Pre-Programming Thermal Sensors Improves Detection During Drone-Based Nocturnal Wildlife Surveys in Warm Weather Lori Massey, Aaron M. Foley, Jeremy Baumgardt, Randy W. DeYoung, Humberto L. Perotto-Baldivieso Drones, 2026 Improvements in thermal infrared imaging provide new opportunities for drone-based wildlife surveys. The use of thermal sensors can be limited by ambient temperatures and vegetation cover, which can limit opportunities to survey during optimal biological seasons. Pre-programming isotherm settings in thermal cameras has the potential to allow surveys during warmer environmental conditions. We evaluated night-time surveys of white-tailed deer (Odocoileus virginianus) using isotherm settings in a 102 ha enclosed property in South Texas during February (winter) and July (summer) 2022. Detection probabilities were 0.84 and 0.65 during winter and summer, respectively. Percent woody cover was 48.1% and 60.7% during these seasons, respectively. The seasonal pattern in detection probabilities met expectations in terms of visibility bias caused by canopy cover. Despite different detection probabilities among seasons, population estimates were similar because distance sampling accounted for visibility bias. The use of isotherm settings allowed us to survey during temperatures previously thought to be too warm for ideal contrast (~21 °C vs. 30 °C), which provides more opportunities to survey during biologically important seasons typically associated with warm temperatures (i.e., fawning and antlerogenesis). We recommend the use of distance sampling methods to evaluate and correct for visibility bias during thermal-based drone surveys because detections of focal species may vary with vegetation.
Developing Large-Scale Pasture Approaches to Quantify Forage Mass in Rangelands Using Drones Michael T. Page, Humberto L. Perotto-Baldivieso, J. Alfonso Ortega-S, Evan P. Tanner, Jay P. Angerer, Rider C. Combs, Bradley K. Johnston, Melaine Ramirez, Annalysa M. Camacho, Alexandria M. DiMaggio, Dwain Daniels, Tony Kimmet Rangeland Ecology and Management, 2025 The use of drones has increased in recent years for monitoring and managing rangelands. High-resolution cameras and improved sensors provide an opportunity to investigate pasture-scale sampling methodology as an operational approach to estimate forage mass on rangelands using canopy height models derived from drone data. Our objectives were (1) to compare double sampling and vegetation clipping methods with very fine 3D data derived from drone-based imagery, (2) to compare forage mass estimation between methods using different numbers of drone-derived samples, and (3) estimate time efficiency of each one of these methods. To accomplish this, we acquired drone imagery in a 1 060-ha pasture in the South Texas Plains ecoregion in June 2020. We used two different pixel sizes for the drone image acquisition: 1.5 cm (50 m above ground level [AGL]) and 3.0 cm (100 m AGL). We compared six forage mass sampling approaches: double sampling (DS-ground), vegetation clipping (VC-ground), drone-double sampling at 50 m (drone-DS50) and 100 m (drone-DS100) AGL, and drone-vegetation clipping at 50 m (drone-VC50) and 100 m (drone-VC100) AGL. We generated 100 and 500 digital samples per site (total 700 and 3500 digital samples) to compare our estimates. Simple linear regression analyses were used to evaluate relationships between drone derived vegetation volume and the forage mass derived from DS and VC. We compared three sampling sizes: 70 field-based quadrats, 700, and 3,500 digital samples. Drone-VC50 with 700 5818 ± 78 kg · ha -1 ) and 3,500 (5653 ± 34 kg · ha -1 ) samples provided the smallest forage mass estimations at a large-pasture scale. Number of samples.h -1 increased from 22 to 52 with the DS methods and 1.2 to 38 with the VC methods. Our results suggest that a combination of DS and VC with drone data collection could be a reliable approach for future drone-based forage estimation.
