence of nitrogen enrichment. It was only when nitrogen limitation was alleviated that large infrequent rain events resulted in the greatest ANPP. Furthermore, we found that nitrogen enrichment had the greatest impact on plant community composition under the small frequent rainfall regime.Synthesis. Our long-term field experiment highlights limitations of the bucket model by demonstrating that water and nitrogen availability sequentially limit dryland ecological processes. Specifically, our findings suggest that while water availability is the primary limiting factor for above-ground net primary production in these ecosystems, nitrogen limitation becomes increasingly important when water is not limiting. Moreover, our findings reveal that small frequent rain events play an important but underappreciated role in driving dryland ecosystem dynamics. The bucket model predicts a shift towards fewer, but larger rain events will increase rates of above-ground net primary production in dryland ecosystems. However, a 14-year field experiment conducted in a desert grassland reveals limitations in the bucket model by demonstrating that water and nitrogen availability sequentially limit ecological processes in these ecosystems. Moreover, this long-term study highlights the importance of small frequent rain events in driving dryland ecosystem dynamics.image

Drylands are key contributors to interannual variation in the terrestrial carbon sink, which has been attributed primarily to broad-scale climatic anomalies that disproportionately affect net primary production (NPP) in these ecosystems. Current knowledge around the patterns and controls of NPP is based largely on measurements of aboveground net primary production (ANPP), particularly in the context of altered precipitation regimes. Limited evidence suggests belowground net primary production (BNPP), a major input to the terrestrial carbon pool, may respond differently than ANPP to precipitation, as well as other drivers of environmental change, such as nitrogen deposition and fire. Yet long-term measurements of BNPP are rare, contributing to uncertainty in carbon cycle assessments. Here, we used 16 years of annual NPP measurements to investigate responses of ANPP and BNPP to several environmental change drivers across a grassland-shrubland transition zone in the northern Chihuahuan Desert. ANPP was positively correlated with annual precipitation across this landscape; however, this relationship was weaker within sites. BNPP, on the other hand, was weakly correlated with precipitation only in Chihuahuan Desert shrubland. Although NPP generally exhibited similar trends among sites, temporal correlations between ANPP and BNPP within sites were weak. We found chronic nitrogen enrichment stimulated ANPP, whereas a one-time prescribed burn reduced ANPP for nearly a decade. Surprisingly, BNPP was largely unaffected by these factors. Together, our results suggest that BNPP is driven by a different set of controls than ANPP. Furthermore, our findings imply belowground production cannot be inferred from aboveground measurements in dryland ecosystems. Improving understanding around the patterns and controls of dryland NPP at interannual to decadal scales is fundamentally important because of their measurable impact on the global carbon cycle. This study underscores the need for more long-term measurements of BNPP to improve assessments of the terrestrial carbon sink, particularly in the context of ongoing environmental change.

Drylands are often characterized by a pulse dynamics framework in which episodic rain events trigger brief pulses of biological activity and resource availability that regulate primary production. In the northern Chihuahuan Desert, growing season precipitation typically comes from monsoon rainstorms that stimulate soil microbial processes like decomposition, releasing inorganic nitrogen needed by plant processes. Compared to microbes, plants require greater amounts of soil moisture, typically from larger monsoon storms predicted to become less frequent and more intense in the future. Yet field‐based studies linking rainfall pulses with soil nutrient dynamics are rare. Consequently, little is known about how changes in rainfall patterns may affect plant available nitrogen in dryland soils, particularly across temporal scales. We measured daily and seasonal responses of soil inorganic nitrogen and related parameters to experimentally applied small frequent and large infrequent rain events throughout a summer growing season in a Chihuahuan Desert grassland. Contrary to long‐standing theories around resource pulse dynamics in drylands, nitrogen availability did not pulse following experimental rain events. Moreover, large infrequent events resulted in significantly less plant available nitrogen despite causing distinct pulses of increased soil moisture availability that persisted for several days. Overall, nitrogen availability increased over the growing season, especially following small frequent rain events that also stimulated some microbial ecoenzymatic activities. Our results suggest that projected changes in climate to fewer, larger rain events could significantly impact primary production in desert grasslands by decreasing plant available nitrogen when soil moisture is least limiting to plant growth.

Primary production, a key regulator of the global carbon cycle, is highly responsive to variations in climate. Yet, a detailed, continental-scale risk assessment of climate-related impacts on primary production is lacking. We combined 16 years of MODIS NDVI data, a remotely sensed proxy for primary production, with observations from 1218 climate stations to derive values of ecosystem sensitivity to precipitation and aridity. For the first time, we produced an empirically-derived map of ecosystem sensitivity to climate across the conterminous United States. Over this 16-year period, annual primary production values were most sensitive to precipitation and aridity in dryland and grassland ecosystems. Century-long trends measured at the climate stations showed intensifying aridity and climatic variability in many of these sensitive regions. Dryland ecosystems in the western US may be particularly vulnerable to reductions in primary production and consequent degradation of ecosystem services as climate change and variability increase in the future.

