Browsing by Author "Portillo-Quintero, Carlos (TTU)"
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Item Can terrestrial laser scanners (TLSs) and hemispherical photographs predict tropical dry forest succession with liana abundance?(2017) Sánchez-Azofeifa, Gerardo Arturo; Guzmán-Quesada, J. Antonio; Vega-Araya, Mauricio; Campos-Vargas, Carlos; Durán, Sandra Milena; D'Souza, Nikhil; Gianoli, Thomas; Portillo-Quintero, Carlos (TTU); Sharp, IainTropical dry forests (TDFs) are ecosystems with long drought periods, a mean temperature of 25gdeg;C, a mean annual precipitation that ranges from 900 to 2000ĝ€mm, and that possess a high abundance of deciduous species (trees and lianas). What remains of the original extent of TDFs in the Americas remains highly fragmented and at different levels of ecological succession. It is estimated that one of the main fingerprints left by global environmental and climate change in tropical environments is an increase in liana coverage. Lianas are non-structural elements of the forest canopy that eventually kill their host trees. In this paper we evaluate the use of a terrestrial laser scanner (TLS) in combination with hemispherical photographs (HPs) to characterize changes in forest structure as a function of ecological succession and liana abundance. We deployed a TLS and HP system in 28 plots throughout secondary forests of different ages and with different levels of liana abundance. Using a canonical correlation analysis (CCA), we addressed how the VEGNET, a terrestrial laser scanner, and HPs could predict TDF structure. Likewise, using univariate analyses of correlations, we show how the liana abundance could affect the prediction of the forest structure. Our results suggest that TLSs and HPs can predict the differences in the forest structure at different successional stages but that these differences disappear as liana abundance increases. Therefore, in well known ecosystems such as the tropical dry forest of Costa Rica, these biases of prediction could be considered as structural effects of liana presence. This research contributes to the understanding of the potential effects of lianas in secondary dry forests and highlights the role of TLSs combined with HPs in monitoring structural changes in secondary TDFs.Item Efficacy of remote sensing technologies for burrow count estimates of a rare kangaroo rat(2024) Stuhler, John D.; Portillo-Quintero, Carlos (TTU); Goetze, Jim R. (TTU); Stevens, Richard D. (TTU)Effective management of rare species requires an understanding of spatial variation in abundance, which is challenging to estimate. We tested the efficacy of high-resolution imagery to detect burrows of the Texas kangaroo rat (TKR; Dipodomys elator) as a means of estimating abundance across its geographic range. Specifically, we estimated burrow counts using an Unmanned Aerial System (UAS) to collect data from very high-resolution Red–Green–Blue (RGB) imagery and estimate digital elevation (2.5-mm pixel resolution) over active and inactive burrows located on mesquite mounds and anthropogenic features (roadsides, fences, etc.). In 2018, we identified 26 burrow locations on a private ranch in Wichita County, Texas, USA, and characterized burrows based on topography and vegetation density. We found that TKR burrows can only be identified with data of <5 cm pixel resolution, thus eliminating the possibility of using high-resolution imagery data currently available for Texas. Alternatively, we propose that the use of National Agriculture Imagery Program (NAIP) imagery at 0.5- and 0.6-m pixel resolution, in combination with resampled digital elevation data, can provide an effective means for identifying potential TKR burrow locations at the county level. We present 3 different approaches at the county and local scale that combine topographic and vegetation fractional cover information using a weighted overlay approach. The modeling approaches have strong predictive capabilities and can be integrated with UAS data for visual confirmation of active and inactive burrows. We concluded that very high-resolution imagery and topographic information at pixel resolutions <5 cm collected by airborne systems can effectively help locate active TKR burrows. However, to remain cost effective, upscaling to the county level will require reducing the sampling area to the most suitable habitat. Modeling approaches, such as those proposed in this study, can help effectively locate these sampling areas.Item Forest Clearing Dynamics and Its Relation to Remotely Sensed Carbon Density and Plant Species Diversity in the Puuc Biocultural State Reserve, Mexico(2023) Portillo-Quintero, Carlos (TTU); Hernandez-Stefanoni, Jose Luis; Dupuy, Juan ManuelThe Puuc Biocultural State Reserve (PBSR) is a unique model for tropical dry forest conservation in Mexico. Preserving forest biodiversity and carbon within the PBSR depends on maintaining low-impact productive activities coordinated by multiple communal and private landowners. In this study, we used state-of-the-art remote sensing data to investigate