Embedded Files
Label political AI and audit its hidden costs.
A Hernandez-Serna. Nature 644, 876 (2025) doi: https://doi.org/10.1038/d41586-025-02702-8
Generative artificial intelligence (AI) technologies are already shaping political persuasion: systems that mimic emotion craft messages at scale and target voters with precision. Yet, citizens seldom know when a machine is speaking to them, and regulators remain behind the curve. Three blind spots need urgent correction. Transparency: recipients rarely know when a message is machine-generated; AI labels are voluntary, inconsistent and easy to evade. Externalities: energy and water use, as well as the invisible labour of moderators and of annotators who label training data and rate model outputs, are mostly absent from risk audits. Stress testing: independent evaluations across languages, vulnerable communities and long time horizons remain scarce. Regulators should require verifiable AI-origin labels on all political communications. Pre-deployment audits must measure persuasive efficacy alongside environmental and labour footprints. Open repositories of AI-generated political adverts would allow continuous scholarly scrutiny instead of relying on corporate self-reporting. These measures do not muzzle speech; they make large-scale persuasion efforts legible and accountable, similar to how twentieth-century campaign-finance rules clarified money flows in politics.
Unprecedentedly high global forest disturbance due to fire in 2023 and 2024.
P Potapov, A Tyukavina, S Turubanova, M C. Hansen, L Giglio, A Hernandez-Serna, A Lima, N Harris, F Stolle. PNAS. July 21, 2025 122 (30) e2505418122 https://doi.org/10.1073/pnas.250541812
Global forests provide key ecosystem services, from climate regulation to biodiversity habitat, but are under increasing pressure from the combined impacts of climate and land use change. Here, we show that forest disturbance due to fire is growing globally, with the most dramatic increases in intact forest landscapes, highlighting an existential threat to remaining high biomass, high biodiversity forests. The global annual area of forest disturbance due to fire for 2023 and 2024 was highest since the beginning of monitoring in 2001. Compared to 2002–2022 average annual forest disturbance due to fire, the 2023–2024 average was 2.2 times higher globally and 3 times higher in the Tropics. More than ¼ of all 2024 forest disturbance from fire occurred in tropical forests. We found a statistically significant increasing trend of forest disturbance due to fire from 2002 to 2024 in all climate domains except Subtropical. High forest, low deforestation tropical countries were not exempt, with Guyana and the Republic of the Congo experiencing record forest disturbance due to fire. Our results agree with recently estimated increases in global forest fire emissions and active fire detections. The unprecedented scale of fires in the world’s most remote forests is a potential harbinger of ecosystem tipping points. Protecting these remaining unfragmented high conservation value forests from this threat poses a daunting and as yet undeveloped policy and capacity challenge.
The dataset is also available at: https://glad.earthengine.app/view/global-forest-change
New York Time: https://www.nytimes.com/2025/07/21/climate/extreme-fire-weather-forests.html
An Accurate 10 m Annual Crop Map Product of Maize and Soybean Across the United States
Status: this preprint is currently under review for the journal ESSD.
H Li, XP Song, B Adusei, J Pickering, A Lima, A Poulson, A Baggett, P Potapov, A Khan, V Zalles, A Hernandez-Serna, S M. Jantz, AH. Pickens, C Ortiz-Dominguez, X Li, T Kerr, Z Song, S Turubanova, E Bongwele, H Koy Kondjo, A Komarova, S V. Stehman, M C. Hansen. https://doi.org/10.5194/essd-2025-361
High-resolution crop maps over large spatial extents are fundamental to many agricultural applications; however, generating high-quality crop maps consistently across space and time remains a challenge. In this study, we improved a workflow for crop mapping and developed the first openly available, annual, 10-m spatial resolution maize and soybean maps over the Contiguous United States (CONUS) from 2019 to 2022. We obtained all available Sentinel-2 surface reflectance data between May and October for every year, applied quality assurance, corrected the bidirectional reflectance distribution function (BRDF) effects, and generated 10-day analysis ready data (ARD) composites. We then derived multi-temporal metrics from the 10-day ARD as training features for the national-scale wall-to-wall mapping.
