For publications earlier than 2019, view our publications archive.
| Buřivalová, Zuzana; Rosin, Cooper; Buchner, Johanna; Radeloff, Volker C.; Ocampo-Peñuela, Natalia: Conservation responsibility for bird species in tropical logged forests. In: Conservation Letters, vol. n/a, no. n/a, pp. e12903, 2022. (Type: Journal Article | | )|
Abstract Unprotected lands can help prevent the extinctions of species if managed carefully. Over half of the tropical forest is leased by logging companies, whereas only 6%–18% is protected. This makes the timber industry, institutions that regulate it, and consumers of its products important actors in conservation. We assessed the conservation responsibility, the proportion of a species’ range that tropical timber industry concessions overlap with, for bird species that decline after selective logging. Up to 32% of the global range and up to 100% of the national range of sensitive species within our study countries are leased by logging companies. Individual concessions overlap with the ranges of up to 25 sensitive and more than 500 total bird species, with a particularly high density in Borneo. Our results can inform governments, forest managers, sustainability certifiers, and consumers so that they can turn this responsibility into a conservation opportunity through interventions at multiple scales.
| Ruis, A. R.; Siebert-Evenstone, A. L.; Brohinsky, J.; Tan, Y.; Hinojosa, C. L.; Cai, Z.; Marquart, C. L.; Lark, T. J.; Barford, C.; Shaffer, D. W.: Localizing Socio-Environmental Problem Solving. In: International Collaboration toward Educational Innovation for All: Overarching Research, Development, and Practices: 15th International Conference on Computer-Supported Collaborative Learning (CSCL), Weinberger, A.; Chen, W.; Hernández-Leo, D.; Chen, B. (Ed.): pp. 459–462, 2022. (Type: Journal Article | | )|
In this paper, we describe iPlan, a web-based software platform for constructing localized, reduced-form models of land-use impacts, enabling students, civic representatives, and others without specialized knowledge of land-use planning practices to explore and evaluate possible solutions to complex, multi-objective land-use problems in their own local contexts.
| Gesangyangji,; Vimont, Daniel J; Holloway, Tracey; Lorenz, David J: A methodology for evaluating the effects of climate change on climatic design conditions for buildings and application to a case study in Madison, Wisconsin. In: Environmental Research: Infrastructure and Sustainability, vol. 2, no. 2, pp. 025007, 2022. (Type: Journal Article | | )|
Climatic design conditions are widely used by the building community as environmental parameters informing the size and energy requirements for heating, ventilation and air conditioning systems, along with other building design characteristics. Climatic design conditions are calculated by the American Society of Heating, Refrigerating and Air-conditioning Engineers using historical climate data. Our work advances methods for projecting future climate design conditions based on data from global climate models. These models do not typically archive the hourly data required for climate design condition calculations, and they often exhibit large biases in extreme conditions, daily minimum temperatures and daily maximum temperatures needed for climatic design conditions. We present a method for rescaling historical hourly data under future climatic states to estimate the impact of climate change on future building climatic design conditions. This rescaling method is then used to calculate future climatic design conditions in Madison, Wisconsin, throughout the 21st century for two future greenhouse gas emissions scenarios. The results are consistent with a warming climate and show increases in heating, cooling, humidification and dehumidification design conditions, suggesting less extreme cold conditions and more extreme hot and humid conditions in Madison. The design conditions used for estimating energy demand, degree days, show that under a business-as-usual scenario, by the mid-century, building heating and cooling in Madison (climate zone 5A) will be similar to the current heating demand in Chicago, IL (climate zone 5A) and cooling demand in Baltimore, MD (climate zone 4A); by the late-century, building heating and cooling in Madison will resemble the current heating demand in St Louis, MO (climate zone 4A) and cooling demand in Augusta, GA (climate zone 3A). Given the rapid pace of climate change in the 21st century, our work suggests that historical design conditions may become obsolete during even the initial stages of a building’s expected life span. Changes in climatic design conditions in Madison highlight the importance of considering future climatic changes in building design to ensure that buildings built today meet the performance needs of the future.
