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USGS2021

Synoptic analysis of a decade of daily measurements of SO2 emission in the troposphere from volcanoes of the global ground-based Network for Observation of Volcanic and Atmospheric Change

Volcanic plumes are common and far-reaching manifestations of volcanic activity during and between eruptions. Observations of the rate of emission and composition of volcanic plumes are essential to recognize and, in some cases, predict the state of volcanic activity. Measurements of the size and location of the plumes are important to assess the impact of the emission from sporadic or localized events to persistent or widespread processes of climatic and environmental importance. These observations provide information on volatile budgets on Earth, chemical evolution of magmas, and atmospheric circulation and dynamics. Space-based observations during the last decades have given us a global view of Earth's volcanic emission, particularly of sulfur dioxide ( SO 2 ). Although none of the satellite missions were intended to be used for measurement of volcanic gas emission, specially adapted algorithms have produced time-averaged global emission budgets. These have confirmed that tropospheric plumes, produced from persistent degassing of weak sources, dominate the total emission of volcanic SO 2 . Although space-based observations have provided this global insight into some aspects of Earth's volcanism, it still has important limitations. The magnitude and short-term variability of lower-atmosphere emissions, historically less accessible from space, remain largely uncertain. Operational monitoring of volcanic plumes, at scales relevant for adequate surveillance, has been facilitated through the use of ground-based scanning differential optical absorption spectrometer (ScanDOAS) instruments since the beginning of this century, largely due to the coordinated effort of the Network for Observation of Volcanic and Atmospheric Change (NOVAC). In this study, we present a compilation of results of homogenized post-analysis of measurements of SO 2 flux and plume parameters obtained during the period March 2005 to January 2017 of 32 volcanoes in NOVAC. This inventory opens a window into the short-term emission patterns of a diverse set of volcanoes in terms of magma composition, geographical location, magnitude of emission, and style of eruptive activity. We find that passive volcanic degassing is by no means a stationary process in time and that large sub-daily variability is observed in the flux of volcanic gases, which has implications for emission budgets produced using short-term, sporadic observations. The use of a standard evaluation method allows for intercomparison between different volcanoes and between ground- and space-based measurements of the same volcanoes. The emission of several weakly degassing volcanoes, undetected by satellites, is presented for the first time. We also compare our results with those reported in the literature, providing ranges of variability in emission not accessible in the past. The open-access data repository introduced in this article will enable further exploitation of this unique dataset, with a focus on volcanological research, risk assessment, satellite-sensor validation, and improved quantification of the prevalent tropospheric component of global volcanic emission.

Earth System Science Data↗

USGS2025

Permafrost–wildfire interactions: active layer thickness estimates for paired burned and unburned sites in northern high latitudes

As the northern high-latitude permafrost zone experiences accelerated warming, permafrost has become vulnerable to widespread thaw. Simultaneously, wildfire activity across northern boreal forest and Arctic/subarctic tundra regions impacts permafrost stability through the combustion of insulating organic matter, vegetation, and post-fire changes in albedo. Efforts to synthesis the impacts of wildfire on permafrost are limited and are typically reliant on antecedent pre-fire conditions. To address this, we created the FireALT dataset by soliciting data contributions that included thaw depth measurements, site conditions, and fire event details with paired measurements at environmentally comparable burned and unburned sites. The solicitation resulted in 52 466 thaw depth measurements from 18 contributors across North America and Russia. Because thaw depths were taken at various times throughout the thawing season, we also estimated end-of-season active layer thickness (ALT) for each measurement using a modified version of the Stefan equation. Here, we describe our methods for collecting and quality-checking the data, estimating ALT, the data structure, strengths and limitations, and future research opportunities. The final dataset includes 48 669 ALT estimates with 32 attributes across 9446 plots and 157 burned–unburned pairs spanning Canada, Russia, and the United States. The data span fire events from 1900 to 2022 with measurements collected from 2001 to 2023. The time since fire ranges from 0 to 114 years. The FireALT dataset addresses a key challenge: the ability to assess impacts of wildfire on ALT when measurements are taken at various times throughout the thaw season depending on the time of field campaigns (typically June through August) by estimating ALT at the end-of-season maximum. This dataset can be used to address understudied research areas, particularly algorithm development, calibration, and validation for evolving process-based models as well as extrapolating across space and time, which could elucidate permafrost–wildfire interactions under accelerated warming across the high-northern-latitude permafrost zone. The FireALT dataset is available through the Arctic Data Center ( https://doi.org/10.18739/A2RN3092P , Talucci et al., 2024).