The dataset is also available at: https://doi.org/10.6084/m9.figshare.28934993.v1
Perennial snow and ice cover change from 2001 to 2021 in the Hindu-Kush Himalayan region derived from the Landsat analysis-ready data.
A Khan, P Potapov, M C. Hansen, A H. Pickens,A Tyukavina, A Hernandez-Serna, K Uddin, J Ahmad. Remote Sensing Applications: Society and Environment March 22, 2024: 101192. https://doi.org/10.1016/j.rsase.2024.101192
The changing climate directly affects spatial and temporal patterns of snow and ice cover globally and in the Hindu-Kush Himalayan (HKH) region. In the HKH, around 3.3 billion people across 11 countries depend on water originating from mountain glaciers and snowfields, and melting snow cover has a direct impact on their livelihood and well-being. Various studies have shown that the snow and ice cover in the HKH is declining at an alarming rate but have been limited in geographic, spatial and temporal scales.
View map data online: https://glad.earthengine.app/view/snow-ice-hkh
Tree canopy extent and height change in Europe, 2001–2021, quantified using Landsat data archive.
S Turubanova, P Potapov, M.C. Hansen, X. Li, A Tyukavina, A.H. Pickens, A Hernandez-Serna, A Pascual Arranz, J Guerra-Hernandez, C Senf, T Häme, R Valbuena, L Eklundh, O Brovkina, B Navrátilová, J Novotný, N Harris, F Stolle. Remote Sensing of Environment. Volume 298, 1 December 2023, 113797 https://doi.org/10.1016/j.rse.2023.113797
European forests are among the most extensively studied ecosystems in the world, yet there are still debates about their recent dynamics. We modeled the changes in tree canopy height across Europe from 2001 to 2021 using the multidecadal spectral data from the Landsat archive and calibration data from Airborne Laser Scanning (ALS) and spaceborne Global Ecosystem Dynamics Investigation (GEDI) lidars. Annual tree canopy height was modeled using regression tree ensembles and integrated with annual tree canopy removal maps to produce harmonized tree height map time series.
View map data online: https://glad.earthengine.app/view/europe-tree-dynamics
Drivers for the artisanal fisheries production in the Magdalena river.
L. Jimenez-Segura, J.D. Restrepo-Angel, A Hernandez-Serna. Front. Environ. Sci., 06 October 2022 https://doi.org/10.3389/fenvs.2022.866575
We review knowledge on the Magdalena River in Colombia and its fish to identify those drivers that influence the artisanal fisheries production. We identify eight direct drivers (four natural and four anthropogenic) and at least four indirect drivers. Those drivers modify conditions in the fluvial network that promote fish movements, reproduction, and their larvae survivor. Landscape, rains, floods, connectivity of the fluvial net as land cover change, water pollution, hydropower, and alien species are the natural and anthropogenic direct drivers described in this article. The river–lake interaction dynamics in the Magdalena River are determined by two rainy cycles per year. Two seasonal flooding periods induce two cycles in the biological productivity of floodplains because water and sediment inputs. The most visible consequences in these hydrological cycles are the migrations of potamodromous fish and the periodic increase in the artisanal fishery production. Major floodplains are reducing their storage capacity by trapping ∼10%–40% of upstream sediment production.
The global 2000-2020 land cover and land use change dataset derived from the Landsat archive: first results.
P Potapov, M C. Hansen, A Pickens, A Hernandez-Serna, A Tyukavina, S Turubanova, V Zalles, X Li, A Khan, F Stolle, N Harris, XP Song, A Baggett, I Kommareddy, A Kommareddy.. Frontiers Remote Sensing. 13 April 2022 https://doi.org/10.3389/frsen.2022.856903
Recent advances in Landsat archive data processing and characterization enhanced our capacity to map land cover and land use globally with higher precision, temporal frequency, and thematic detail. Here, we present the first results from a project aimed at annual, multidecadal land monitoring providing critical information for tracking global progress towards sustainable development. The global 30-m spatial resolution dataset quantifies changes in forest extent and height, cropland, built-up lands, surface water, and perennial snow and ice extent from the year 2000 to 2020. Landsat Analysis Ready Data served as an input for multidecadal land cover and use mapping. Each thematic product was independently derived using state-of-the-art, locally and regionally calibrated machine learning tools. The dataset was validated using a statistical sampling which confirms its high accuracy (user’s and producer’s accuracies above 85% for all land cover and use themes, except for built-up land). Our results revealed dramatic changes in global land cover and land use over the past twenty years. The dataset is provided for public use and served as a first input for the planned global land monitoring system.