| Lesiv, Myroslava; Schepaschenko, Dmitry; Buchhorn, Marcel; See, Linda; Dürauer, Martina; Georgieva, Ivelina; Jung, Martin; et al,: Global forest management data for 2015 at a 100m resolution. In: Scientific Data, vol. 9, no. 1, pp. 199, 2022, ISSN: 2052-4463. (Type: Journal Article | | )|
Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki (https://www.geo-wiki.org/). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services.
| Skidmore, Marin Elisabeth; Sims, Kaitlyn M; Rausch, Lisa L; Gibbs, Holly K: Sustainable intensification in the Brazilian cattle industry: the role for reduced slaughter age. In: Environmental Research Letters, vol. 17, no. 6, pp. 064026, 2022. (Type: Journal Article | | )|
The cattle industry in the Brazilian Amazon causes vast deforestation while producing at only one-third of the sustainable capacity. Slaughtering cattle at a younger age directly increases production per hectare per year, all else equal, and provides a potential path for sustainable intensification. Here we show that slaughter age is decreasing in the Amazon biome, but this increase in productivity varies across space and throughout the cattle supply chain. We characterize the properties and municipalities that have reduced slaughter age, providing insights into the incentives and barriers to this form of intensification. Most notably, reductions in slaughter age occurred in regions with low remaining forest cover and on properties with little current deforestation, suggesting that ranchers intensify via slaughter age as an alternative to deforestation. We then estimate how changing production practices to reduce slaughter age can reduce enteric methane emissions, accounting for production of additional feed. Our results indicate that reducing slaughter age through improved pasture and feed sources are a path to lower global GHG emissions from cattle production, particularly as beef is increasingly produced in developing countries with historically higher emissions. Yet in the Amazon, deforestation remains the leading source of GHG emissions, necessitating that any effort to reduce slaughter age must be coupled with strict enforcement of zero-deforestation policy. Our findings demonstrate the potential of policy limiting deforestation as a means to reduce both emissions from deforestation and enteric emissions from cattle.
| Campbell, Tracy A.; Booth, Eric G.; Gratton, Claudio; Jackson, Randall D.; Kucharik, Christopher J.: Agricultural Landscape Transformation Needed to Meet Water Quality Goals in the Yahara River Watershed of Southern Wisconsin. In: Ecosystems, vol. 25, no. 3, pp. 507-525, 2022, ISSN: 1435-0629. (Type: Journal Article | | )|
Balancing agricultural production with other ecosystem services is a vexing challenge. The Yahara River watershed in southern Wisconsin is a place where tensions among farmers, policymakers, and citizens at-large run high because nutrient loss from the agricultural practices of a few drive the impairment of surface waters for many. Reducing manure and fertilizer application, as well as increasing perennial grass cover have been proposed as potential solutions. Using the Agro-IBIS agroecosystem model, we examined 48 scenarios of future land management and climate for the Yahara River watershed to the year 2070. Scenarios included combinations of reduced livestock and increased perennial grassland under alternative climate trajectories. Results suggested that business as usual will lead to further environmental degradation with phosphorus-loading to waterways increasing 13, 7, and 23% under baseline, warmer and drier, and warmer and wetter climates, respectively. Watershed-wide phosphorous yield and nitrate leaching could be reduced by 50%, but only when nutrient application was reduced 50% and grassland cover was increased 50%. Furthermore, water quality improvements only materialized 50 years after modified land management practices were implemented under the most likely future climate. Our findings highlight that improving water quality under a changing climate will require long-term investment and transformative changes to current agricultural land use and land cover. Agricultural management solutions exist but are unlikely to be implemented without policies that incentivize transformative agricultural change.
