In adaptive management of rangelands, monitoring is the vital link that connects management actions with on‐the‐ground changes. Traditional field monitoring methods can provide detailed information ...for assessing the health of rangelands, but cost often limits monitoring locations to a few key areas or random plots. Remotely sensed imagery, and drone‐based imagery in particular, can observe larger areas than field methods while retaining high enough spatial resolution to estimate many rangeland indicators of interest. However, the geographic extent of drone imagery products is often limited to a few hectares (for resolution ≤1 cm) due to image collection and processing constraints. Overcoming these limitations would allow for more extensive observations and more frequent monitoring. We developed a workflow to increase the extent and speed of acquiring, processing, and analyzing drone imagery for repeated monitoring of two common indicators of interest to rangeland managers: vegetation cover and vegetation heights. By incorporating a suite of existing technologies in drones (real‐time kinematic GPS), data processing (automation with Python scripts, high performance computing), and cloud‐based analysis (Google Earth Engine), we greatly increased the efficiency of collecting, analyzing, and interpreting high volumes of drone imagery for rangeland monitoring. End‐to‐end, our workflow took 30 d, while a workflow without these innovations was estimated to require 141 d to complete. The technology around drones and image analysis is rapidly advancing which is making high volume workflows easier to implement. Larger quantities of monitoring data will significantly improve our understanding of the impact management actions have on land processes and ecosystem traits.
Abstract
Dryland ecosystems are dominant influences on both the trend and interannual variability of the terrestrial carbon sink. Despite their importance, dryland carbon dynamics are not ...well-characterized by current models. Here, we present DryFlux, an upscaled product built on a dense network of eddy covariance sites in the North American Southwest. To estimate dryland gross primary productivity, we fuse in situ fluxes with remote sensing and meteorological observations using machine learning. DryFlux explicitly accounts for intra-annual variation in water availability, and accurately predicts interannual and seasonal variability in carbon uptake. Applying DryFlux globally indicates existing products may underestimate impacts of large-scale climate patterns on the interannual variability of dryland carbon uptake. We anticipate DryFlux will be an improved benchmark for earth system models in drylands, and prompt a more sensitive accounting of water limitation on the carbon cycle.
In the southwest United States, the current prolonged warm drought is similar to the predicted future climate change scenarios for the region. This study aimed to determine patterns in vegetation ...response to the early 21st century drought across multiple biomes. We hypothesized that different biomes (forests, shrublands, and grasslands) would have different relative sensitivities to both climate drivers (precipitation and temperature) and legacy effects (previous‐year's productivity). We tested this hypothesis at eight Ameriflux sites in various Southwest biomes using NASA Moderate‐resolution Imaging Spectroradiometer Enhanced Vegetation Index (EVI) from 2001 to 2013. All sites experienced prolonged dry conditions during the study period. The impact of combined precipitation and temperature on Southwest ecosystems at both annual and sub‐annual timescales was tested using Standardized Precipitation Evapotranspiration Index (SPEI). All biomes studied had critical sub‐annual climate periods during which precipitation and temperature influenced production. In forests, annual peak greenness (EVImax) was best predicted by 9‐month SPEI calculated in July (i.e., January–July). In shrublands and grasslands, EVImax was best predicted by SPEI in July through September, with little effect of the previous year's EVImax. Daily gross ecosystem production (GEP) derived from flux tower data yielded further insights into the complex interplay between precipitation and temperature. In forests, GEP was driven by cool‐season precipitation and constrained by warm‐season maximum temperature. GEP in both shrublands and grasslands was driven by summer precipitation and constrained by high daily summer maximum temperatures. In grasslands, there was a negative relationship between temperature and GEP in July, but no relationship in August and September. Consideration of sub‐annual climate conditions and the inclusion of the effect of temperature on the water balance allowed us to generalize the functional responses of vegetation to predicted future climate conditions. We conclude that across biomes, drought conditions during critical sub‐annual climate periods could have a strong negative impact on vegetation production in the southwestern United States.
Precipitation regimes are predicted to shift to more extreme patterns that are characterized by more heavy rainfall events and longer dry intervals, yet their ecological impacts on vegetation ...production remain uncertain across biomes in natural climatic conditions. This in situ study investigated the effects of these climatic conditions on aboveground net primary production (ANPP) by combining a greenness index from satellite measurements and climatic records during 2000–2009 from 11 long‐term experimental sites in multiple biomes and climates. Results showed that extreme precipitation patterns decreased the sensitivity of ANPP to total annual precipitation (PT) at the regional and decadal scales, leading to decreased rain use efficiency (RUE; by 20% on average) across biomes. Relative decreases in ANPP were greatest for arid grassland (16%) and Mediterranean forest (20%) and less for mesic grassland and temperate forest (3%). The cooccurrence of heavy rainfall events and longer dry intervals caused greater water stress conditions that resulted in reduced vegetation production. A new generalized model was developed using a function of both PT and an index of precipitation extremes and improved predictions of the sensitivity of ANPP to changes in precipitation patterns. Our results suggest that extreme precipitation patterns have substantially negative effects on vegetation production across biomes and are as important as PT. With predictions of more extreme weather events, forecasts of ecosystem production should consider these nonlinear responses to altered extreme precipitation patterns associated with climate change.