Global land use extent and dispersion within natural land cover using Landsat data
Global land use extent and dispersion within natural land cover using Landsat data
M.C. Hansen, P.V. Potapov, A.H. Pickens, A. Tyukavina, A. Hernandez-Serna, V. Zalles, S. Turubanova, I. Kommareddy, S.V. Stehman (2021). Environmental Research Letters in press https://doi.org/10.1088/1748-9326/ac46ec
The conversion of natural land cover into human-dominated land use systems has significant impacts on the environment. Global mapping and monitoring of human-dominated land use extent via satellites provides an empirical basis for assessing land use pressures. Here, we present a novel 2019 global land cover, land use, and ecozone map derived from Landsat satellite imagery and topographical data using derived image feature spaces and algorithms suited per theme. From the map, we estimate the spatial extent and dispersion of land use disaggregated by climate domain and ecozone, where dispersion is the mean distance of land use to all land within a subregion. We find that percent of area under land use and distance to land use follow a power law that depicts an increasingly random spatial distribution of land use as it extends across lands of comparable development potential. For highly developed climate/ecozones, such as temperate and sub-tropical terra firma vegetation on low slopes, area under land use is contiguous and remnant natural land cover have low areal extent and high fragmentation. The tropics generally have the greatest potential for land use expansion, particularly in South America. An exception is Asian humid tropical terra firma vegetated lowland, which has land use intensities comparable to that of temperate breadbaskets such as the United States' corn belt. Wetland extent is inversely proportional to land use extent within climate domains, indicating historical wetland loss for temperate, sub-tropical, and dry tropical biomes. Results highlight the need for planning efforts to preserve natural systems and associated ecosystem services. The demonstrated methods will be implemented operationally in quantifying global land change, enabling a monitoring framework for systematic assessments of the appropriation and restoration of natural land cover.
Data download: https://glad.umd.edu/dataset/global-land-cover-land-use-v1
View map data online: https://glad.earthengine.app/view/global-land-cover-land-use-v1
Massive soybean expansion in South America since 2000 and implications for conservation.
Massive soybean expansion in South America since 2000 and implications for conservation.
X.-P. Song, M.C. Hansen, P. Potapov, B. Adusei, J. Pickering, M. Adami, A. Lima, V. Zalles, S.V. Stehman, C.M. Di Bella, C.M. Conde, E.J. Copati, L.B. Fernandes, A. Hernandez-Serna, S.M. Jantz, A.H. Pickens, S. Turubanova, A. Tyukavina Nature Sustainability . https://www.nature.com/articles/s41893-021-00729-z
A prominent goal of policies mitigating climate change and biodiversity loss is to achieve zero-deforestation in the global supply chain of key commodities, such as palm oil and soybean. However, the extent and dynamics of deforestation driven by commodity expansion are largely unknown. Here we mapped annual soybean expansion in South America between 2000 and 2019 by combining satellite observations and sample field data. From 2000-2019, the area cultivated with soybean more than doubled from 26.4 Mha to 55.1 Mha. Most soybean expansion occurred on pastures originally converted from natural vegetation for cattle production. The most rapid expansion occurred in the Brazilian Amazon, where soybean area increased more than 10-fold, from 0.4 Mha to 4.6 Mha. Across the continent, 9% of forest loss was converted to soybean by 2016. Soy-driven deforestation was concentrated at the active frontiers, nearly half located in the Brazilian Cerrado. Efforts to limit future deforestation must consider how soybean expansion may drive deforestation indirectly by displacing pasture or other land uses. Holistic approaches that track land use across all commodities coupled with vegetation monitoring are required to maintain critical ecosystem services.
Data download: https://glad.earthengine.app/view/south-america-soybean and https://glad.umd.edu/projects/commodity-crop-mapping-and-monitoring-south-america
Rapid expansion of human impact on natural land in South America since 1985.
Rapid expansion of human impact on natural land in South America since 1985.