| Edwards, Morgan R; Cui, Ryna; Bindl, Matilyn; Hultman, Nathan; Mathur, Krinjal; McJeon, Haewon; Iyer, Gokul; Song, Jiawei; Zhao, Alicia: Quantifying the regional stranded asset risks from new coal plants under 1.5 °C. In: Environmental Research Letters, vol. 17, no. 2, pp. 024029, 2022. (Type: Journal Article | | )|
Momentum to phase out unabated coal use is growing globally. This transition is critical to meeting the Paris climate goals but can potentially lead to large amounts of stranded assets, especially in regions with newer and growing coal fleets. Here we combine plant-level data with a global integrated assessment model to quantify changes in global stranded asset risks from coal-fired power plants across regions and over time. With new plant proposals, cancellations, and retirements over the past five years, global net committed emissions in 2030 from existing and planned coal plants declined by 3.3 GtCO2 (25%). While these emissions are now roughly in line with initial Nationally Determined Contributions (NDCs) to the Paris Agreement, they remain far off track from longer-term climate goals. Progress made in 2021 towards no new coal can potentially avoid a 24% (503 GW) increase in capacity and a 55% ($520 billion) increase in stranded assets under 1.5 °C. Stranded asset risks fall disproportionately on emerging Asian economies with newer and growing coal fleets. Recent no new coal commitments from major coal financers can potentially reduce stranding of international investments by over 50%.
| Michalska-Smith, Matthew; Song, Zewei; Spawn-Lee, Seth A.; Hansen, Zoe A.; Johnson, Mitch; May, Georgiana; Borer, Elizabeth T.; Seabloom, Eric W.; Kinkel, Linda L.: Network structure of resource use and niche overlap within the endophytic microbiome. In: The ISME Journal, vol. 16, no. 2, pp. 435-446, 2022, ISSN: 1751-7370. (Type: Journal Article | | )|
Endophytes often have dramatic effects on their host plants. Characterizing the relationships among members of these communities has focused on identifying the effects of single microbes on their host, but has generally overlooked interactions among the myriad microbes in natural communities as well as potential higher-order interactions. Network analyses offer a powerful means for characterizing patterns of interaction among microbial members of the phytobiome that may be crucial to mediating its assembly and function. We sampled twelve endophytic communities, comparing patterns of niche overlap between coexisting bacteria and fungi to evaluate the effect of nutrient supplementation on local and global competitive network structure. We found that, despite differences in the degree distribution, there were few significant differences in the global network structure of niche-overlap networks following persistent nutrient amendment. Likewise, we found idiosyncratic and weak evidence for higher-order interactions regardless of nutrient treatment. This work provides a first-time characterization of niche-overlap network structure in endophytic communities and serves as a framework for higher-resolution analyses of microbial interaction networks as a consequence and a cause of ecological variation in microbiome function.
| Lark, Tyler J.; Hendricks, Nathan P.; Smith, Aaron; Pates, Nicholas; Spawn-Lee, Seth A.; Bougie, Matthew; Booth, Eric G.; Kucharik, Christopher J.; Gibbs, Holly K.: Environmental outcomes of the US Renewable Fuel Standard. In: Proceedings of the National Academy of Sciences, vol. 119, no. 9, pp. e2101084119, 2022. (Type: Journal Article | | )|
Biofuels are included in many proposed strategies to reduce anthropogenic greenhouse gas emissions and limit the magnitude of global warming. The US Renewable Fuel Standard is the world’s largest existing biofuel program, yet despite its prominence, there has been limited empirical assessment of the program’s environmental outcomes. Even without considering likely international land use effects, we find that the production of corn-based ethanol in the United States has failed to meet the policy’s own greenhouse gas emissions targets and negatively affected water quality, the area of land used for conservation, and other ecosystem processes. Our findings suggest that profound advances in technology and policy are still needed to achieve the intended environmental benefits of biofuel production and use. The Renewable Fuel Standard (RFS) specifies the use of biofuels in the United States and thereby guides nearly half of all global biofuel production, yet outcomes of this keystone climate and environmental regulation remain unclear. Here we combine econometric analyses, land use observations, and biophysical models to estimate the realized effects of the RFS in aggregate and down to the scale of individual agricultural fields across the United States. We find that the RFS increased corn prices by 30% and the prices of other crops by 20%, which, in turn, expanded US corn cultivation by 2.8 Mha (8.7%) and total cropland by 2.1 Mha (2.4%) in the years following policy enactment (2008 to 2016). These changes increased annual nationwide fertilizer use by 3 to 8%, increased water quality degradants by 3 to 5%, and caused enough domestic land use change emissions such that the carbon intensity of corn ethanol produced under the RFS is no less than gasoline and likely at least 24% higher. These tradeoffs must be weighed alongside the benefits of biofuels as decision-makers consider the future of renewable energy policies and the potential for fuels like corn ethanol to meet climate mitigation goals.