When the wild things are: Defining mammalian diel activity and plasticity Kadambari Devarajan, Mason Fidino, Zach J. Farris, Solny A. Adalsteinsson, Gabriel Andrade-Ponce, Julia L. Angstmann, Whitney Anthonysamy, Jesica Aquino, Addisu Asefa, Belen Avila, Larissa L. Bailey, Lyandra Maria de Sousa Barbosa, Marcela de Frias Barreto, Owain Barton, Chloe E. Bates, Mayara Guimarães Beltrão, Tori Bird, Elizabeth G. Biro, Francesco Bisi, Daniel Bohórquez, Mark Boyce, Justin S. Brashares, Grace Bullington, Phoebe Burns, Jessica Burr, Andrew R. Butler, Kendall L. Calhoun, Tien Trung Cao, Natalia Casado, Juan Camilo Cepeda-Duque, Jonathon D. Cepek, Adriano Garcia Chiarello, Merri Collins, Pedro Cordeiro-Estrela, Sebastian Costa, Giacomo Cremonesi, Bogdan Cristescu, Paula Cruz, Anna Carolina Figueiredo de Albuquerque, Carlos De Angelo, Cláudia Bueno de Campos, Liana Mara Mendes de Sena, Mario Di Bitetti, Douglas de Matos Dias, Duane Diefenbach, Tim S. Doherty, Thais P. dos Santos, Gabriela Teixeira Duarte, Timothy M. Eppley, John Erb, Carolina Franco Esteves, Bryn Evans, Maria L. M. Falcão, Hugo Fernandes-Ferreira, John R. Fieberg, Luiz Carlos Firmino de Souza Filho, Jason Fisher, Marie-Josee Fortin, George A. Gale, Travis Gallo, Laken S. Ganoe, Rony Garcia-Anleu, Kaitlyn M. Gaynor, Tiziana A. Gelmi-Candusso, Phillys N. Gichuru, Quimey Gomez, Austin M. Green, Luiza Neves Guimarães, Jeffrey D. Haight, Lavendar R. Harris, Zachary D. Hawn, Jordan Heiman, Huy Quoc Hoang, Sarah Huebner, Fabiola Iannarilli, María Eugenia Iezzi, Jacob S. Ivan, Kodi J. Jaspers, Mark J. Jordan, Jason Kamilar, Mamadou Kane, Mohammad Hosein Karimi, Marcella Kelly, Michel T. Kohl, William P. Kuvlesky, Andrew Ladle, Rachel N. Larson, Quy Tan Le, Duy Le, Van Son Le, Elizabeth W. Lehrer, Patrick E. Lendrum, Jesse Lewis, Andrés Link, Diego J. Lizcano, Jason V. Lombardi, Robert Long, Eva López-Tello, Camile Lugarini, David Lugo, Paula MacKay, Maria Madadi, Rodolfo Assis Magalhães, Seth B. Magle, Ludmila Hufnagel Regis Diniz Maia, Salvador Mandujano, Taisiia Marchenkova, Paulo Henrique Marinho, Laurie Marker, Julia Martinez Pardo, Adriano Martinoli, Rodrigo Lima Massara, Juliana Masseloux, Dina Matiukhina, Amy Mayer, Luis Mazariegos, Maureen R. McClung, Alex McInturff, Darby McPhail, Amy Mertl, Christopher R. Middaugh, David Miller, David Mills, Dale Miquelle, Vivianna Miritis, Remington J. Moll, Péter Molnár, Robert A. Montgomery, Toni Lyn Morelli, Alessio Mortelliti, Rachael I. Mueller, Anna S. Mukhacheva, Kayleigh Mullen, Asia Murphy, Vance Nepomuceno, Dusit Ngoprasert, An Nguyen, Thanh Van Nguyen, Van Thai Nguyen, Hoa Anh Nguyen Quang, Rob Nipko, Ana Clarissa Costa Nobre, Joseph Northrup, Megan A. Owen, Adriano Pereira Paglia, Meredith S. Palmer, Gabriela Palomo-Munoz, Lain E. Pardo, Chrystina Parks, Ana Maria de Oliveira Paschoal, Brent Patterson, Agustin Paviolo, Liba Pejchar, Mary E. Pendergast, Humberto L. Perotto-Baldivieso, Timofei Petrov, Mairi K. P. Poisson, Daiana Jeronimo Polli, Morteza Pourmirzai, Alexander Reebin, Katie R. Remine, Lindsey Rich, Christopher S. Richardson, Facundo Robino, Daniel G. Rocha, Fabiana Lopes Rocha, Flávio Henrique Guimarães Rodrigues, Adam T. Rohnke, Travis J. Ryan, Carmen M. Salsbury, Heather A. Sander, Nadia Maria da Cruz Santos-Cavalcante, Cagan H. Sekercioglu, Ivan Seryodkin, Dede Hendra Setiawan, Shabnam Shadloo, Mahsa Shahhosseini, Graeme Shannon, Catherine J. Shier, G. Bradley Smith, Tom Snyder, Rahel Sollmann, Kimberly L. Sparks, Kriangsak Sribuarod, Colleen C. St. Clair, Theodore Stankowich, Robert Steinmetz, Cassondra J. Stevenson, Sunarto Sunarto, Thilina D. Surasinghe, Svetlana V. Sutyrina, Ronald R. Swaisgood, Atie Taktehrani, Kanchan Thapa, Matthew Thorton, Andrew Tilker, Mathias W. Tobler, Van Bang Tran, Jody Tucker, Russell C. Van Horn, Juan S. Vargas-Soto, Karen