V .Zalles, MC. Hansen, P V. Potapov, D Parker, S V. Stehman, A H. Pickens, LLeal Parente, L G. Ferreira, XP Song, A Hernandez-Serna, I Kommareddyn. Science Advances 02 Apr 2021: Vol. 7, no. 14, eabg1620 DOI: 10.1126/sciadv.abg162
Across South America, the expansion of commodity land uses has underpinned substantial economic development at the expense of natural land cover and associated ecosystem services. Here, we show that such human impact on the continent’s land surface, specifically land use conversion and natural land cover modification, expanded by 268 million hectares (Mha), or 60%, from 1985 to 2018. By 2018, 713 Mha, or 40%, of the South American landmass was impacted by human activity. Since 1985, the area of natural tree cover decreased by 16%, and pasture, cropland, and plantation land uses increased by 23, 160, and 288%, respectively. A substantial area of disturbed natural land cover, totaling 55 Mha, had no discernable land use, representing land that is degraded in terms of ecosystem function but not economically productive. These results illustrate the extent of ongoing human appropriation of natural ecosystems in South America, which intensifies threats to ecosystem-scale functions.
Data download: https://glad.umd.edu/dataset/rapid-expansion-human-impact-natural-land-south-america-1985
Mapping global forest canopy height through integration of GEDI and Landsat data.
Mapping global forest canopy height through integration of GEDI and Landsat data.
P. V Potapov; X. Lia, A. Hernandez-Serna, A. Tyukavina, M. C. Hansen, A. Kommareddy, A. Pickens, S. Turubanova, H. Tanga, C. Edibaldo Silva, J. Armstona, R. Dubayah, J. Bryan Blair, M Hofton. Remote Sensing of Environment. Volume 253, February 2021, 112165 https://doi.org/10.1016/j.rse.2020.112165
A new, 30-m spatial resolution global forest canopy height map was developed through the integration of the Global Ecosystem Dynamics Investigation (GEDI) lidar forest structure measurements and Landsat analysis-ready data time-series (Landsat ARD). The GEDI RH95 (relative height at 95%) metric was used to calibrate the model. The Landsat multi-temporal metrics that represent the surface phenology serve as the independent variables. The “moving window” locally calibrated and applied regression tree ensemble model was implemented to ensure high quality of forest height prediction and global map consistency. The model was extrapolated in the boreal regions (beyond the GEDI data range, 52°N to 52°S) to create the global forest height prototype map.
Data download: https://glad.umd.edu/dataset/gedi/
Automatic identification of species with neural networks.
Automatic identification of species with neural networks.
A Hernandez-Serna and LF Jiménez-Segura. 2014. PeerJ 2:e563 .
A new automatic identification system using photographic images has been designed to recognize fish, plant, and butterfly species from Europe and South America. The automatic classification system integrates multiple image processing tools to extract the geometry, morphology, and texture of the images. Artificial neural networks (ANNs) were used as the pattern recognition method. We tested a data set that included 740 species and 11,198 individuals. Our results show that the system performed with high accuracy, reaching 91.65% of true positive fish identifications, 92.87% of plants and 93.25% of butterflies. Our results highlight how the neural networks are complementary to species identification.
TROPICAL FOREST CANOPY STRUCTURE AND CHANGE ASSESSMENT USING LANDSAT, GEDI, AND AIRBORNE LIDAR DATA
TROPICAL FOREST CANOPY STRUCTURE AND CHANGE ASSESSMENT USING LANDSAT, GEDI, AND AIRBORNE LIDAR DATA
P. V Potapov; X. Lia, A. Hernandez-Serna, A. Tyukavina, S. Turubanova, M. C. Hansen, H. Tang, Q. Hanh Nguyen 2021 IEEE International Geoscience and Remote Sensing, pp. 666-669, doi: 10.1109/IGARSS47720.2021.9554814.
Spatiotemporally consistent multidecadal data on forest extent and structure is the key for quantifying carbon storage, GHG emissions, degradation, and recovery of tropical forests. Consistently processed long-term Landsat data record is the only tool that enables such capacity. Here, we prototyped regional-level 2000-2019 forest structure monitoring and pantropical forest structure mapping for the year 2019 through the integration of the Landsat analysis ready data with airborne lidar and Global Ecosystem Dynamics Investigation (GEDI) data. The presented approach can support the data needs of many global, regional, and national climate change mitigation and sustainable development initiatives.