Arctic↗

USGS2017

Geoelectric monitoring at the Boulder magnetic observatory

Despite its importance to a range of applied and fundamental studies, and obvious parallels to a robust network of magnetic-field observatories, long-term geoelectric field monitoring is rarely performed. The installation of a new geoelectric monitoring system at the Boulder magnetic observatory of the US Geological Survey is summarized. Data from the system are expected, among other things, to be used for testing and validating algorithms for mapping North American geoelectric fields. An example time series of recorded electric and magnetic fields during a modest magnetic storm is presented. Based on our experience, we additionally present operational aspects of a successful geoelectric field monitoring system.

Colorado↗

USGS2019

A General Lake Model (GLM 3.0) for linking with high-frequency sensor data from the Global Lake Ecological Observatory Network (GLEON)

The General Lake Model (GLM) is a one-dimensional open-source code designed to simulate the hydrodynamics of lakes, reservoirs, and wetlands. GLM was developed to support the science needs of the Global Lake Ecological Observatory Network (GLEON), a network of researchers using sensors to understand lake functioning and address questions about how lakes around the world respond to climate and land use change. The scale and diversity of lake types, locations, and sizes, and the expanding observational datasets created the need for a robust community model of lake dynamics with sufficient flexibility to accommodate a range of scientific and management questions relevant to the GLEON community. This paper summarizes the scientific basis and numerical implementation of the model algorithms, including details of sub-models that simulate surface heat exchange and ice cover dynamics, vertical mixing, and inflow–outflow dynamics. We demonstrate the suitability of the model for different lake types that vary substantially in their morphology, hydrology, and climatic conditions. GLM supports a dynamic coupling with biogeochemical and ecological modelling libraries for integrated simulations of water quality and ecosystem health, and options for integration with other environmental models are outlined. Finally, we discuss utilities for the analysis of model outputs and uncertainty assessments, model operation within a distributed cloud-computing environment, and as a tool to support the learning of network participants.

Geoscientific Model Development↗

USGS2016

Parameter regionalization of a monthly water balance model for the conterminous United States

A parameter regionalization scheme to transfer parameter values from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash–Sutcliffe efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.

Hydrology and Earth System Sciences↗

USGS2017

Correcting spacecraft jitter in HiRISE images

Mechanical oscillations or vibrations on spacecraft, also called pointing jitter, cause geometric distortions and/or smear in high resolution digital images acquired from orbit. Geometric distortion is especially a problem with pushbroom type sensors, such as the High Resolution Imaging Science Experiment (HiRISE) instrument on board the Mars Reconnaissance Orbiter (MRO). Geometric distortions occur at a range of frequencies that may not be obvious in the image products, but can cause problems with stereo image correlation in the production of digital elevation models, and in measuring surface changes over time in orthorectified images. The HiRISE focal plane comprises a staggered array of fourteen charge-coupled devices (CCDs) with pixel IFOV of 1 microradian. The high spatial resolution of HiRISE makes it both sensitive to, and an excellent recorder of jitter. We present an algorithm using Fourier analysis to resolve the jitter function for a HiRISE image that is then used to update instrument pointing information to remove geometric distortions from the image. Implementation of the jitter analysis and image correction is performed on selected HiRISE images. Resulting corrected images and updated pointing information are made available to the public. Results show marked reduction of geometric distortions. This work has applications to similar cameras operating now, and to the design of future instruments (such as the Europa Imaging System).

The International Archives of the Photogrammetry, ↗

USGS2017

Community tools for cartographic and photogrammetric processing of Mars Express HRSC images

