Jonathan Pando Ocón

Bio: Jonathan Pando Ocón is an academic researcher from University of California, Los Angeles. The author has contributed to research in topics: Precipitation & Tropical and subtropical dry broadleaf forests. The author has an hindex of 2, co-authored 2 publications receiving 7 citations.

Global tropical dry forest extent and cover: A comparative study of bioclimatic definitions using two climatic data sets.

Abstract: There is a debate concerning the definition and extent of tropical dry forest biome and vegetation type at a global spatial scale. We identify the potential extent of the tropical dry forest biome based on bioclimatic definitions and climatic data sets to improve global estimates of distribution, cover, and change. We compared four bioclimatic definitions of the tropical dry forest biome–Murphy and Lugo, Food and Agriculture Organization (FAO), DryFlor, aridity index–using two climatic data sets: WorldClim and Climatologies at High-resolution for the Earth’s Land Surface Areas (CHELSA). We then compared each of the eight unique combinations of bioclimatic definitions and climatic data sets using 540 field plots identified as tropical dry forest from a literature search and evaluated the accuracy of World Wildlife Fund tropical and subtropical dry broadleaf forest ecoregions. We used the definition and climate data that most closely matched field data to calculate forest cover in 2000 and change from 2001 to 2020. Globally, there was low agreement (< 58%) between bioclimatic definitions and WWF ecoregions and only 40% of field plots fell within these ecoregions. FAO using CHELSA had the highest agreement with field plots (81%) and was not correlated with the biome extent. Using the FAO definition with CHELSA climatic data set, we estimate 4,931,414 km 2 of closed canopy (≥ 40% forest cover) tropical dry forest in 2000 and 4,369,695 km 2 in 2020 with a gross loss of 561,719 km 2 (11.4%) from 2001 to 2020. Tropical dry forest biome extent varies significantly based on bioclimatic definition used, with nearly half of all tropical dry forest vegetation missed when using ecoregion boundaries alone, especially in Africa. Using site-specific field validation, we find that the FAO definition using CHELSA provides an accurate, standard, and repeatable way to assess tropical dry forest cover and change at a global scale.

Leveraging the NEON Airborne Observation Platform for socio-environmental systems research

Abstract: SESYNC under National Science Foundation [DBI-1639145]; National Science FoundationNational Science Foundation (NSF); National Science Foundation through the NEON Program

More than surface temperature: mitigating thermal exposure in hyper-local land system

Abstract: ABSTRACT Regional land surface temperature (LST) maps derived from remote sensing data are most available to cities to assess and respond to heat. Yet, LST only captures one dimension of urban climate. This study investigates the extent to which remote sensing derived estimates of LST are a proxy for multiple climate variables at hyper-local scales (<10s of meters). We compare remotely sensed estimates of LST (RS-LST) to field and simulated LST, MRT, and air temperature (AT), in a neighborhood in Tucson, Arizona, USA. We find that LST, MRT, and ST follow different diurnal trends masked by RS-LST. We also find that three-dimensional urban design is a better predictor of MRT than two-dimensional land cover and albedo – a known determinant of RS-LST. Shade is a better predictor of both simulated LST and MRT than RS-LST. We conclude that RS-LST is not adequate for guiding heat mitigation at hyper-local scales in cities.

A Near Four-Decade Time Series Shows the Hawaiian Islands Have Been Browning Since the 1980s

Abstract: Abstract The Hawaiian Islands have been identified as a global biodiversity hotspot. We examine the Normalized Difference Vegetation Index (NDVI) using Climate Data Records products (0.05 × 0.05°) to identify significant differences in NDVI between neutral El Niño-Southern Oscillation years (1984, 2019) and significant long-term changes over the entire time series (1982–2019) for the Hawaiian Islands and six land cover classes. Overall, there has been a significant decline in NDVI (i.e., browning) across the Hawaiian Islands from 1982 to 2019 with the islands of Lāna’i and Hawai’i experiencing the greatest decreases in NDVI (≥44%). All land cover classes significantly decreased in NDVI for most months, especially during the wet season month of March. Native vegetation cover across all islands also experienced significant declines in NDVI, with the leeward, southwestern side of the island of Hawai’i experiencing the greatest declines. The long-term trends in the annual total precipitation and annual mean Palmer Drought Severity Index (PDSI) for 1982–2019 on the Hawaiian Islands show significant concurrent declines. Primarily positive correlations between the native ecosystem NDVI and precipitation imply that significant decreases in precipitation may exacerbate the decrease in NDVI of native ecosystems. NDVI-PDSI correlations were primarily negative on the windward side of the islands and positive on the leeward sides, suggesting a higher sensitivity to drought for leeward native ecosystems. Multi-decadal time series and spatially explicit data for native landscapes provide natural resource managers with long-term trends and monthly changes associated with vegetation health and stability.