Key Points
Extreme rainfall events reduced the sensitivity of ANPP to total annual rainfallCo‐occurrence of intense rainfall and longer dry interval reduced greater ANPPA new model improved predictions of ANPP by accounting for extreme patterns
Intra-annual precipitation patterns are expected to shift toward more intense storms and longer dry periods because of changes in climate within future decades. Using satellite-derived estimates of ...plant growth combined with in situ measurements of precipitation and soil moisture between 1999 and 2013, this study quantified the relationship between intra-annual precipitation patterns, annual average soil moisture (at 5-cm depth), and plant growth at nine grassland sites across the southern United States. Results showed a fundamental difference in the response to varying precipitation patterns between mesic and semiarid grasslands. Surface soil moisture in mesic grasslands decreased with an increase of high-intensity storms, whereas in semiarid grasslands, soil moisture decreased with longer dry periods. For these sites, annual average soil moisture was a better indicator of grassland production than total annual precipitation. This improved ability to predict variability in soil moisture and plant growth with changing hydroclimatic conditions will result in more efficient resource management and better-informed policy decisions.
Much of the western United States is covered by rangelands used for grazing and wildlife. Woody plant cover is increasing in areas historically covered by grasslands and can cause numerous problems, ...including losses in wildlife habitat, forage for grazing, and overall losses in soil health. Land managers and conservationists are working to control these increases in woody plants, but need tools to help determine target areas to focus efforts and resources where they are most needed. In this work, we present RaBET (Rangeland Brush Estimation Tool), which uses transparent, well-understood methodologies with remotely sensed data to map woody canopy cover across large areas of rangelands. We demonstrate that our process produced more accurate results than two currently available tools based on advanced machine learning techniques. We compare two methods of map validation: traditional field methods of plant canopy measurements; and aircraft-based photography, which decreases the amount of time and resources needed. RaBET is a remote sensing-based application for obtaining repeatable, accurate measures of woody cover to aid land managers and conservationists in the control of woody plants on rangelands.
Juniper trees are widely distributed throughout the world and are common sources of allergies when microscopic pollen grains are transported by wind and inhaled. In this study, we investigated the ...spectral influences of pollen-discharging male juniper cones within a juniper canopy. This was done through a controlled outdoor experiment involving ASD FieldSpec Pro Spectroradiometer measurements over juniper canopies of varying cone densities. Broadband and narrowband spectral reflectance and vegetation index (VI) patterns were evaluated as to their sensitivity and their ability to discriminate the presence of cones. The overall aim of this research was to assess remotely sensed phenological capabilities to detect pollen-bearing juniper trees for public health applications. A general decrease in reflectance values with increasing juniper cone density was found, particularly in the Green (545–565 nm) and NIR (750–1,350 nm) regions. In contrast, reflectances in the shortwave-infrared (SWIR, 2,000 nm to 2,350 nm) region decreased from no cone presence to intermediate amounts (90 g/m2) and then increased from intermediate levels to the highest cone densities (200 g/m2). Reflectance patterns in the Red (620–700 nm) were more complex due to shifting contrast patterns in absorptance between cones and juniper foliage, where juniper foliage is more absorbing than cones only within the intense narrowband region of maximum chlorophyll absorption near 680 nm. Overall, narrowband reflectances were more sensitive to cone density changes than the equivalent MODIS broadbands. In all VIs analyzed, there were significant relationships with cone density levels, particularly with the narrowband versions and the two-band vegetation index (TBVI) based on Green and Red bands, a promising outcome for the use of phenocams in juniper phenology trait studies. These results indicate that spectral indices are sensitive to certain juniper phenologic traits that can potentially be used for juniper cone detection in support of public health applications.
Global-scale studies suggest that dryland ecosystems dominate an increasing trend in the magnitude and interannual variability of the land CO
sink. However, such analyses are poorly constrained by ...measured CO
exchange in drylands. Here we address this observation gap with eddy covariance data from 25 sites in the water-limited Southwest region of North America with observed ranges in annual precipitation of 100-1000 mm, annual temperatures of 2-25°C, and records of 3-10 years (150 site-years in total). Annual fluxes were integrated using site-specific ecohydrologic years to group precipitation with resulting ecosystem exchanges. We found a wide range of carbon sink/source function, with mean annual net ecosystem production (NEP) varying from -350 to +330 gCm
across sites with diverse vegetation types, contrasting with the more constant sink typically measured in mesic ecosystems. In this region, only forest-dominated sites were consistent carbon sinks. Interannual variability of NEP, gross ecosystem production (GEP), and ecosystem respiration (R
) was larger than for mesic regions, and half the sites switched between functioning as C sinks/C sources in wet/dry years. The sites demonstrated coherent responses of GEP and NEP to anomalies in annual evapotranspiration (ET), used here as a proxy for annually available water after hydrologic losses. Notably, GEP and R
were negatively related to temperature, both interannually within site and spatially across sites, in contrast to positive temperature effects commonly reported for mesic ecosystems. Models based on MODIS satellite observations matched the cross-site spatial pattern in mean annual GEP but consistently underestimated mean annual ET by ~50%. Importantly, the MODIS-based models captured only 20-30% of interannual variation magnitude. These results suggest the contribution of this dryland region to variability of regional to global CO
exchange may be up to 3-5 times larger than current estimates.