Data download: https://glad.umd.edu/dataset/gedi/
Annual continuous fields of woody vegetation structure in the Lower Mekong region from 2000‐2017 Landsat time-series.
Annual continuous fields of woody vegetation structure in the Lower Mekong region from 2000‐2017 Landsat time-series.
P. V. Potapov, A. Tyukavina, .S Turubanova, A. Hernandez-Serna, Y Talero, M.C. Hansen, D. Saah, K. Tenneson, A. Poortinga, A. Aekakkararungroj, F. Chishtie, P. Towashiraporn, B. Bhandari, KS Aung, NH Quyen. Remote Sensing of Environment, Volume 232, October 2019, 111278; doi: 10.1016/j.rse.2019.111278.
Spatially and temporally consistent vegetation structure time-series have great potential to improve the capacity for national land cover monitoring, to reduce latency and cost of international reporting, and to harmonize regional land cover characterizations. Here we present a semi-automatic, operational algorithm for mapping and monitoring of woody vegetation canopy cover and height at a regional scale using freely available Landsat time-series data. The presented algorithm employs automatic data processing and mapping using a set of lidar-based vegetation structure prediction models. Changes in vegetation cover are detected separately and integrated into the structure time-series. Sample-based validation and inter-comparison with existing datasets demonstrates the spatial and temporal consistency of our regional data time-series. The dataset reliably reflects changes in tree cover (tree cover loss user's accuracy of 0.84 and producer's accuracy of 0.75) and can serve as a tool to map annual forest extent (user's accuracy of 0.98 and producer's accuracy of 0.81 for 10% canopy cover threshold to define the forest class). The tree height estimates are consistent with a GLAS-based global map (mean average error of 3.7 m, the correlation coefficient of 0.92 and the R2 of 0.85). Total forest area decreased by 6.2% within the region, and 11.1% of year 2000 primary forest area was lost by 2017. At the national level, Cambodia demonstrated the highest rate of deforestation, with a net forest area loss of 22.5%. We estimated that 21.3% of 2017 forest cover had an age of 17 years or less, illustrating the intensive forest land uses within the region. The time-series product is suitable for mapping annual land cover and inter-annual land cover change using customized class definitions.
Data download: https://landcovermapping.org/en/
Soundscape analysis and acoustic monitoring document impacts of natural gas exploration on biodiversity in a tropical forest.
Soundscape analysis and acoustic monitoring document impacts of natural gas exploration on biodiversity in a tropical forest.
J.L Deichmann, A Hernandez-Serna, J.A Delgado C , M Campos-Cerqueira, T.M Aide. Ecological Indicators. Volume 74, March 2017, Pages 39–48
Natural resource extraction is increasing rapidly in tropical forests, but we lag behind in understanding the impacts of these disturbances on biodiversity. In high diversity tropical habitats, acoustic monitoring is an efficient tool for sampling a large proportion of the fauna across varied spatial and temporal scales. We used passive acoustic monitoring in a pre-montane forestin Peru to investigate how soundscape composition and richness of acoustic frequencies varied with distance from a natural gas exploratory well and with operational phase (construction and drilling). We also evaluated how anuran and avian species richness and vocal activity varied with distance and between phases. Soundscape analyses showed that acoustic frequency similarity was greatest among sites closer to (≤250 m) and farther from (≥500 m) the platform. Soundscapes revealed more frequencies were used during construction and showed a weak trend of increasing frequency richness with increasing distance from the disturbance. Avian species richness and detections increased with distance from the platform, but anuran richness and detections declined with distance. Operational phase did not play a significant role in overall richness or activity patterns of either group. Among birds, insectivore detections increased with distance from the platform, and nectarivores were detected more frequently during the drilling phase. Results demonstrate that acoustic monitoring and soundscape analyses are useful tools for evaluating the impact of development activity on the vocalizing community, and should be implemented as a best practice in monitoring biodiversity and for guiding specific mitigation strategies.