| Rayadin, Yaya; Buřivalová, Zuzana: What does it take to have a mutually beneficial research collaboration across countries?. In: Conservation Science and Practice, vol. 4, no. 5, pp. e528, 2022. (Type: Journal Article | | )|
Abstract We reflect on the challenges researchers face when working in multi-national collaborations in conservation science, whereby the researchers' countries are unequal in terms of financial and institutional support or other factors that contribute to a power imbalance. Based on our personal experiences and challenges, we outline four key aspects of the research cycle that provide opportunities to build or strengthen more equitable research partnerships: defining the shared research agenda, obtaining funding, publication, and the connecting thread of effective communication. We give recommendations for both the visiting scientist and the local scientist hosting international collaborators, as well as for institutions involved in conservation science. We hope that our perspectives can help other conservation scientists achieve productive and mutually beneficial collaborations that can lead to positive conservation outcomes.
| Neij, Lena; Nemet, Gregory: Accelerating the low-carbon transition will require policy to enhance local learning. In: Energy Policy, vol. 167, pp. 113043, 2022, ISSN: 0301-4215. (Type: Journal Article | | )|
The transition to a low-carbon society requires a deep transformation, enabled by rapid adoption of new energy technologies. A main driver for this will be technology learning, providing cost reductions in low-carbon technologies. Over the past two decades, learning has provided substantial cost reductions for a number of hardware technologies, such as PV modules, wind turbines, and battery packs, some by a factor of ten. Still, we observe weaker cost reductions in installing and integrating such technologies into the broader system. As a result, hardware costs comprise a decreasing share of total costs. In the case of US rooftop PV installations, hardware today accounts for less than a quarter of the total costs. Accelerating the transition to a low-carbon society will thus require more attention to learning in the implementation of technologies. In contrast to cost reductions of technology hardware, driven by global learning, learning in implementation is typically framed by local geography and structure, involving local actors, networks and institutions. In this Perspective we argue that accelerating the transition to a low-carbon society, depends on the advancement of our understanding of 1) the local learning required to reduce implementation costs, and 2) the policy mechanisms vital to stimulate local learning. The transition process calls for an improved understanding of the spatial dimensions that shape learning and the implications in designing policy that support local learning. Accordingly, we advocate for more comprehensive and contextualized research on policy to support local learning providing cost reductions in low-carbon technologies.
| Steckel, J.; Jakob, M.: To end coal, adapt to regional realities. In: Nature, vol. 507, pp. 29-31, 2022, (co-signatory). (Type: Journal Article | )|
| Gao, Xue; Rai, Varun; Nemet, Gregory F.: The roles of learning mechanisms in services: Evidence from US residential solar installations. In: Energy Policy, vol. 167, pp. 113003, 2022, ISSN: 0301-4215. (Type: Journal Article | | )|
Non-hardware costs are majority of the cost of producing solar photovoltaic (PV) electricity. We use matched data on patents and over 125,000 residential PV installations to estimate the effects of three learning mechanisms in reducing PV costs: learning by doing, searching, and interacting. While previous work in this area has focused predominantly on learning by doing, we find that learning by searching and interacting are also significant mechanisms to facilitate non-hardware cost reductions. Including these two mechanisms reduces the effect of learning by doing in explaining non-hardware cost reductions by 43%. Our results suggest that prior work may overemphasize the role of learning by doing and the policies that help generate learning by doing. Analysis of the supplier-network between installers and their suppliers shows that concentrated supplier networks are associated with lower non-hardware costs, although there are key differences between installer-panel and installer-inverter manufacturer networks. An important implication is that policies for reducing non-hardware costs need to take a more complete view of how different learning mechanisms engender cost reductions. They should particularly consider the important role of learning in supplier networks in cost reductions—an effect that until now has largely been missing in analyses of solar non-hardware costs.