The High Resolution Stereo Camera (HRSC) on the Mars Express orbiter (Neukum et al. 2004) is a multi-line pushbroom scanner that can obtain stereo and color coverage of targets in a single overpass, with pixel scales as small as 10 m at periapsis. Since commencing operations in 2004 it has imaged ~ 77 % of Mars at 20 m/pixel or better. The instrument team uses the Video Image Communication And Retrieval (VICAR) software to produce and archive a range of data products from uncalibrated and radiometrically calibrated images to controlled digital topographic models (DTMs) and orthoimages and regional mosaics of DTM and orthophoto data (Gwinner et al. 2009; 2010b; 2016). Alternatives to this highly effective standard processing pipeline are nevertheless of interest to researchers who do not have access to the full VICAR suite and may wish to make topographic products or perform other (e. g., spectrophotometric) analyses prior to the release of the highest level products. We have therefore developed software to ingest HRSC images and model their geometry in the USGS Integrated Software for Imagers and Spectrometers (ISIS3), which can be used for data preparation, geodetic control, and analysis, and the commercial photogrammetric software SOCET SET (® BAE Systems; Miller and Walker 1993; 1995) which can be used for independent production of DTMs and orthoimages. The initial implementation of this capability utilized the then-current ISIS2 system and the generic pushbroom sensor model of SOCET SET, and was described in the DTM comparison of independent photogrammetric processing by different elements of the HRSC team (Heipke et al. 2007). A major drawback of this prototype was that neither software system then allowed for pushbroom images in which the exposure time changes from line to line. Except at periapsis, HRSC makes such timing changes every few hundred lines to accommodate changes of altitude and velocity in its elliptical orbit. As a result, it was necessary to split observations into blocks of constant exposure time, greatly increasing the effort needed to control the images and collect DTMs. Here, we describe a substantially improved HRSC processing capability that incorporates sensor models with varying line timing in the current ISIS3 system (Sides 2017) and SOCET SET. This enormously reduces the work effort for processing most images and eliminates the artifacts that arose from segmenting them. In addition, the software takes advantage of the continuously evolving capabilities of ISIS3 and the improved image matching module NGATE (Next Generation Automatic Terrain Extraction, incorporating area and feature based algorithms, multi-image and multi-direction matching) of SOCET SET, thus greatly reducing the need for manual editing of DTM errors. We have also developed a procedure for geodetically controlling the images to Mars Orbiter Laser Altimeter (MOLA) data by registering a preliminary stereo topographic model to MOLA by using the point cloud alignment ( pc_align ) function of the NASA Ames Stereo Pipeline (ASP; Moratto et al. 2010). This effectively converts inter-image tiepoints into ground control points in the MOLA coordinate system. The result is improved absolute accuracy and a significant reduction in work effort relative to manual measurement of ground control. The ISIS and ASP software used are freely available; SOCET SET, is a commercial product. By the end of 2017 we expect to have ported our SOCET SET HRSC sensor model to the Community Sensor Model (CSM; Community Sensor Model Working Group 2010; Hare and Kirk 2017) standard utilized by the successor photogrammetric system SOCET GXP that is currently offered by BAE. In early 2018, we are also working with BAE to release the CSM source code under a BSD or MIT open source license.

The International Archives of the Photogrammetry, ↗

USGS2021

Further adventures in Mars DTM quality: Smoothing errors, sharpening details

We have used high-precision, high-resolution digital terrain models (DTMs) of the NASA Mars Science Laboratory (MSL) and Mars 2020 rover landing sites based on mosaicked images from the Mars Reconnaissance Orbiter High Resolution Imaging Science Experiment (MRO HiRISE) camera as a reference data set to evaluate DTMs based on Mars Express High Resolution Stereo Camera (MEX HRSC) images. The Next Generation Automatic Terrain Extraction (NGATE) matcher in the SOCET SET/GXP † commercial photogrammetric system produces DTMs with relatively good (small) horizontal resolution but high error, and results are terrain dependent, with poorer resolution and smaller errors on smoother surfaces. Multiple approaches to smoothing the NGATE DTMs give very similar tradeoffs between resolution and error. Smoothing the NGATE DTMs with a single pass of an area-based matcher, which has been the standard approach to generating planetary DTMs at the U.S. Geological Survey (USGS) to date is probably near-optimal in terms of both combined resolution-error performance and local slope estimation, but smoothing with a 5x5 lowpass filter performs as well or better. DTMs from the HRSC team processing pipeline fall within this same trade space but are less sensitive to terrain roughness. DTMs produced with the Ames Stereo Pipeline also fall in this space at resolutions intermediate between NGATE and the team pipeline. Although DTM resolution and error each vary by a factor of two, their product is much more consistent, varying by <20% across multiple image sets and matching algorithms. Refinement of the stereo DTM by photoclinometry can yield significant quantitative improvement in resolution and some improvement in error (improving their product by as much as a factor of two), provided that albedo variations over distances smaller than the stereo DTM resolution are not too severe.