Where Are Ecology and Biodiversity in Social–Ecological Systems Research? A Review of Research Methods and Applied Recommendations

Abstract: Understanding social–ecological systems (SES) is critical for effective sustainability and biodiversity conservation initiatives. We systematically reviewed SES research to examine whether and how it integrates ecological and social domains and generates decision-relevant recommendations. We aim to inform SES research methods and improve the relevance of SES research. Of 120 SES articles, two-thirds included an ecological variable while all but one included a social variable. Biodiversity was a less common ecological variable than resource productivity, land cover, and abiotic measures. We found six diverse social–ecological linking methods: modeling (9%), causal loop diagrams (18%), quantitative correlations (8%), separate quantitative measures (13%), indicators (14%), and rich description (37%). Policy recommendations addressing social–ecological dynamics were more likely in articles including both ecological and social variables, suggesting the importance of research approach for policy and practice application. Further integration of ecology and biodiversity is needed to support governance, policy, and management for SES sustainability.

Recreational demand for clean water: evidence from geotagged photographs by visitors to lakes

Abstract: More than 41 000 water bodies are listed as impaired by the US Environmental Protection Agency under the Clean Water Act Implementation and enforcement of regulations designed to address these impairments can be costly, raising questions about the value of the public benefits derived from improved surface water quality Here, we assess the recreational value of changes in water quality using freely available geotagged photographs, taken by members of the public, as a proxy for recreational visits to lakes We found that improved water clarity is associated with increased numbers of visits to lakes and that lake users were willing to incur greater costs to visit clearer lakes Lake users were willing to travel 56 minutes farther (equivalent to US$22 in travel costs) for every one-meter increase in water clarity in Minnesota and Iowa lakes, when controlling for other lake attributes Our approach demonstrates the potential for social-media data to inform social–ecological research, including assessment of the recreational benefits of improvements in water quality

Building functional cities

Abstract: The literature views many African cities as dysfunctional with a hodgepodge of land uses and poor “connectivity.” One driver of inefficient land uses is construction decisions for highly durable buildings made under weak institutions. In a novel approach, we model the dynamics of urban land use with both formal and slum dwellings and ongoing urban redevelopment to higher building heights in the formal sector as a city grows. We analyze the evolution of Nairobi using a unique high–spatial resolution data set. The analysis suggests insufficient building volume through most of the city and large slum areas with low housing volumes near the center, where corrupted institutions deter conversion to formal sector usage.

Factors affecting relative height and ground elevation estimations of GEDI among forest types across the conterminous USA

Abstract: ABSTRACT The Global Ecosystem Dynamics Investigation (GEDI), a new spaceborne LiDAR system of the National Aeronautics and Space Administration (NASA), has the potential to revolutionize global measurements of vertical vegetation structure. However, GEDI performance among different forest types and factors influencing GEDI performance needs to be evaluated against similar measurements from existing airborne LiDAR platforms. Ideally, comparisons across diverse forest types will inform future work quantifying biomass or mapping species habitats. Thus, we compared the second version of GEDI L2A product (GEDI V2) with Airborne Observation Platform (AOP) leaf-on LiDAR data across 33 National Ecological Observation Network (NEON) sites. Comparisons were made for ground elevation and relative height (RH) of GEDI with simulated airborne laser scanning (ALS) waveforms from discrete point cloud LiDAR. Results indicated that GEDI V2 obtained high accuracy on ground elevation and RH100 estimations (3σ) with RMSEs of 1.38 m and 2.62 m, respectively. GEDI produced forest height estimations (RH100) for all 12 forest types with a %RMSE below 25%. GEDI RHs were sensitive to ground finding accuracy, and GEDI performance of RH estimation varied from forest profiles of different forest types. For factors influencing GEDI performance, greater than 21% of GEDI RH95 and 33% of ground elevation variations can be explained by land surface attributes, observing sensor system characteristics, and the collection time differences between GEDI and NEON LiDAR. Furthermore, geolocation error remains an essential factor affecting GEDI performance, which varies among forest and land cover types, especially for canopy height estimation. The findings reported here can provide insights to guide and enhance future GEDI-based global forest structure mapping and applications.

Phyto-ecological studies and distribution pattern of plant species and communities of Dhirkot, Azad Jammu and Kashmir, Pakistan.

Abstract: Plant species represent the hierarchical expression of vegetation as it is affected by various environmental gradients. We explored the plant species composition, distribution pattern, communities formation and their respective indicators under the influence of various environmental factors in the Dhirkot region, Azad Jammu and Kashmir. It was hypothesized that different environmental factors were responsible for the formation of various plant communities each with a distinct indicator. Quantitative ecological techniques were used for the sampling of vegetation. A total of 114 quadrats were established in 13 selected sampling sites. Phytosociological attributes were calculated for each plant species at each quadrat. Soil samples were collected and analyzed using different standard protocols. All the collected data were analyzed using Cluster Analysis, Indicator Species Analysis and Canonical Correspondence Analysis of PCORD and CANOCO software, respectively. A total of 145 plant species were recorded belong to 62 different families. Asteraceae and Lamiaceae were the dominant families, represented by 12 species each (8.27%). Cluster Analysis classify all the stations and plants into four major plant communities as 1) Olea-Desmodium-Prunilla community. 2) Abies-Zanthoxylum-Pteracanthus community 3) Cedrus-Elaeagnus-Hypericum community 4) Alnus-Myrsine-Ranunculus community. Soil pH, electrical conductivity, soil saturation, organic matter and altitude were the significant environmental factors that play its essential role in the plant species distribution, composition, formation of major plant communities and their respective indicators in the region. It is recommended that the identified indicator and rare plant species of the investigated area can further be grown for conservation and management purposes in in-situ environment.