The research data repository of the Environmental Data Initiative (EDI) is building on over 30 years of data curation research and experience in the National Science Foundation-funded US Long-Term Ecological Research (LTER) Network. It provides mature functionalities, well established workflows, and now publishes all ‘long-tail’ environmental data. High quality scientific metadata are enforced through automatic checks against community developed rules and the Ecological Metadata Language (EML) standard. Although the EDI repository is far along in making its data findable, accessible, interoperable, and reusable (FAIR), representatives from EDI and the LTER are developing best practices for the edge cases in environmental data publishing. One of these is the vast amount of imagery taken in the context of ecological research, ranging from wildlife camera traps to plankton imaging systems to aerial photography. Many images are used in biodiversity research for community analyses (e.g., individual counts, species cover, biovolume, productivity), while others are taken to study animal behavior and landscape-level change. Some examples from the LTER Network include: using photos of a heron colony to measure provisioning rates for chicks (Clarkson and Erwin 2018) or identifying changes in plant cover and functional type through time (Peters et al. 2020). Multi-spectral images are employed to identify prairie species. Underwater photo quads are used to monitor changes in benthic biodiversity (Edmunds 2015). Sosik et al. (2020) used a continuous Imaging FlowCytobot to identify and measure phyto- and microzooplankton. Cameras at McMurdo Dry Valleys assess snow and ice cover on Antarctic lakes allowing estimation of primary production (Myers 2019). It has been standard practice to publish numerical data extracted from images in EDI; however, the supporting imagery generally has not been made publicly available. Our goal in developing best practices for documenting and archiving these images is for them to be discovered and re-used. Our examples demonstrate several issues. The research questions, and hence, the image subjects are variable. Images frequently come in logical sets of time series. The size of such sets can be large and only some images may be contributed to a dedicated specialized repository. Finally, these images are taken in a larger monitoring context where many other environmental data are collected at the same time and location. Currently, a typical approach to publishing image data in EDI are packages containing compressed (ZIP or tar) files with the images, a directory manifest with additional image-specific metadata, and a package-level EML metadata file. Images in the compressed archive may be organized within directories with filenames corresponding to treatments, locations, time periods, individuals, or other grouping attributes. Additionally, the directory manifest table has columns for each attribute. Package-level metadata include standard coverage elements (e.g., date, time, location) and sampling methods. This approach of archiving logical ‘sets’ of images reduces the effort of providing metadata for each image when most information would be repeated, but at the expense of not making every image individually searchable. The latter may be overcome if the provided manifest contains standard metadata that would allow searching and automatic integration with other images.

Earth and Space Science Open Archive PosterOpen AccessYou are viewing the latest version by default [v1]Going beyond the spreadsheet - developing Best Practices in ‘long-tail’ environmental data curation and publishingAuthorsCorinnaGriesiDRenéeBrowniDMaryGastil-BuhlSarahElmendorfHapGarrittiDMaryMartinGregMaureriDAnNguyenJohnPorteriDTimothyWhiteakerSee all authors Corinna GriesiDCorresponding Author• Submitting AuthorUniversity of Wisconsin MadisoniDhttps://orcid.org/0000-0002-9091-6543view email addressThe email was not providedcopy email addressRenée BrowniDUniversity of New Mexico Main CampusiDhttps://orcid.org/0000-0002-4986-7663view email addressThe email was not providedcopy email addressMary Gastil-BuhlMoorea Coral Reef LTERview email addressThe email was not providedcopy email addressSarah ElmendorfUniversity of Colorado Boulderview email addressThe email was not providedcopy email addressHap GarrittiDWoods Hole Marine Biological LabiDhttps://orcid.org/0000-0001-5912-0769view email addressThe email was not providedcopy email addressMary MartinUniversity of New Hampshire Main Campusview email addressThe email was not providedcopy email addressGreg MaureriDNew Mexico State UniversityiDhttps://orcid.org/0000-0002-3007-8058view email addressThe email was not providedcopy email addressAn NguyenUniversity of Texas at Austinview email addressThe email was not providedcopy email addressJohn PorteriDUniversity of VirginiaiDhttps://orcid.org/0000-0003-3118-5784view email addressThe email was not providedcopy email addressTimothy WhiteakerCRWRview email addressThe email was not providedcopy email address

A data manager's perspective of challenges and unique constraints in acquiring environmental data from the McMurdo Dry Valleys in Antarctica. This presentation was given in July 2019 at the EnviroSensing Cluster session at the Earth Science Information Partners (ESIP) Summer Meeting held in Tacoma, Washington.

Tremendous growth has occurred over the past fifteen years or so in the development and use of sensors and associated technological infrastructure in ecological field research (Porter et al. 2009). Of course, ecologists have been using sensors in a monitoring context for decades. Instrumented meteorological stations, for example, are commonly used in terrestrial systems to collect highfrequency measurements of air temperature, soil moisture, and other climatological parameters, while multiparameter sondes have been used extensively in aquatic systems to collect physicochemical data for assessing water quality. Sensor technologies are also deployed by researchers interested in monitoring and comparing ecological systems within an organized network, such as the National Ecological Observatory Network (NEON) or the Global Lakes Ecological Observatory Network (GLEON). Flux towers dot the landscape. However, sensors are increasingly being used in combination with associated cyberinfrastructure as tools that integrate data collection, processing, analysis, and visualization in experimental contexts. Here, we focus on the use of terrestrial sensor arrays, defined as multiple sensor systems (e.g., a suite of temperature, moisture, and CO 2 probes), that can be deployed to generate integrated measurements of ecological phenomena (e.g., soil CO 2 efflux) at high temporal resolution in manipulative experiments (Fig. 1). It is from this perspective that we are writing our personal experience using sensor technologies in ecological research.