Data download: https://arbimon.sieve-analytics.com/
Species richness (of insects) drives the use of acoustic space in the tropics
Species richness (of insects) drives the use of acoustic space in the tropics
T.M Aide, A Hernandez-Serna, M Campos-Cerqueira, O.A Acevedo-Charry, J.L Deichmann. Remote Sensing. 9 (11), 1096; 2017. doi: 10.3390/rs9111096.
Acoustic ecology, or ecoacoustics, is a growing field that uses sound as a tool to evaluate animal communities. In this manuscript, we evaluate recordings from eight tropical forest sites that vary in species richness, from a relatively low diversity Caribbean forest to a megadiverse Amazonian forest, with the goal of understanding the relationship between acoustic space use (ASU) and species diversity across different taxonomic groups. For each site, we determined the acoustic morphospecies richness and composition of the biophony, and we used a global biodiversity dataset to estimate the regional richness of birds. Here, we demonstrate how detailed information on activity patterns of the acoustic community (<22 kHz) can easily be visualized and ASU determined by aggregating recordings collected over relatively short periods (4–13 days). We show a strong positive relationship between ASU and regional and acoustic morphospecies richness. Premontane forest sites had the highest ASU and the highest species richness, while dry forest and montane sites had lower ASU and lower species richness. Furthermore, we show that insect richness was the best predictor of variation in total ASU, and that insect richness was proportionally greater at high-diversity sites. In addition, insects used a broad range of frequencies, including high frequencies (>8000 Hz), which contributed to greater ASU. This novel approach for analyzing the presence and acoustic activity of multiple taxonomic groups contributes to our understanding of ecological community dynamics and provides a useful tool for monitoring species in the context of restoration ecology, climate change and conservation biology.
Data download: https://arbimon.sieve-analytics.com/
Diel cycle size-dependent trophic structure of neotropical fishes: a three year case analysis from 35 floodplain lakes in Colombia.
Diel cycle size-dependent trophic structure of neotropical fishes: a three year case analysis from 35 floodplain lakes in Colombia.
A Hernandez-Serna, C Granado-Lorencio and LF Jiménez-Segura. Journal of Applied Ichthyology. 31: 638–645. 2015
Investigated were whether fish assemblages in 35 neotropical floodplain lakes along the Magdalena River, Colombia (ranging from 4 to 2333 ha) have a trophic structure that is dependent on fish body size within the diel cycle (24 h), and whether any changes to the trophic structure of fish assemblages occur during the diel cycle. Sampling was done during diel cycles in the rainy seasons between 2008 and 2011 (ten lakes in 2008, 20 in 2010, and five in 2011). Small fish (27–87 mm) were most active from 06:01 to 18:00, while larger predatory fish (>87 mm) were inactive during this time. In addition to fish body size, trophic group composition also varied throughout the diel cycle: insectivores, piscivores, and omnivore-insectivores were the dominant groups from 06:01 to 18:00; carnivores, carnivore-insectivores, and detritivores dominated from 18:01 to 06:00. This study highlights the importance of fish size in predicting predator-prey interactions during different periods of the diel cycle.
Impacts of small-scale gold mining on birds and anurans near the Tambopata Natural Reserve, Peru, assessed using passive acoustic monitoring.
Impacts of small-scale gold mining on birds and anurans near the Tambopata Natural Reserve, Peru, assessed using passive acoustic monitoring.
N Alvarez-Berríos, M Campos-Cerqueira, A Hernandez-Serna, J.A Delgado C, F Román-Dañobeytia and T. Mitchell Aide Aide. Tropical Conservation Science. Vol. 9 (2): 832-851, 2016.
Artisanal and small-scale gold mining (ASM) is becoming a significant cause of environmental degradation in tropical ecosystems. In this study, we conducted a rapid assessment on the impact of an ASM gold mine on the vocalizing avian and anuran communities in the buffer zone of the Tambopata National Reserve in Peru. We used seven audio recorders (three near an active mine, two in an abandoned mine, and two in an adjacent forest) to collect 2900 recordings to generate soundscapes and compare acoustic activity patterns of birds and anurans among sites. We identified 56 bird species during the morning chorus (05:00-07:00) and 9 anurans species in the evening chorus (18:00-20:00). Bird speciesrichness wassimilar between the forest (28 bird species), the abandoned mine (25 species) and the active mine (24 species), but species richness of birds sensitive to disturbance was much lower in the active mine. In contrast, anuran species richness was highest in the active mine (5 species) and lowest in the forest (2 species). Results indicate that acoustic monitoring and soundscape analysis can be effective tools for evaluating the impact of mining activities on vocalizing species, and could become useful tools in rapid environmental impact assessments for mitigation and conservation strategies in ASM mining regions.
