Automated wildlife image classification: An active learning tool for ecological applications

Wildlife camera trap images are being used extensively to investigate animal abundance, habitat associations, and behavior, which is complicated by the fact that experts must first classify the images manually. Artificial intelligence systems can take over this task but usually need a large number of already-labeled training images to achieve sufficient performance. This requirement necessitates human expert labor and poses a particular challenge for projects with few cameras or short durations. We propose a label-efficient learning strategy that enables researchers with small or medium-sized image databases to leverage the potential of modern machine learning, thus freeing crucial resources for subsequent analyses. Our methodological proposal is two-fold: (1) We improve current strategies of combining object detection and image classification by tuning the hyperparameters of both models. (2) We provide an active learning (AL) system that allows training deep learning models very efficiently in terms of required human-labeled training images. We supply a software package that enables researchers to use these methods directly and thereby ensure the broad applicability of the proposed framework in ecological practice. We show that our tuning strategy improves predictive performance. We demonstrate how the AL pipeline reduces the amount of pre-labeled data needed to achieve a specific predictive performance and that it is especially valuable for improving out-of-sample predictive performance. We conclude that the combination of tuning and AL increases predictive performance substantially. Furthermore, we argue that our work can broadly impact the community through the ready-to-use software package provided. Finally, the publication of our models tailored to European wildlife data enriches existing model bases mostly trained on data from Africa and North America

The DEEP Groth Strip Galaxy Redshift Survey. III. Redshift Catalog and Properties of Galaxies

The Deep Extragalactic Evolutionary Probe (DEEP) is a series of spectroscopic surveys of faint galaxies, targeted at the properties and clustering of galaxies at redshifts z ~ 1. We present the redshift catalog of the DEEP 1 GSS pilot phase of this project, a Keck/LRIS survey in the HST/WFPC2 Groth Survey Strip. The redshift catalog and data, including reduced spectra, are publicly available through a Web-accessible database. The catalog contains 658 secure galaxy redshifts with a median z=0.65, and shows large-scale structure walls to z = 1. We find a bimodal distribution in the galaxy color-magnitude diagram which persists to z = 1. A similar color division has been seen locally by the SDSS and to z ~ 1 by COMBO-17. For red galaxies, we find a reddening of only 0.11 mag from z ~ 0.8 to now, about half the color evolution measured by COMBO-17. We measure structural properties of the galaxies from the HST imaging, and find that the color division corresponds generally to a structural division. Most red galaxies, ~ 75%, are centrally concentrated, with a red bulge or spheroid, while blue galaxies usually have exponential profiles. However, there are two subclasses of red galaxies that are not bulge-dominated: edge-on disks and a second category which we term diffuse red galaxies (DIFRGs). The distant edge-on disks are similar in appearance and frequency to those at low redshift, but analogs of DIFRGs are rare among local red galaxies. DIFRGs have significant emission lines, indicating that they are reddened mainly by dust rather than age. The DIFRGs in our sample are all at z>0.64, suggesting that DIFRGs are more prevalent at high redshifts; they may be related to the dusty or irregular extremely red objects (EROs) beyond z>1.2 that have been found in deep K-selected surveys. (abridged)Comment: ApJ in press. 24 pages, 17 figures (12 color). The DEEP public database is available at http://saci.ucolick.org

Using Dark Energy Explorers and Machine Learning to Enhance the Hobby-Eberly Telescope Dark Energy Experiment