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•Assessed common metrics with data from 34 cropland, grazing & integrated systems.•Compared production and phenology metrics from eddy covariance, PhenoCam and Landsat.•Correlations ...among metrics varied across diverse U.S. agroecosystems.•Devised a metric assessment framework to streamline decision making for monitoring.
Effective measurement of seasonal variations in the timing and amount of production is critical to managing spatially heterogeneous agroecosystems in a changing climate. Although numerous technologies for such measurements are available, their relationships to one another at a continental extent are unknown. Using data collected from across the Long-Term Agroecosystem Research (LTAR) network and other networks, we investigated correlations among key metrics representing primary production, phenology, and carbon fluxes in croplands, grazing lands, and crop-grazing integrated systems across the continental U.S. Metrics we examined included gross primary productivity (GPP) estimated from eddy covariance (EC) towers and modelled from the Landsat satellite, Landsat NDVI, and vegetation greenness (Green Chromatic Coordinate, GCC) from tower-mounted PhenoCams for 2017 and 2018. Overall, our analysis compared production dynamics estimated from three independent ground and remote platforms using data for 34 agricultural sites constituting 51 site-years of co-located time series.
Pairwise sensor comparisons across all four metrics revealed stronger correlation and lower root mean square error (RMSE) between end of season (EOS) dates (Pearson R ranged from 0.6 to 0.7 and RMSE from 32.5 to 67.8) than start of season (SOS) dates (0.46 to 0.69 and 40.4 to 66.2). Overall, moderate to high correlations between SOS and EOS metrics complemented one another except at some lower productivity grazing land sites where estimating SOS can be challenging. Growing season length estimates derived from 16-day satellite GPP (179.1 days) were significantly longer than those from PhenoCam GCC (70.4 days, padj < 0.0001) and EC GPP (79.6 days, padj < 0.0001). Landscape heterogeneity did not explain differences in SOS and EOS estimates. Annual integrated estimates of productivity from EC GPP and PhenoCam GCC diverged from those estimated by Landsat GPP and NDVI at sites where annual production exceeds 1000 gC/m−2 yr−1. Based on our results, we developed a “metric assessment framework” that articulates where and how metrics from satellite, eddy covariance and PhenoCams complement, diverge from, or are redundant with one another. The framework was designed to optimize instrumentation selection for monitoring, modeling, and forecasting ecosystem functioning with the ultimate goal of informing decision-making by land managers, policy-makers, and industry leaders working at multiple scales.
Agriculture and natural systems interweave in the southeastern US, including Florida, Georgia, and Alabama, where topographic, edaphic, hydrologic, and climatic gradients form nuanced landscapes. ...These are largely working lands under private control, comprising mosaics of timberlands, grazinglands, and croplands. According to the “ecosystem services” framework, these landscapes are multifunctional. Generally, working lands are highly valued for their provisioning services, and to some degree cultural services, while regulating and supporting services are harder to quantify and less appreciated. Trade-offs and synergies exist among these services. Regional ecological assessments tend to broadly paint working lands as low value for regulating and supporting services. But this generalization fails to consider the complexity and tight spatial coupling of land uses and land covers evident in such regions. The challenge of evaluating multifunctionality and ecosystem services is that they are not spatially concordant. While there are significant acreages of natural systems embedded in southeastern working lands, their spatial characteristics influence the balance of tradeoffs between ecosystem services at differing scales. To better understand this, we examined the configuration of working lands in the southeastern US by comparing indicators of ecosystem services at multiple scales. Indicators included measurements of net primary production (provisioning), agricultural Nitrogen runoff (regulating), habitat measured at three levels of land use intensity, and biodiversity (supporting). We utilized a hydrographic and ecoregional framework to partition the study region. We compared indicators aggregated at differing scales, ranging from broad ecoregions to local landscapes focused on the USDA Long-Term Agroecosystem Research (LTAR) Network sites in Florida and Georgia. Subregions of the southeastern US differ markedly in contributions to overall ecosystem services. Provisioning services, characterized by production indicators, were very high in northern subregions of Georgia, while supporting services, characterized by habitat and biodiversity indicators, were notably higher in smaller subregions of Florida. For supporting services, the combined contributions of low intensity working lands with embedded natural systems made a critical difference in their regional evaluation. This analysis demonstrated how the inclusion of working lands combined with examining these at different scales shifted our understanding of ecosystem services trade-offs and synergies in the southeastern United States.
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