| Nemet, Gregory; Greene, Jenna: Innovation in low-energy demand and its implications for policy. In: Oxford Open Energy, vol. 1, 2022, ISSN: 2752-5082, (oiac003). (Type: Journal Article | | )|
Scenarios featuring low-energy demand have the potential to meet climate stabilization targets while also pursuing inclusive well-being and multiple Sustainable Development Goals. Recent papers have assembled detailed bottom-up estimates to inform integrated assessment modeling and show that LED outcomes are feasible and have beneficial effects across multiple goals. But realizing the full potential in LED depends on innovation -- i.e. improvement in LED technology and widespread adoption of both LED technology and behavior -- as well as policies supporting innovation. We review the literature to better understand the role of technological innovation in enabling LED scenarios and how policy interventions can stimulate those innovations. We structure our review using a policy analysis framework that includes specifying multiple LED policy goals, describing the distinct characteristics of LED technology to understand policy needs. The distinct characteristics of LED innovation include multiple attributes and new services, many heterogeneous adopters, small granular scale, many iterations, local system integration, and rebound effects, among others. We also consider five important drivers of change in LED innovation: higher living standards and preferences for clean environments, urbanization, digitalization, demand for novel services and the emergence of prosumers. The analysis in this review of the literature leads to nine LED policy design guidelines.
| Li, Shihua; Wang, Yingping; Ciais, Philippe; Sitch, Stephen; Sato, Hisashi; Shen, Miaogen; Chen, Xiuzhi; Ito, Akihiko; Wu, Chaoyang; Kucharik, Christopher J.; Yuan, Wenping: Deficiencies of Phenology Models in Simulating Spatial and Temporal Variations in Temperate Spring Leaf Phenology. In: Journal of Geophysical Research: Biogeosciences, vol. 127, no. 3, pp. e2021JG006421, 2022, (e2021JG006421 2021JG006421). (Type: Journal Article | | )|
Abstract Spring leaf phenology and its response to climate change have crucial effects on surface albedo, carbon balance, and the water cycle of terrestrial ecosystems. Based on long-term (period 1963–2014) in situ observations of budburst date and leaf unfolding date of more than 300 deciduous woody species from 32 sites across the temperate zone in China, we conducted model-data comparison of spatial and temporal variations for spring leaf phenology calculated using the phenology modules that were embed into 10 existing terrestrial ecosystem models. Our results suggested that ORganizing Carbon and Hydrology in Dynamic EcosystEms and Spatially Explicit Individual-Based performed the best in reproducing the spatial patterns of spring leaf phenology, but tended to underestimate the temporal variations in responding to temperature warming, showing low interannual variability (IAV) and temperature sensitivity (ST). In contrast, the performances of Vegetation Integrated SImulator for Trace Gases were the best in modeling IAV and ST. BIOME3, Lund-Potsdam-Jena model, Joint UK Land Environment Simulator, BioGeochemical Cycles, Community Land Model, Integrated Biosphere Simulator, and Commonwealth Scientific and Industrial Research Organisation Atmosphere Biosphere Land Exchange Model failed to reproduce both the spatial and temporal patterns. Using temperature series (1960–2100) form Coupled Model Intercomparison Project Number 6 scenarios to force the 10 phenology modules, our results highlighted large uncertainties in predicting spring leaf phenology changes with the warming climate, and more work is required to deal with the deficiencies of phenology model parameters and algorithms.