L. Velásquez-C, Jan Venter, Eduardo M. Venticinque, Stijn Verschueren, Erin Wampole, Darcy J Watchorn, Oliver R. Wearn, Katherine C.B. Weiss, Alejandro Welschen, Febri Anggriawan Widodo, Jacque Williamson, Andreas Wilting, George Wittemyer, Arturo Zavaleta, Amanda J. Zellmer, Brian D. Gerber Science Advances, 2025 Circadian rhythms are a mechanism by which species adapt to environmental variability and fundamental to understanding species behavior. However, we lack data and a standardized framework to accurately assess and compare temporal activity for species during rapid ecological change. Through a global network representing 38 countries, we leveraged 8.9 million mammalian observations to create a library of 14,587 standardized diel activity estimates for 445 species. We found that less than half the species’ estimates were in agreement with diel classifications from the reference literature and that species commonly used more than one diel classification. Species diel activity was highly plastic when exposed to anthropogenic change. Furthermore, body size and distributional extent were strongly associated with whether a species is diurnal or nocturnal. Our findings provide essential knowledge of species behavior in an era of rapid global change and suggest the need for a new, quantitative framework that defines diel activity logically and consistently while capturing species plasticity.
Fine spatial scale assessment of structure and configuration of vegetation cover for northern bobwhites in grazed pastures J. Silverio Avila-Sanchez, Humberto L. Perotto-Baldivieso, Lori D. Massey, J. Alfonso Ortega-S, Leonard A. Brennan, Fidel Hernández Ecological Processes, 2024 Background Monitoring forage in livestock operations is critical to sustainable rangeland management of soil and ecological processes that provide both livestock and wildlife habitat. Traditional ground-based sampling methods have been widely used and provide valuable information; however, they are time-consuming, labor-intensive, and limited in their ability to capture larger extents of the spatial and temporal dynamics of rangeland ecosystems. Drones provide a solution to collect data to larger extents than field-based methods and with higher-resolution than traditional remote sensing platforms. Our objectives were to (1) assess the accuracy of vegetation cover height in grasses using drones, (2) quantify the spatial distribution of vegetation cover height in grazed and non-grazed pastures during the dormant (fall–winter) and growing seasons (spring–summer), and (3) evaluate the spatial distribution of vegetation cover height as a proxy for northern bobwhite (Colinus virginianus) habitat in South Texas. We achieved this by very fine scale drone-derived imagery and using class level landscape metrics to assess vegetation cover height configuration. Results Estimated heights from drone imagery had a significant relationship with the field height measurements in September (r2 = 0.83; growing season) and February (r2 = 0.77; dormant season). Growing season pasture maintained residual landscape habitat configuration adequate for bobwhites throughout the fall and winter of 2022–2023 following grazing. Dormant season pasture had an increase in bare ground cover, and a shift from many large patches of tall herbaceous cover (40–120 cm) to few large patches of low herbaceous cover (5–30 cm) (p < 0.05). Conclusions Drones provided high-resolution imagery that allowed us to assess the spatial and temporal changes of vertical herbaceous vegetation structure in a semi-arid rangeland subject to grazing. This study shows how drone imagery can be beneficial for wildlife conservation and management by providing insights into changes in fine-scale vegetation spatial and temporal heterogeneity from livestock grazing.