Conference Paper↗

USGS2022

Comparison of Digital Terrain Models from two photoclinometry methods

We evaluate the horizontal resolution and vertical precision for digital topographic models (DTMs) of the Moon derived from image radiance information, a process known as photoclinometry (PC) or shape-from-shading (SfS). We use the implementations in two available planetary image processing software systems, single image PC in the U.S. Geological Survey Integrated Software for Imagers and Spectrometers (ISIS) system, and multi-image SfS in the Ames Stereo Pipeline (ASP), and test results obtained with and without use of a starting solution from stereo, with single and multiple images, and for varying illumination conditions. To obtain the higher quality reference DTMs against which the products can be evaluated, we derived DTMs by stereoanalysis of Lunar Reconnaissance Orbiter Narrow-Angle Camera (LROC NAC) images at their native pixel spacing of ∼0.5 m, then produced a 16-m/post stereo DTM from images downsampled to 4 m/pixel and refined it with images at 16 m/pixel. When used with a single image, both algorithms improved resolution (by a factor of 1.4 for PC and 2.4 for SfS compared to stereo). An albedo map produced in ISIS by ratioing the image to a simulation based on the stereo DTM was well correlated with one output by SfS. The albedo correction was crucial for PC with ∼60° incidence but not at ∼80°. DTMs produced by PC and SfS without a starting stereo DTM had larger errors but good detail, and could be useful for many applications. In SfS, it was necessary to increase smoothing to get a usable DTM when the weighting on an a priori DTM was reduced. Multi-image SfS including modeling of spatially varying albedo reduced vertical errors by factors of 1.5 or more compared to single-image SfS.

International Archives of the Photogrammetry, Remo↗

USGS2012

Burn severity mapping in Australia 2009

In 2009, the Victoria Department of Sustainability and Environment estimated approximately 430,000 hectares of Victoria Australia were burned by numerous bushfires. Burned Area Emergency Response (BAER) teams from the United States were deployed to Victoria to assist local fire managers. The U.S. Geological Survey Earth Resources Observation and Science Center (USGS/EROS) and U.S. Forest Service Remote Sensing Applications Center (USFS/RSAC) aided the support effort by providing satellite-derived "soil burn severity " maps for over 280,000 burned hectares. In the United States, BAER teams are assembled to make rapid assessments of burned lands to identify potential hazards to public health and property. An early step in the assessment process is the creation of a soil burn severity map used to identify hazard areas and prioritize treatment locations. These maps are developed primarily using Landsat satellite imagery and the differenced Normalized Burn Ratio (dNBR) algorithm.

Conference Paper↗

USGS2026

The damability function: A probabilistic approach to regional landslide dam susceptibility analysis applied to the Oregon Coast Range, USA

Landslides can dam rivers and require rapid response to mitigate catastrophic outburst floods. Here, we present a workflow to map landslide dam formation susceptibility at a regional scale. We define a probabilistic function that combines river valley width and landslide volume to efficiently determine the likelihood of a landslide dam or “damability”. We combine damability values with landslide susceptibility to estimate landslide dam susceptibility. The valley width measurements are automated using a new elevation threshold-based algorithm. Landslide volume is represented as a statistical distribution from mapped landslides. We validate and apply our approach to the Oregon Coast Range, USA and find that 36 % of river stretches exceed a dam potential threshold; these are in river headwaters and steeper terrain, which in this case correlate with more resistant lithologies. We also estimate volumes of the potential dammed lakes and find that most rivers with high dam susceptibility are less likely to impound large lakes because they have low drainage areas. However, widespread susceptibility, and the potential impacts from exceptionally large landslides, suggest that this hazard should be considered in the Pacific Northwest. The damability function workflow can ingest new data and be applied more broadly to assess future landslide dam hazards.