past spatial patterns in forest clearing dynamics and their relation to forest carbon density and forest plant species richness and diversity in the context of the forest conservation goals of the PBSR. We used a Landsat-based continuous change detection product for the 2000–2021 period and compared it to carbon density and tree species richness models generated from ALOS-2 PALSAR 2 imagery and national scale forest inventory data. The estimated error-adjusted area of detected annual forest clearings from the year 2000 until the year 2021 was 230,511 ha in total (±19,979 ha). The analysis of annual forest clearing frequency and area suggests that although forest clearing was significantly more intensive outside of the PBSR than within the PBSR during the entire 2000–2021 period, there is no evidence suggesting that the frequency and magnitude of forest clearing changed over the years after the creation of the PBSR in 2011. However, an emergent hotspot analysis shows that high spatiotemporal clustering of forest clearing events (hotspots) during the 2012–2021 period was less common than prior to 2011, and these more recent hotspots have been confined to areas outside the PBSR. After comparing forest clearing events to carbon density and tree species richness models, the results show that landowners outside the PBSR often clear forests with lower carbon density and species diversity than those inside the PBSR. This suggests that, compared to landowners outside the PBSR, landowners within the PBSR might be practicing longer fallow periods allowing forests to attain higher carbon density and tree species richness and hence better soil nutrient recovery after land abandonment. In conclusion, our results show that the PBSR effectively acted as a stabilizing forest management scheme during the 2012–2021 period, minimizing the impact of productive activities by lowering the frequency of forest clearing events and preserving late secondary forests within the PBSR. We recommend continuing efforts to provide alternative optimal field data collection strategies and modeling techniques to spatially predict key tropical forest attributes. Combining these models with continuous change detection datasets will allow for underlying ecological processes to be revealed and the generation of information better adapted to forest governance scales.Item Trends in Lesser Prairie-Chicken Habitat Extent and Distribution on the Southern High Plains(2022) Portillo-Quintero, Carlos (TTU); Grisham, Blake (TTU); Haukos, David; Boal, Clint W. (TTU); Hagen, Christian; Wan, Zhanming; Subedi, Mukti (TTU); Menkiti, NwasinachiThe lesser prairie-chicken (Tympanuchus pallidicinctus) is a species of prairie grouse that occupies grassland ecosystems in the Southern and Central High Plains of the Great Plains. Reduced abundance and occupied ranges have led to increased conservation efforts throughout the species’ range. Habitat loss is considered the predominant cause of these declines. In the Southern High Plains of Texas and New Mexico, lesser prairie-chicken habitat corresponds to the Sand Shinnery Oak Prairie Ecoregion, which is comprised of a mixture of sand shinnery oak (Quercus havardii)-dominated grasslands, sand sagebrush (Artemisia filifolia)-dominated grasslands, and mixed grasslands. In sand shinnery oak–grassland communities, conversion to row-crop agriculture, continuous unmanaged livestock grazing, restriction of natural fire, invasive plant species (e.g., mesquite (Prosopis spp.)), extensive use of herbicides, energy development, and a variety of other factors have also negatively affected ecosystem extent and function. We integrated historical maps and remote sensing-derived information to measure trends in the extent and geographical distribution of sand shinnery oak prairies in eastern New Mexico and northwest Texas. Potential lesser prairie-chicken habitat was reduced by 56% from a potential of 43,258 km2 to 18,908 km2 in ~115 years (since pre-settlement). Our assessment indicated both mixed grasslands and sand shinnery oak-dominated grasslands were transformed from large parcels of existing vegetation communities to urban settlements, row crops, roads, and industrial land uses by the 1970s. Currently, potential habitat is highly fragmented and restricted to isolated locations in Texas and New Mexico, with an increasing dominance in mixed grasslands, especially in the southeastern portion of the lesser prairie-chicken range. Sand shinnery oak-dominated grasslands have been declining rapidly, from 69% of its potential extent in 1985, 65% in 1995, 54% in 2005, to 42% in 2015. Mixed grasslands drastically declined to 50% of its potential distribution by 1985. Since then, it has been stable until the 2005–2015 period when it declined to 45% of its potential extent. Based on the 2015 assessment, the current potential habitat for lesser prairie-chicken is estimated at 18,908 km2 (1,890,800 ha or 4.6 million acres), where 13,126 km2 corresponds to mixed grasslands and 5782 km2 corresponds to sand shinnery oak-dominated grasslands.