A multivariate approach to assessing landscape structure effects on wildlife crossing structure use Thomas J. Yamashita, Humberto L. Perotto-Baldivieso, David B. Wester, Kevin W. Ryer, Richard J. Kline, Michael E. Tewes, John H. Young, Jason V. Lombardi Ecological Processes, 2024 Background Complexity in landscape structure is often assessed using individual metrics related to ecological processes. However, this rarely incorporates important relationships among metrics and may miss landscape structure effects. Multivariate statistics provide techniques for assessing overall landscape structure effects. We assessed how multivariate statistics could be used to connect landscape structure with an ecological process [bobcat (Lynx rufus) wildlife crossing structure (WCS) use]. We tested how landscape structure at WCS sites compared to the surrounding landscape and how structure affected detections at WCS sites. Our study was conducted in Cameron County, Texas, USA where WCSs are in various stages of construction and monitoring. We used a classified land use/land cover map and aerial LiDAR to calculate configuration and density metrics at WCS and random sites. We created indices for configuration and density using principal components analysis to assess landscape structure effects on camera trap detections at WCSs. Results Landscape structure at WCSs did not differ from random locations. Wildlife crossing structure use increased with greater woody cover and decreased with increasing vegetation density. Our indices allowed identification of differences in how configuration and density impacted WCS use. Ordination methods helped identify individual contributions of landscape metrics to the overall landscape structure effect. Conclusions Wildlife crossing structures are permanent fixtures on landscapes, so selecting appropriate locations using broad-scale landscape structure likely increases target species use. Using indices of landscape structure provides planners with a more holistic approach to WCS placement and provides a more comprehensive picture of landscape pattern and process relationships.
Reproductive Capabilities of Female Nilgai (Boselaphus tragocamelus) in Southern Texas Megan M. Granger, Clayton D. Hilton, Scott E. Henke, Humberto L. Perotto-Baldivieso, Landon R. Schofield, Tyler A. Campbell Animals, 2024 Free-ranging nilgai antelope (Boselaphus tragocamelus) are an understudied species, both on their native ranges of India, Pakistan, and Nepal and on their introduced ranges in southern Texas. Basic data related to population sizes, survival, reproduction, and recruitment are needed throughout their range to inform management and conservation decisions. We collected nilgai fetuses from 3 ranches in southern Texas, including East Foundation’s El Sauz and Santa Rosa ranches, and the Norias Division of the King Ranch® from 2018–2021. We calculated the percentage of individuals that were pregnant in each of the sample years and overall. We determined monthly average, maximum, and minimum fetus length. Of 488 nilgai cows, we found 386 to be pregnant (79%) and 214 to be pregnant with twins (56%). We found nilgai cows as young as 1-year old to have fetuses and therefore to have reached sexual maturity. Sex ratios of fetuses during any sampling year did not differ. We found ample evidence supporting our hypothesis that nilgai are fecund on their introduced range of southern Texas. To prevent nilgai overpopulation and associated problems, harvest management strategies should be implemented, specifically on nilgai cows.
Evaluation of drone surveys for ungulates in southwestern rangelands Jesse Blum, Aaron M. Foley, Randy W. DeYoung, David G. Hewitt, Jeremy Baumgardt, Mickey W. Hellickson, Humberto L. Perotto‐Baldivieso Wildlife Society Bulletin, 2024 Drone platforms are increasingly used for aerial wildlife surveys, but the validity of population counts has not been fully evaluated in all environments. Aerial surveys generally undercount the true population size and one must estimate detection probability (p) to correct for missed individuals. Detection probability for visual observers is influenced by vegetation and terrain characteristics, but the use of thermal cameras as the observer may also introduce additional factors influencing detection probability. We conducted diurnal, thermal‐based drone surveys for ungulates during February–April 2020 in South Texas, USA, on sites with varying degrees of woody cover and terrain. We examined histograms of georeferenced perpendicular distances to determine the effect of habitat on detection probabilities. We also examined precision in population estimates and variation in repeated surveys. Finally, we compared drone population estimates to independent estimates derived from helicopter, spotlight, and trail‐camera surveys. Distributions of perpendicular distances from the transect were affected by habitat characteristics. A flat grassland site had relatively few detections near the transect because thermal (solar) reflectance in the center of the footage obscured detections. A hilly brushy site had a uniform p (1.00) but resulted in a severe undercount due to the inability of the drone to follow contours of hills. The flat brushy site had a lower p (0.63), indicating visibility bias. Two additional flat, brushy sites were surveyed repeatedly (n = 5 and 9 surveys, respectively). All combinations of up to 3 repeated surveys were pooled to meet the recommended minimum number of detections for distance sampling analyses (≥60 detections). Population estimates had acceptable precision (CV ≤ 20%) 80.7% of the time and variation among repeated surveys was acceptable (CV = 9% and 23%, respectively). Drone‐based population estimates were comparable with estimates generated from corrected helicopter, spotlight, and trail‐camera surveys. Overall, diurnal drone surveys can generate population estimates for large ungulates on southwestern rangelands after accounting for visibility bias, but may be limited by terrain and thermal conditions.