Oregon↗

USGS2025

Automated snow cover detection on mountain glaciers usingspaceborne imagery and machine learning

Tracking the extent of seasonal snow on glaciers over time is critical for assessing glacier vulnerability and the response of glacierized watersheds to climate change. Existing snow cover products do not reliably distinguish seasonal snow from glacier ice and firn, preventing their use for glacier snow cover detection. Despite previous efforts to classify glacier surface facies using machine learning on local scales, currently there is no published comparison of machine learning models for classifying glacier snow cover across different satellite image products. We present an automated snow detection workflow for mountain glaciers using supervised machine-learning-based image classifiers and Landsat 8 and 9, Sentinel-2, and PlanetScope satellite imagery. We develop the image classifiers by testing numerous machine learning algorithms with training and validation data from the U.S. Geological Survey Benchmark Glacier Project glaciers. The workflow produces daily to twice monthly time series of several glacier mass balance and snowmelt indicators (snow-covered area, accumulation area ratio, and seasonal snow line) from 2013 to present. Workflow performance is assessed by comparing automatically classified images and snow lines to manual interpretations at each glacier site. The image classifiers exhibit overall accuracies of 92%–98%, K scores of 84%–96%, and F scores of 93%–98% for all image products. The median difference between automatically and manually delineated median snow line altitudes is 31m (IQR of 73to0m)across all image products. The Sentinel-2 classifier (support vector machine) produces the most accurate glacier mass balance and snowmelt indicators and distinguishes snow from ice and f irn the most reliably. Although they are less accurate, the Landsat- and PlanetScope-derived estimates greatly enhance the temporal coverage of observations. The transient accumulation area ratio produces the least noisy time series, making it the most reliable indicator for characterizing seasonal snow trends. The temporally detailed accumulation area ratio time series reveal that the timing of minimum snow cover conditions varies by up to a month between Arctic (63°N) and midlatitude (48°N) sites, underscoring the potential for bias when estimating glacier minimum snow cover conditions from a single late-summer image. Widespread application of our automated snow detection workflow has the potential to improve regional assessments of glacier mass balance, land ice representations within Earth system models, water resources, and the impacts of climate change on snow cover across broad spatial scales.

The Cryosphere↗

USGS2015

Sensitivity of airborne geophysical data to sublacustrine and near-surface permafrost thaw

A coupled hydrogeophysical forward and inverse modeling approach is developed to illustrate the ability of frequency-domain airborne electromagnetic (AEM) data to characterize subsurface physical properties associated with sublacustrine permafrost thaw during lake-talik formation. Numerical modeling scenarios are evaluated that consider non-isothermal hydrologic responses to variable forcing from different lake depths and for different hydrologic gradients. A novel physical property relationship connects the dynamic distribution of electrical resistivity to ice saturation and temperature outputs from the SUTRA groundwater simulator with freeze–thaw physics. The influence of lithology on electrical resistivity is controlled by a surface conduction term in the physical property relationship. Resistivity models, which reflect changes in subsurface conditions, are used as inputs to simulate AEM data in order to explore the sensitivity of geophysical observations to permafrost thaw. Simulations of sublacustrine talik formation over a 1000-year period are modeled after conditions found in the Yukon Flats, Alaska. Synthetic AEM data are analyzed with a Bayesian Markov chain Monte Carlo algorithm that quantifies geophysical parameter uncertainty and resolution. Major lithological and permafrost features are well resolved by AEM data in the examples considered. The subtle geometry of partial ice saturation beneath lakes during talik formation cannot be resolved using AEM data, but the gross characteristics of sub-lake resistivity models reflect bulk changes in ice content and can identify the presence of a talik. A final synthetic example compares AEM and ground-based electromagnetic responses for their ability to resolve shallow permafrost and thaw features in the upper 1–2 m below ground outside the lake margin.

The Cryosphere↗

USGS2014

Semi-automated identification of leopard frogs

Principal component analysis is used to implement a semi-automatic recognition system to identify recaptured northern leopard frogs (Lithobates pipiens). Results of both open set and closed set experiments are given. The presented algorithm is shown to provide accurate identification of 209 individual leopard frogs from a total set of 1386 images.

Book↗

USGS2024

Software application for spectral mixture analysis for surveillance of harmful algal blooms (SMASH): A tool for identifying cyanobacteria genera from remotely sensed data

Remote sensing is often used to detect algae, but standard techniques do not provide information on the types of algae present or their potential to form a harmful algal bloom (HAB). We developed a framework for identifying algal genera based on reflectance: SMASH, short for Spectral Mixture Analysis for Surveillance of HABs. The Software Application for SMASH (SAS) was developed in MATLAB and makes use of a Multiple Endmember Spectral Mixture Analysis (MESMA) algorithm implemented in Python but packaged as a standalone executable. SAS includes functions for importing hyperspectral images, resampling spectral libraries, evaluating endmember spectral separability, performing MESMA, and generating various output data products.