We present analysis using a citizen science campaign to improve the cosmological measures from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). The goal of HETDEX is to measure the Hubble expansion rate, $H(z)$, and angular diameter distance, $D_A(z)$, at $z =$ 2.4, each to percent-level accuracy. This accuracy is determined primarily from the total number of detected Lyman-$\alpha$ emitters (LAEs), the false positive rate due to noise, and the contamination due to [O II] emitting galaxies. This paper presents the citizen science project, Dark Energy Explorers, with the goal of increasing the number of LAEs, decreasing the number of false positives due to noise and the [O II] galaxies. Initial analysis shows that citizen science is an efficient and effective tool for classification most accurately done by the human eye, especially in combination with unsupervised machine learning. Three aspects from the citizen science campaign that have the most impact are 1) identifying individual problems with detections, 2) providing a clean sample with 100% visual identification above a signal-to-noise cut, and 3) providing labels for machine learning efforts. Since the end of 2022, Dark Energy Explorers has collected over three and a half million classifications by 11,000 volunteers in over 85 different countries around the world. By incorporating the results of the Dark Energy Explorers we expect to improve the accuracy on the $D_A(z)$ and $H(z)$ parameters at $z =$ 2.4 by 10 - 30%. While the primary goal is to improve on HETDEX, Dark Energy Explorers has already proven to be a uniquely powerful tool for science advancement and increasing accessibility to science worldwide.Comment: 14 pages, 6 figures, accepted for publication in The Astrophysical Journa

Diversity and specialization responses to climate and land use differ between deadwood fungi and bacteria

Climate and land use are major determinants of biodiversity, and declines in species richness in cold and human exploited landscapes can be caused by lower rates of biotic interactions. Deadwood fungi and bacteria interact strongly with their hosts due to long-lasting evolutionary trajectories. However, how rates of biotic interactions (specialization) change with temperature and land-use intensity are unknown for both microbial groups. We hypothesize a decrease in species richness and specialization of communities with decreasing temperature and increasing land use intensity while controlling for precipitation. We used a full-factorial nested design to disentangle land use at habitat and landscape scale and temperature spanning an area of 300 × 300 km in Germany. We exposed four deadwood objects representing the main tree species in Central Europe (beech, oak, spruce, pine) in 175 study plots. Overall, we found that fungal and bacterial richness, community composition and specialization were weakly related to temperature and land use. Fungal richness was slightly higher in near-natural than in urban landscapes. Bacterial richness was positively associated with mean annual temperature, negatively associated with local temperature and highest in grassland habitats. Bacterial richness was positively related to the covariate mean annual precipitation. We found strong effects of host-tree identity on species richness and community composition. A generally high level of fungal host-tree specialization might explain the weak response to temperature and land use. Effects of host-tree identity and specialization were more pronounced in fungi. We suggest that host tree changes caused by land use and climate change will be more important for fungal communities, while changes in climate will affect bacterial communities more directly. Contrasting responses of the two taxonomic groups suggest a reorganization of deadwood microbial communities, which might have further consequences on diversity and decomposition in the Anthropocene

Relationship of insect biomass and richness with land use along a climate gradient

Recently reported insect declines have raised both political and social concern. Although the declines have been attributed to land use and climate change, supporting evidence suffers from low taxonomic resolution, short time series, a focus on local scales, and the collinearity of the identified drivers. In this study, we conducted a systematic assessment of insect populations in southern Germany, which showed that differences in insect biomass and richness are highly context dependent. We found the largest difference in biomass between semi-natural and urban environments (−42%), whereas differences in total richness (−29%) and the richness of threatened species (−56%) were largest from semi-natural to agricultural environments. These results point to urbanization and agriculture as major drivers of decline. We also found that richness and biomass increase monotonously with increasing temperature, independent of habitat. The contrasting patterns of insect biomass and richness question the use of these indicators as mutual surrogates. Our study provides support for the implementation of more comprehensive measures aimed at habitat restoration in order to halt insect declines

Dung‐visiting beetle diversity is mainly affected by land use, while community specialization is driven by climate