Evaluating soil erosion and runoff dynamics in a humid subtropic, low stream order, southern plains watershed from cultivation and solar farm development Luis Mier-Valderrama, Julianna Leal, Humberto L. Perotto-Baldivieso, Brent Hedquist, Hector M. Menendez, Ambrose Anoruo, Benjamin L. Turner International Soil and Water Conservation Research, 2024 Much work has been done to understand and improve soil and water conservation where agriculture has driven land use intensification. Less is known about soil- and water-related impacts from intensification driven by solar farming, especially at watershed-scales. Here we employed Hydrologic Engineering Center's Hydrologic Modeling System (HEC-HMS) to model Pond Creek, a rural watershed in Texas, USA. Land use is primarily crop cultivation and secondarily pasture for cattle grazing. Presently, several industrial-scale projects are planned to convert ≈15–30% of Pond Creek from agriculture to solar farms. The model was parameterized using public data sources and information from local stakeholders, then calibrated to several historical precipitation events. Experiments were conducted by varying precipitation depth, duration, and land uses: native vegetation pre-cultivation (control), cultivation (current), current conditions with 15% solar farm conversion (solar), and current conditions with 30% solar farm conversion (solar x2). Shifting to solar farming led to significant increases in cumulative sediment load (+12%–30%), with no significant differences in peak discharge rate changes (+0.38%–4%). Comparison to soil loss tolerance values showed current and solar treatment erosion rates exceeded tolerance values between 0.17 and 2.29 tons per hectare and all treatments were significantly different than the native treatment. We discuss high leverage strategies applicable to solar farm development sites as well as watersheds where they reside. Accelerating demand for land for renewable energy such as solar farming warrants greater attention from the soil and water conservation community to anticipate and mitigate impacts across landscapes.
Evaluating Mesquite Distribution Using Unpiloted Aerial Vehicles and Satellite Imagery Michael T. Page, Humberto L. Perotto-Baldivieso, J. Alfonso Ortega-S, Evan P. Tanner, Jay P. Angerer, Rider C. Combs, Annalysa M. Camacho, Melaine Ramirez, Victoria Cavazos, Hunter Carroll, Kiri Baca, Dwain Daniels, Tony Kimmet Rangeland Ecology and Management, 2022
Evolution of green space under rapid urban expansion in southeast Asian cities Amal Najihah Muhamad Nor, Hasifah Abdul Aziz, Siti Aisyah Nawawi, Rohazaini Muhammad Jamil, Muhamad Azahar Abas, Kamarul Ariffin Hambali, Abdul Hafidz Yusoff, Norfadhilah Ibrahim, Nur Hairunnisa Rafaai, Ron Corstanje, Jim Harris, Darren Grafius, Humberto L. Perotto-Baldivieso Sustainability Switzerland, 2021
Landscape patterns of ocelot–vehicle collision sites AnnMarie Blackburn, C. Jane Anderson, Amanda M. Veals, Michael E. Tewes, David B. Wester, John H. Young, Randy W. DeYoung, Humberto L. Perotto-Baldivieso Landscape Ecology, 2021
Raccoon roundworm as an occupational hazard to caregivers of captive wildlife Journal of Wildlife Rehabilitation, 2021