| Sanford, Gregg R.; Jackson, Randall D.; Rui, Yichao; Kucharik, Christopher J.: Land use-land cover gradient demonstrates the importance of perennial grasslands with intact soils for building soil carbon in the fertile Mollisols of the North Central US. In: Geoderma, vol. 418, pp. 115854, 2022, ISSN: 0016-7061. (Type: Journal Article | | )|
The impact of land use change and agricultural management on the cycling of soil organic carbon (SOC) is not well understood, limiting our ability to manage for, and accurately model, soil carbon changes at both local and regional scales. To address this issue, we combined long-term soil incubations with acid-hydrolysis and dry combustion to parse total SOC (Ct) into three operationally defined SOC pools (active, slow, and recalcitrant) from 9 long-term sites with varying land uses on current and former tallgrass prairie soil. Land uses represented a gradient of soil disturbance histories including remnant prairie, restored prairie, grazed pasture, annual crop rotations, and continuous maize. Dry combustion was used to estimate total carbon (Ct, physical), while acid hydrolysis of both the active (Ca) and slow (Cs) pools was used to estimate a recalcitrant carbon pool (Cr, chemical). Non-linear modeling of CO2 efflux data from the long-term incubations was then used to estimate Ca, and the decomposition rates of both Ca and Cs (ka and kr, biological). The size of the slow pools Cs was then defined mathematically as Ct-(Ca + Cr). Remnant prairie had the highest Ct, while cool-season pasture and a 35-y-old restored prairie had higher Ct than the other agricultural systems. All agricultural systems, including pasture, had the highest fraction of Ct as Cr (∼50%), whose mean residence time (MRT) in these soils is ≥500 years (Paul et al., 2001a) demonstrating that this fraction persists, while the more labile fractions were lost over the course of a few months (Ca) to a few decades (Cs) as a result of tillage-intensive agriculture. The two- to four-decade MRT time of Cs indicated a pool likely to be more responsive to the 20 to 40 years of land-use practices used at some of the sites. The Cs pool was largest in the remnant- and 35-y-old prairies indicating significant C accrual and stabilization compared to the agricultural ecosystems. Interestingly, the remnant prairie maintained the highest Ca pool as well, demonstrating the strong connection between the quantity of fresh C inputs and the potential for long-term C stabilization and accrual. The accumulation of C in active (≈labile) pools as a first step toward long-term stabilization highlights the tenuous nature of early carbon gains, which can be quickly lost in response to climate change or poor management.
| Vavrus, Stephen J; Kucharik, Christopher J; He, Feng; Kutzbach, John E; Ruddiman, William F: Did agriculture beget agriculture during the past several millennia?. In: The Holocene, vol. 32, no. 7, pp. 680-689, 2022. (Type: Journal Article | | )|
The Early Anthropogenic Hypothesis posits that carbon emissions from ancient farming caused global warming by raising greenhouse gas concentrations (GHG) during the late-Holocene, in contrast to declining GHG during prior interglacials. Here, we explore whether this hypothesized pre-industrial anthropogenic climate change also fostered agriculture by creating more favorable growing conditions. We investigate this question using transient GCM experiments and the Cultivation Suitability Index, CSI, which quantifies farming potential based on climatic and soil factors. The Community Earth System Model (CESM) simulated the climate of the last 6000 years under two alternative forcing scenarios: (1) ACTUAL: orbital variations, historical land cover change, and observed GHG increase; and (2) NATURAL: orbital variations, fixed (natural) land cover, and expected natural GHG decline. The CSI was computed using CESM model output and observed soil properties. Ancient land clearance affected the simulated climate both biogeochemically (via carbon emissions) and biogeophysically (altered surface albedo and land-atmosphere energy fluxes). Biogeochemical effects generally dominated, as evidenced by a warmer (and slightly wetter) global climate in ACTUAL versus NATURAL by year 1850. But a few regions were cooler in ACTUAL, especially interior Eurasia during winter-spring, due to a higher surface albedo from cropland. The expansion of agriculture generally mitigated the orbitally induced decline in cultivation potential in boreal extratropics but worsened it in low latitudes. Our results suggest that ancient farming may have thus promoted a “push-pull” migration during the late-Holocene by inducing climate changes that encouraged a northward spread of agriculture.
| Heineman, Emily Marrs; Kucharik, Christopher J.: Characterizing Dominant Field-Scale Cropping Sequences for a Potato and Vegetable Growing Region in Central Wisconsin. In: Land, vol. 11, no. 2, 2022, ISSN: 2073-445X. (Type: Journal Article | | )|
Crop rotations are known to improve soil health by replenishing lost nutrients, increasing organic matter, improving microbial activity, and reducing disease risk and weed pressure. We characterized the spatial distribution of crops and dominant field-scale cropping sequences from 2008 to 2019 for the Wisconsin Central Sands (WCS) region, a major producer of potato and vegetables in the U.S. The dominant two- and three-year rotations were determined, with an additional focus on assessing regional potato rotation management. Our results suggest corn and soybean are the two most widely planted crops, occurring on 67% and 36% of all agricultural land at least once during the study period. The most frequent two- and three-year crop rotations include corn, soybean, alfalfa, sweet corn, potato, and beans, with continuous corn being the most dominant two- and three-year rotations (13.2% and 8.5% of agricultural land, respectively). While four- and five-year rotations for potato are recommended to combat pest and disease pressure, 23.2% and 65.9% of potato fields returned to that crop in rotation after two and three years, respectively. Furthermore, 5.6% of potato fields were planted continuously with that crop. Given potato’s high nitrogen (N) fertilizer requirements, the prevalence of sandy soils, and ongoing water quality issues, adopting more widespread use of four- or five-year rotations of potato with crops that require zero or less N fertilizer could reduce groundwater nitrate concentrations and improve water quality.