Dung beetles are important actors in the self‐regulation of ecosystems by driving nutrient cycling, bioturbation, and pest suppression. Urbanization and the sprawl of agricultural areas, however, destroy natural habitats and may threaten dung beetle diversity. In addition, climate change may cause shifts in geographical distribution and community composition. We used a space‐for‐time approach to test the effects of land use and climate on α‐diversity, local community specialization (H (2)′) on dung resources, and γ‐diversity of dung‐visiting beetles. For this, we used pitfall traps baited with four different dung types at 115 study sites, distributed over a spatial extent of 300 km × 300 km and 1000 m in elevation. Study sites were established in four local land‐use types: forests, grasslands, arable sites, and settlements, embedded in near‐natural, agricultural, or urban landscapes. Our results show that abundance and species density of dung‐visiting beetles were negatively affected by agricultural land use at both spatial scales, whereas γ‐diversity at the local scale was negatively affected by settlements and on a landscape scale equally by agricultural and urban land use. Increasing precipitation diminished dung‐visiting beetle abundance, and higher temperatures reduced community specialization on dung types and γ‐diversity. These results indicate that intensive land use and high temperatures may cause a loss in dung‐visiting beetle diversity and alter community networks. A decrease in dung‐visiting beetle diversity may disturb decomposition processes at both local and landscape scales and alter ecosystem functioning, which may lead to drastic ecological and economic damage

The DEEP Groth Strip Survey. I. The Sample

The Deep Extragalactic Exploratory Probe (DEEP) is a multi-phase research program dedicated to the study of the formation and evolution of galaxies and of large scale structure in the distant Universe. This paper describes the first five-year phase, denoted DEEP1. A series of ten DEEP1 papers will discuss a range of scientific topics (e.g., the study of photometric and spectral properties of a general distant galaxy survey, the evolution observed in galaxy populations of varied morphologies). The observational basis for these studies is the Groth Survey Strip field, a 127 square arcminute region which has been observed with the Hubble Space Telescope in both broad I-band and V-band optical filters and with the Low Resolution Imaging Spectrograph on the Keck Telescopes. Catalogs of photometric and structural parameters have been constructed for 11,547 galaxies and stars at magnitudes brighter than 29, and spectroscopy has been conducted for a magnitude-color weighted subsample of 818 objects. We evaluate three independent techniques for constructing an imaging catalog for the field from the HST data, and discuss the depth and sampling of the resultant catalogs. The selection of the spectroscopic subsample is discussed, and we describe the multifaceted approach taken to prioritizing objects of interest for a variety of scientific subprograms. A series of Monte Carlo simulations then demonstrates that the spectroscopic subsample can be adequately modeled as a simple function of magnitude and color cuts in the imaging catalog.Comment: ApJS accepted, 15 pages, 12 figures. Version with higher-quality figures available at http://astronomy.nmsu.edu/nicol

Disentangling effects of climate and land use on biodiversity and ecosystem services - a multi‐scale experimental design

Climate and land-use change are key drivers of environmental degradation in the Anthropocene, but too little is known about their interactive effects on biodiversity and ecosystem services. Long-term data on biodiversity trends are currently lacking. Furthermore, previous ecological studies have rarely considered climate and land use in a joint design, did not achieve variable independence or lost statistical power by not covering the full range of environmental gradients. Here, we introduce a multi-scale space-for-time study design to disentangle effects of climate and land use on biodiversity and ecosystem services. The site selection approach coupled extensive GIS-based exploration (i.e. using a Geographic information system) and correlation heatmaps with a crossed and nested design covering regional, landscape and local scales. Its implementation in Bavaria (Germany) resulted in a set of study plots that maximise the potential range and independence of environmental variables at different spatial scales. Stratifying the state of Bavaria into five climate zones (reference period 1981–2010) and three prevailing land-use types, that is, near-natural, agriculture and urban, resulted in 60 study regions (5.8 × 5.8 km quadrants) covering a mean annual temperature gradient of 5.6–9.8°C and a spatial extent of ~310 × 310 km. Within these regions, we nested 180 study plots located in contrasting local land-use types, that is, forests, grasslands, arable land or settlement (local climate gradient 4.5–10°C). This approach achieved low correlations between climate and land use (proportional cover) at the regional and landscape scale with |r ≤ 0.33| and |r ≤ 0.29| respectively. Furthermore, using correlation heatmaps for local plot selection reduced potentially confounding relationships between landscape composition and configuration for plots located in forests, arable land and settlements. The suggested design expands upon previous research in covering a significant range of environmental gradients and including a diversity of dominant land-use types at different scales within different climatic contexts. It allows independent assessment of the relative contribution of multi-scale climate and land use on biodiversity and ecosystem services. Understanding potential interdependencies among global change drivers is essential to develop effective restoration and mitigation strategies against biodiversity decline, especially in expectation of future climatic changes. Importantly, this study also provides a baseline for long-term ecological monitoring programs