Effects of grazing pressure on plant species composition and water presence on bofedales in the Andes mountain range of Bolivia Alternativas Agropecuarias (ALTAGRO), La Paz, Bolivia, N. Cochi Machaca, B. Condori, Instituto Nacional de Innovación Agropecuaria y Forestal, La Paz, Bolivia, A. Rojas Pardo, Alternativas Agropecuarias (ALTAGRO), La Paz, Bolivia, F. Anthelme, UMR AMAP, IRD, CIRAD, CNRS, INRA, Université de Montpellier, Montpellier, France, Herbario Nacional de Bolivia, Universidad Mayor de San Andrés, La Paz, Bolivia, Museo Nacional de Historia Natural, La Paz, Bolivia, R.I. Meneses, Herbario Nacional de Bolivia, Universidad Mayor de San Andrés, La Paz, Bolivia, Museo Nacional de Historia Natural, La Paz, Bolivia, Universidad Católica del Norte, Programa de Doctorado en Antropología, San Pedro de Atacama, Chile, C.E. Weeda, King Ranch® Institute for Ranch Management, Texas A&M University - Kingsville, Kingsville, Texas, USA, H.L. Perotto-Baldivieso, Caesar Kleberg Wildlife Research Institute, Texas A&M University - Kingsville, Kingsville, Texas, USA Mires and Peat, 2018
Challenges and opportunities for the Bolivian Biodiversity Observation Network Miguel Fernández, Laetitia M. Navarro, Amira Apaza-Quevedo, Silvia C. Gallegos, Alexandra Marques, Carlos Zambrana-Torrelio, Florian Wolf, Healy Hamilton, Alvaro J. Aguilar-Kirigin, Luis F. Aguirre, Marcela Alvear, James Aparicio, Lilian Apaza-Vargas, Gabriel Arellano, Eric Armijo, Nataly Ascarrunz, Soraya Barrera, Stephan G. Beck, Héctor Cabrera-Condarco, Consuelo Campos-Villanueva, Leslie Cayola, N. Paola Flores-Saldana, Alfredo F. Fuentes, M. Carolina García-Lino, M. Isabel Gómez, Yara S. Higueras, Michael Kessler, Juan Carlos Ledezma, J. Miguel Limachi, Ramiro P. López, M. Isabel Loza, Manuel J. Macía, Rosa I. Meneses, Tatiana B. Miranda, A. Bruno Miranda-Calle, R. Fernando Molina-Rodriguez, Mónica Moraes R., M. Isabel Moya-Diaz, Mauricio Ocampo, Humberto L. Perotto-Baldivieso, Oscar Plata, Steffen Reichle, Kathia Rivero, Renate Seidel, Liliana Soria, Marcos F. Terán, Marisol Toledo, F. Santiago Zenteno-Ruiz, Henrique Miguel Pereira Biodiversity, 2015
Pre-Programming Thermal Sensors Improves Detection During Drone-Based Nocturnal Wildlife Surveys in Warm Weather L Massey, AM Foley, J Baumgardt, RW DeYoung, HL Perotto-Baldivieso Drones 10 (2), 127 , 2026 2026
In the heat of the night: temperature and vegetation structure disparity in habitat suitability for scaled quail KA Travis, CM McKinney, EP Tanner, AM Tanner, F Hernández, ... Journal of Thermal Biology, 104381 , 2026 2026
The future of northern bobwhites and urbanization in Texas, Oklahoma, and Louisiana KS Miller, AZ Okay, LA Brennan, XB Wu, MJ Peterson, H Hannusch, ... Discover Conservation 2 (1), 43 , 2025 2025
Remote Sensing of Drylands: An Overview HL Perotto-Baldivieso, KF Perez, JS Avila-Sanchez 2025
Developing large-scale pasture approaches to quantify forage mass in rangelands using drones MT Page, HL Perotto-Baldivieso, JA Ortega-S, EP Tanner, JP Angerer, ... Rangeland Ecology & Management 100, 111-120 , 2025 2025 Citations: 3
Thermal Imaging for Wildlife Applications HL Perotto-Baldivieso JOURNAL OF WILDLIFE MANAGEMENT 89 (3) , 2025 2025
Thermal Imaging for Wildlife Applications By Kayleigh Fawcett Williams, London, UK: Pelagic Publishing. 2024. pp. 148. $51.00 (paperback). ISBN 978‐1784273873 HL Perotto‐Baldivieso The Journal of Wildlife Management, e22730 , 2025 2025