Journal of Open Research Software (JORS)↗

USGS2023

Genomes & islands & evolution: Oh my!

A central question in evolutionary biology is how lineages quickly diversify to occupy different ecological niches, along with determining genomic factors that facilitate evolutionary change. Isolated, oceanic archipelagos are famous for adaptive radiations characterized by endemic, species-rich clades with substantial ecological variation, yet genome resources key to determining eco-evo processes are generally lacking. Here I present a comparison of the number of genome reference assemblies available (as of May 31, 2023) for three major eukaryotic lineages, briefly describe genome sequencing and benchmarking strategies, and highlight as a case study a genome assembly project for Bidens hawaiensis (Koʻokoʻolau, Asteraceae or Compositae; Coreopsidae), a member of a hexaploid Hawaiian plant adaptive radiation. The total number of plant genome references (1,394) was found to substantially lag the total number of genome references for animal (6,003) and fungi (4,400). Improvements to the quality of de novo assembled genomes are fueled by second- and third-generation long-read sequencing advancements, among other sequencing approaches. In conjunction, strategies to improve genome contiguity include optical maps, Hi-C chromatin capture, or trio binning. Continual improvements to genome sequencing and assembly algorithms have brought within reach telomere-to-telomere genome assemblies, albeit this level of sequencing has to date only been achieved in a few cases. With improvements in sequencing techniques and per-base pair costs that continue to trend downward, the number of high-quality genomes is anticipated to continue to increase, leading to the filling in of taxonomic gaps and sampling of groups of taxa from under sampled geographic areas. Increasing the number of plant genome resources available for the study of island endemism could help to shed light on genome-phenome relationships and genome characteristics that have produced the stunning biological diversity that we now observe across the globe.

Capitulum↗

USGS2018

Density estimation of sound-producing terrestrial animals using single automatic acoustic recorders and distance sampling

Obtaining accurate information on the distribution, density, and abundance of animals is an important first step toward their conservation. Methodological approaches using automatic acoustic recorders for species that communicate acoustically are gaining increased interest because of their advantages over traditional sampling methods. In this study, we created and evaluated a protocol to estimate population density, which can be used to compute abundance of terrestrial sound-producing animals from single automatic acoustic recorders and using an automatic detection algorithm. The protocol uses cue rates from the target species, environmental conditions, and an estimate of the distance of the individual to the recorder based on the power of the received sound. We applied our protocol to estimate the density of a Hawaiian forest bird species (Hawaiˊi ˊAmakihi [ Chlorodrepanis virens ]) on the island of Hawaiˊi, USA. We validated our approach by comparing our density estimates with those calculated at the same stations using a traditional point-transect distance sampling method based on human observations. Overall density estimates based on recorded signals were lower than those based on human observations, but 95% confidence intervals of the two density estimates overlapped. This study presents a relatively simple but effective protocol for estimating animal density using single automatic acoustic recorders. Our protocol may easily be adapted to other sound-emitting terrestrial animals.

Avian Conservation and Ecology↗

USGS2014

Optimization in the utility maximization framework for conservation planning: a comparison of solution procedures in a study of multifunctional agriculture

Quantitative methods of spatial conservation prioritization have traditionally been applied to issues in conservation biology and reserve design, though their use in other types of natural resource management is growing. The utility maximization problem is one form of a covering problem where multiple criteria can represent the expected social benefits of conservation action. This approach allows flexibility with a problem formulation that is more general than typical reserve design problems, though the solution methods are very similar. However, few studies have addressed optimization in utility maximization problems for conservation planning, and the effect of solution procedure is largely unquantified. Therefore, this study mapped five criteria describing elements of multifunctional agriculture to determine a hypothetical conservation resource allocation plan for agricultural land conservation in the Central Valley of CA, USA. We compared solution procedures within the utility maximization framework to determine the difference between an open source integer programming approach and a greedy heuristic, and find gains from optimization of up to 12%. We also model land availability for conservation action as a stochastic process and determine the decline in total utility compared to the globally optimal set using both solution algorithms. Our results are comparable to other studies illustrating the benefits of optimization for different conservation planning problems, and highlight the importance of maximizing the effectiveness of limited funding for conservation and natural resource management.

California↗