HETDEX Public Source Catalog 1: 220K Sources Including Over 50K Lyman Alpha Emitters from an Untargeted Wide-area Spectroscopic Survey

We present the first publicly released catalog of sources obtained from the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). HETDEX is an integral field spectroscopic survey designed to measure the Hubble expansion parameter and angular diameter distance at 1.88<z<3.52 by using the spatial distribution of more than a million Ly-alpha-emitting galaxies over a total target area of 540 deg^2. The catalog comes from contiguous fiber spectra coverage of 25 deg^2 of sky from January 2017 through June 2020, where object detection is performed through two complementary detection methods: one designed to search for line emission and the other a search for continuum emission. The HETDEX public release catalog is dominated by emission-line galaxies and includes 51,863 Ly{\alpha}-emitting galaxy (LAE) identifications and 123,891 OII-emitting galaxies at z<0.5. Also included in the catalog are 37,916 stars, 5274 low-redshift (z<0.5) galaxies without emission lines, and 4976 active galactic nuclei. The catalog provides sky coordinates, redshifts, line identifications, classification information, line fluxes, OII and Ly-alpha line luminosities where applicable, and spectra for all identified sources processed by the HETDEX detection pipeline. Extensive testing demonstrates that HETDEX redshifts agree to within deltaz < 0.02, 96.1% of the time to those in external spectroscopic catalogs. We measure the photometric counterpart fraction in deep ancillary Hyper Suprime-Cam imaging and find that only 55.5% of the LAE sample has an r-band continuum counterpart down to a limiting magnitude of r~26.2 mag (AB) indicating that an LAE search of similar sensitivity with photometric pre-selection would miss nearly half of the HETDEX LAE catalog sample. Data access and details about the catalog can be found online at http://hetdex.org/.Comment: 38 pages, 20 figures. Data access and details about the catalog can be found online at http://hetdex.org/. A copy of the catalogs presented in this work (Version 3.2) is available to download at Zenodo doi:10.5281/zenodo.744850

The Hobby–Eberly Telescope Dark Energy Experiment (HETDEX) Survey Design, Reductions, and Detections

We describe the survey design, calibration, commissioning, and emission-line detection algorithms for the Hobby–Eberly Telescope Dark Energy Experiment (HETDEX). The goal of HETDEX is to measure the redshifts of over a million Lyα emitting galaxies between 1.88 < z < 3.52, in a 540 deg2 area encompassing a comoving volume of 10.9 Gpc3. No preselection of targets is involved; instead the HETDEX measurements are accomplished via a spectroscopic survey using a suite of wide-field integral field units distributed over the focal plane of the telescope. This survey measures the Hubble expansion parameter and angular diameter distance, with a final expected accuracy of better than 1%. We detail the project’s observational strategy, reduction pipeline, source detection, and catalog generation, and present initial results for science verification in the Cosmological Evolution Survey, Extended Groth Strip, and Great Observatories Origins Deep Survey North fields. We demonstrate that our data reach the required specifications in throughput, astrometric accuracy, flux limit, and object detection, with the end products being a catalog of emission-line sources, their object classifications, and flux-calibrated spectra