An assessment of chemical control options for whitebrush (Aloysia gratissima) in South Texas KJ Pennartz, EP Tanner, MK Clayton, AD Falk, DB Wester, ... Rangelands 47 (2), 118-127 , 2025 2025 Citations: 1
When the wild things are: Defining mammalian diel activity and plasticity K Devarajan, M Fidino, ZJ Farris, SA Adalsteinsson, G Andrade-Ponce, ... Science Advances 11 (9), eado3843 , 2025 2025 Citations: 27
Temporal Relationships of Breeding Landbirds and Productivity on a Working Landscape JL Ortiz, AAT Conkey, ML Lipschutz, LA Brennan, DB Wester, ... Wild 2 (1), 4 , 2025 2025
Integrating drone technology into rangeland management: plants, livestock, and wildlife HL Perotto-Baldivieso, KF Perez, DJ Goodwin, JS Avila-Sanchez, ... XII International Rangeland Congress 12, 538-543 , 2025 2025
Landscape dynamics of floodplain rangelands under different management units on a ranch in the Pantanal, Brazil. SA SANTOS, H PEROTTO-BALDIVIESO, BMA SORIANO 2025
Determining the age classes of free-ranging female nilgai (Boselaphus tragocamelus) in southern Texas, USA MM Granger, CD Hilton, SE Henke, HL Perotto-Baldivieso, LR Schofield, ... Journal of Wildlife Science (JWLS) 1 (3), 135-140 , 2024 2024
A multivariate approach to assessing landscape structure effects on wildlife crossing structure use TJ Yamashita, HL Perotto-Baldivieso, DB Wester, KW Ryer, RJ Kline, ... Ecological Processes 13 (1), 76 , 2024 2024 Citations: 7
Fine spatial scale assessment of structure and configuration of vegetation cover for northern bobwhites in grazed pastures JS Avila-Sanchez, HL Perotto-Baldivieso, LD Massey, JA Ortega-S, ... Ecological Processes 13 (1), 64 , 2024 2024 Citations: 4
Reproductive Capabilities of Female Nilgai ( Boselaphus tragocamelus ) in Southern Texas MM Granger, CD Hilton, SE Henke, HL Perotto-Baldivieso, LR Schofield, ... Animals 14 (15), 2150 , 2024 2024
Evaluation of drone surveys for ungulates in southwestern rangelands J Blum, AM Foley, RW DeYoung, DG Hewitt, J Baumgardt, MW Hellickson, ... Wildlife Society Bulletin 48 (2), e1515 , 2024 2024 Citations: 9
Evaluating soil erosion and runoff dynamics in a humid subtropic, low stream order, southern plains watershed from cultivation and solar farm development L Mier-Valderrama, J Leal, HL Perotto-Baldivieso, B Hedquist, ... International Soil and Water Conservation Research 12 (2), 432-445 , 2024 2024 Citations: 5
Evaluating the use of a thermal sensor to detect small ground-nesting birds in semi-arid environments during winter JS Avila-Sanchez, HL Perotto-Baldivieso, LD Massey, JA Ortega-S, ... Drones 8 (2), 64 , 2024 2024 Citations: 5
International Soil and Water Conservation Research L Mier-Valderrama, J Leal, HL Perotto-Baldivieso, B Hedquist, ... 2023
Are Flying-Foxes Coming to Town? Urbanisation of the Spectacled Flying-Fox ( Pteropus conspicillatus ) in Australia J Tait, HL Perotto-Baldivieso, A McKeown, DA Westcott PLoS one 9 (10), e109810 , 2014 2014 Citations: 105
Impact of deforestation on habitat connectivity thresholds for large carnivores in tropical forests MA Zemanova, HL Perotto-Baldivieso, EL Dickins, AB Gill, JP Leonard, ... Ecological Processes 6 (1), 21 , 2017 2017 Citations: 93
Evolution of green space under rapid urban expansion in Southeast Asian cities AN Muhamad Nor, H Abdul Aziz, SA Nawawi, R Muhammad Jamil, ... Sustainability 13 (21), 12024 , 2021 2021 Citations: 82