Data download: https://arbimon.sieve-analytics.com/
Length–weight relationships of 38 fish species of the Magdalena river floodplain lakes.
Length–weight relationships of 38 fish species of the Magdalena river floodplain lakes.
A Hernandez-Serna, V Márquez Velásquez, JD Carvajal-Quintero, A Gulfo, C Granado-Lorencio and LF Jiménez-Segura. 2014. Journal of Applied Ichthyology. 30: 549-55.
This study reports length–weight relationships for 38 fish species belonging to 18 families inhabiting the Magdalena River floodplain lakes of Colombia. Samples were taken during the high water season of 2008, 2010 and 2011. Two species are presented for the first time. Maximum total length records for 24 species exceed those in FishBase.
V Márquez Velásquez, R Galdino Leite, A Hernandez-Serna, F Alvarado. 2020. Journal of Fish Biology. doi : 10.1111/jfb.14565
Analysis of feeding habits was performed for early life stages of Brachyplatystoma rousseauxii and Brachyplatystoma filamentosum in the Madeira River, Brazil. Stomach contents of B. rousseauxii and B. filamentosum were identified and analyzed. The percentage of frequency of occurrence (%FO) and area (%A) and the alimentary index IAi were used to quantify the feeding habits of the two species. The order Diptera represented the most important item consumed by both species. This is the first analyses of the trophic ecology of these ecologically and economically important species of the Amazonian region in early life stages.
Regionally nested patterns of fish assemblages in floodplain lakes of the Magdalena river (Colombia).
Regionally nested patterns of fish assemblages in floodplain lakes of the Magdalena river (Colombia).
C Granado-Lorencio, A Hernandez Serna, JD Carvajal, LF Jiménez-Segura, A Gulfo, and F Alvarez. 2012. Ecology and Evolution. 2: 1296-1303.
We investigated if fish assemblages in neotropical floodplain lakes (cienagas) exhibit nestedness, and thus offer support to the managers of natural resources of the area for their decision making. The location was floodplain lakes of the middle section of the Magdalena river, Colombia. We applied the nested subset analysis for the series of 30 cienagas (27 connected to the main river and three isolated). All fish were identified taxonomically in the field and the matrix for presence–absence in all the lakes was used for the study of the pattern of nestedness. The most diverse order was Characiformes (20 species), followed by Siluriformes (19 species). Characidae and Loricaridae were the richest families. The species found in all the lakes studied were migratory species (17), and sedentary species (33). Two species (Caquetaia kraussii and Cyphocharax magdalenae) were widespread across the cienagas archipelago (100% of incidence). Nestedness analysis showed that the distribution of species over the spatial gradient studied (840 km) is significantly nested. The cienagas deemed the most hospitable were Simiti, El Llanito, and Canaletal. Roughly, 13 out of the 50 species caught show markedly idiosyncratic distributions. The resulting dataset showed a strong pattern of nestedness in the distribution of Magdalenese fishes, and differed significantly from random species assemblages. Out of all the measurements taken in the cienagas, only the size (area) and local richness are significantly related to the range of order of nested subset patterns (r = –0.59 and –0.90, respectively, at p < 0.01). Differential species extinction is suggested as the cause of a nested species assemblage, when the reorganized matrix of species occurring in habitat islands is correlated with the island area. Our results are consistent with this hypothesis.
Fish assemblages in floodplain lakes in a Neotropical river during the wet season (Magdalena River, Colombia).
Fish assemblages in floodplain lakes in a Neotropical river during the wet season (Magdalena River, Colombia).
Granado-Lorencio, A Gulfo, F Alvarez, LF Jiménez-Segura, JD Carvajal-Quintero, and A Hernandez-Serna. 2012. Journal of Tropical Ecology. 28:271-279.