| Berg, Elizabeth; Kucharik, Christopher: The Dynamic Relationship between Air and Land Surface Temperature within the Madison, Wisconsin Urban Heat Island. In: Remote Sensing, vol. 14, no. 1, 2022, ISSN: 2072-4292. (Type: Journal Article | | )|
The urban heat island (UHI) effect, the phenomenon by which cities are warmer than rural surroundings, is increasingly important in a rapidly urbanizing and warming world, but fine-scale differences in temperature within cities are difficult to observe accurately. Networks of air temperature (Tair) sensors rarely offer the spatial density needed to capture neighborhood-level disparities in warming, while satellite measures of land surface temperature (LST) do not reflect the air temperatures that people physically experience. This analysis combines both Tair measurements recorded by a spatially-dense stationary sensor network in Dane County, Wisconsin, and remotely-sensed measurements of LST over the same area—to improve the use and interpretation of LST in UHI studies. The data analyzed span three summer months (June, July, and August) and eight years (2012–2019). Overall, Tair and LST displayed greater agreement in spatial distribution than in magnitude. The relationship between day of the year and correlation was fit to a parabolic curve (R2 = 0.76
| Turlej, Contributors: Konrad; Ozdogan, Mutlu; Radeloff, Volker C.: Mapping forest types over large areas with Landsat imagery partially affected by clouds and SLC gaps. In: International Journal of Applied Earth Observation and Geoinformation, vol. 107, pp. 102689, 2022, ISSN: 1569-8432. (Type: Journal Article | | )|
The ecosystem services that forests provide depend on tree species composition. Therefore, it is important to map not only forest extent and its dynamics, but also composition. Open access to Landsat has resulted in considerable improvements in remote sensing methods for mapping tree species, but most approaches fail to perform when there is a shortage of clear observations. Our main goal was to map forest composition with Landsat imagery in various data availability conditions, and to investigate how the missing data, either due to clouds or scan line problems affect classification accuracy. We tested a data driven approach that is based on multi-temporal analysis of the tree species’ spectral characteristics making it applicable to regional-scale mapping even when the gap-free imagery is not available. Our study area consisted of one Landsat footprint (26/28) located in Northern Wisconsin, USA. We selected this area because of numerous tree species (23), heterogenic composition of forests where the majority of stands are mixed, and availability of high-quality reference data. We quantified how classification accuracy at the species level was affected by a) the amount of missing data due to cloud cover and Scanning Line Corrector (SLC) gaps, b) the number of acquisitions, and c) the seasonal availability of images. We applied a decision tree classifier, capable of handling missing data to both single- and a three-year Landsat-7 and Landsat-8 observations. We classified the dominant tree species in each pixel and grouped results to forest stands to match our reference data. Our results show four major findings. First, producer’s and user’s accuracies range from 46.2% to 96.2% and from 59.9% to 93.7%, respectively for the most abundant forest types in the study area (all types covering greater than 2% of the forest area). Second, all tree species were mapped with overall accuracy above 70% even in when we restricted our data set to images having gaps larger than 30% of the study area. Third, the classification accuracy improved with more acquisitions, especially when images were available for the fall, spring, and summer. Finally, producer’s accuracies for pure-stands were higher than those for mixed stands by 10 to 30 percentage points. We conclude that inclusion of Landsat imagery with missing data allows to map forest types with accuracies that previously could be achieved only for those rare years for which several gap-free images were available. The approach presented here is directly applicable to Landsat-like observations and derived products such as seasonal composites and temporal statistics that miss 30% or more of the data for any single date to develop forest composition maps that are important for both forest management and ecology.