Distribution and interaction of white-tailed deer and cattle in a semi-arid grazing system SM Cooper, HL Perotto-Baldivieso, MK Owens, MG Meek, ... Agriculture, ecosystems & environment 127 (1-2), 85-92 , 2008 2008 Citations: 82
Detecting autocorrelation problems from GPS collar data in livestock studies HL Perotto-Baldivieso, SM Cooper, AF Cibils, M Figueroa-Pagán, ... Applied Animal Behaviour Science 136 (2-4), 117-125 , 2012 2012 Citations: 62
Co‐occurrence of bobcats, coyotes, and ocelots in Texas JV Lombardi, DI MacKenzie, ME Tewes, HL Perotto‐Baldivieso, JM Mata, ... Ecology and Evolution 10 (11), 4903-4917 , 2020 2020 Citations: 57
Invasive grasses in South Texas rangelands: historical perspectives and future directions JP Wied, HL Perotto-Baldivieso, AAT Conkey, LA Brennan, JM Mata Invasive Plant Science and Management 13 (2), 41-58 , 2020 2020 Citations: 57
Land cover trends in South Texas (1987–2050): potential implications for wild felids JV Lombardi, HL Perotto-Baldivieso, ME Tewes Remote Sensing 12 (4), 659 , 2020 2020 Citations: 55
Quantifying citrus tree health using true color UAV images BN Garza, V Ancona, J Enciso, HL Perotto-Baldivieso, M Kunta, ... Remote Sensing 12 (1), 170 , 2020 2020 Citations: 50
Springs on rangelands: runoff dynamics and influence of woody plant cover Y Huang, BP Wilcox, L Stern, H Perotto‐Baldivieso Hydrological Processes: An International Journal 20 (15), 3277-3288 , 2006 2006 Citations: 50
Spatial distribution, connectivity, and the influence of scale: habitat availability for the endangered Mona Island rock iguana HL Perotto-Baldivieso, E Meléndez-Ackerman, MA García, P Leimgruber, ... Biodiversity and Conservation 18 (4), 905-917 , 2009 2009 Citations: 47
Spatial structure of woody cover affects habitat use patterns of ocelots in Texas JV Lombardi, ME Tewes, HL Perotto-Baldivieso, JM Mata, TA Campbell Mammal Research 65 (3), 555-563 , 2020 2020 Citations: 42
Steepland resources: characteristics, stability and micromorphology LR Drees, LP Wilding, PR Owens, B Wu, H Perotto, H Sierra Catena 54 (3), 619-636 , 2003 2003 Citations: 41
Assessment of available rangeland woody plant biomass with a terrestrial LIDAR system NW Ku, SC Popescu, RJ Ansley, HL Perotto-Baldivieso, AM Filippi Photogrammetric Engineering & Remote Sensing 78 (4), 349-361 , 2012 2012 Citations: 40
Flooding-induced landscape changes along dendritic stream networks and implications for wildlife habitat HL Perotto-Baldivieso, XB Wu, MJ Peterson, FE Smeins, NJ Silvy, ... Landscape and Urban Planning 99 (2), 115-122 , 2011 2011 Citations: 36
A pilot study to estimate forage mass from unmanned aerial vehicles in a semi-arid rangeland AM DiMaggio, HL Perotto-Baldivieso, JA Ortega-S, C Walther, ... Remote Sensing 12 (15), 2431 , 2020 2020 Citations: 35
The declining Ogallala aquifer and the future role of rangeland science on the North American High Plains EC Rhodes, HL Perotto-Baldivieso, EP Tanner, JP Angerer, WE Fox Rangeland Ecology & Management 87, 83-96 , 2023 2023 Citations: 32
Landscape patterns of ocelot–vehicle collision sites AM Blackburn, CJ Anderson, AM Veals, ME Tewes, DB Wester, ... Landscape Ecology 36 (2), 497-511 , 2021 2021 Citations: 31
Environmental and landscape influences on the spatial and temporal distribution of a cattle herd in a South Texas rangeland C Cheleuitte-Nieves, HL Perotto-Baldivieso, XB Wu, SM Cooper Ecological Processes 9 (1), 39 , 2020 2020 Citations: 31