A number of studies have pointed out that abiotic factors and recolonization dynamics appear to be more important than biotic interactions in structuring river–fish assemblages. In this paper, we studied the fish assemblages in 27 floodplain lakes, with perennial connection to the river, in the middle section of the Magdalena River (Colombia), to examine spatial pattern in freshwater fish diversity in relation to some environmental parameters. Our objective was to examine relationships between floodplain-lake fish communities and nvironmental variables associated with lake morphology, water chemistry and river–floodplain connectivity in a large river–floodplain ecosystem. During the study, a total of 18 237 fish were caught from 50 species (regional richness; 17 were migrants and 33 residents). In the present study, the most diverse order was Characiformes with 20 species, followed by Siluriformes, with 19 species. Characidae and Loricaridae were the richest families. The range of species richness (local richness) varied between five and 39 species. Similarity of local assemblages (using the presence–absence data) depends on the distance between lakes. A positive relationship was observed between the Ln of the total abundance of each species and the number of lakes where they were found. Out of all the environmental parameters taken in the lakes, only the size (Log Area) and relative perimeter length are significantly related to local assemblage species richness. It has not been possible to demonstrate that the connectivity (distance) from lakes to the main river can be considered a predictor of the local richness.
Books and chapters
Books and chapters
Guía Ilustrada Peces cañón del río Porce, Antioquia.
Guía Ilustrada Peces cañón del río Porce, Antioquia.
L.F Jiménez-Segura, J Álvarez, L.E Ochoa, A Loaiza, J.P Londoño, D Restrepo, K Aguirre, A Hernandez-Serna, J.D Correa y U Jaramillo-Villa. 2015. EPM. Universidad de Antioquia - Medellín, Colombia. ISBN:978958582968-8 ed:1. 106 pp. pdf
I Catalogo de los Recursos Pesqueros continentales de Colombia.
I Catalogo de los Recursos Pesqueros continentales de Colombia.
J.D Carvajal-Quintero, A Hernández-Serna y L.F Jiménez-Segura. 2011. "Familia Loricariidae: Hypostomus hondae y Pterygoplichthys undecimalis". Instituto de Investigaciones de Recursos Biológicos Alexandervon Humboldt ISBN: 978958834354 ONU 9 ed: 1, vol 1, pag: 370-378. pdf
Species Richness drives the Use of Acoustic Space.
Species Richness drives the Use of Acoustic Space.
Acoustic signals are used for species recognition, mate choice, and resource defense, but the frequencies used are restricted by body-size, phylogeny, habitat structure, and biotic and abiotic sounds in the habitat. Acoustic space is a limited resource, and studies have suggested that species avoid competition by partitioning this space in time and frequency. Alternatively, other studies have reported temporal synchrony and spectral overlap among species. These studies have focused on individual taxonomic groups (e.g. fish, bird, insects, and anurans), and no study has assessed patterns of acoustic activity for all species in a community across a gradient of species richness. Here we compare the use of acoustic space (i.e. soundscape) in nine tropical forest sites, and show a highly significant positive relationship between the percent of acoustic space used and total bird, amphibian, and mammal species richness. If community richness is relatively low, species may avoid overlapping and maintain signals within the optimal frequency range of a given habitat, but in species-rich communities, species will encounter greater signal overlap and will be forced to use other frequencies. Our acoustic species richness hypothesis unifies the acoustic partitioning and network hypotheses by demonstrating how variation in species richness across sites affects the patterns of activity within the acoustic space. This novel approach for analyzing soundscapes contributes to our understanding of ecological community dynamics (e.g. niche theory) and provides useful tools for monitoring species in the context of restoration ecology, climate change, and conservation biology.
Automatic identification of species with neural networks.
Automatic identification of species with neural networks.
A new automatic identification system using photographic images has been designed to recognize fish, plant, and butterfly species from Europe and South America. The automatic classification system integrates multiple image processing tools to extract the geometry, morphology, and texture of the images. Artificial neural networks (ANNs) were used as the pattern recognition method. We tested a data set that included 740 species and 11,198 individuals. Our results show that the system performed with high accuracy, reaching 91.65% of true positive fish identifications, 92.87% of plants and 93.25% of butterflies. Our results highlight how the neural networks are complementary to species identification.
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