Is color data from citizen science photographs reliable for biodiversity research?

1. Color research continuously demands better methods and larger sample sizes. Citizen science (CS) projects are producing an ever‐growing geo‐ and time‐referenced set of photographs of organisms. These datasets have the potential to make a huge contribution to color research, but the reliability of these data need to be tested before widespread implementation.
2. We compared the difference between color extracted from CS photographs with that of color extracted from controlled lighting conditions (i.e., the current gold standard in spectrometry) for both birds and plants. First, we tested the ability of CS photographs to quantify interspecific variability by assessing > 9,000 CS photographs of 537 Australian bird species with controlled museum spectrometry data. Second, we tested the ability of CS photographs to quantify intraspecific variability by measuring petal color data for two plant species using seven methods/sources with varying levels of control.
3. For interspecific questions, we found that by averaging out variability through a large sample size, CS photographs capture a large proportion of across species variation in plumage color within the visual part of the spectrum (R² = 0.68–0.71 for RGB space and 0.72–0.77 for CIE‐LAB space). Between 12 and 14 photographs per species are necessary to achieve this averaging effect for interspecific studies. Unsurprisingly, the CS photographs taken with commercial cameras failed to capture information in the UV part of the spectrum. For intraspecific questions, decreasing levels of control increase the color variation but averaging larger sample sizes can partially mitigate this, aside from particular issues related to saturation and irregularities in light capture.
4. CS photographs offer a very large sample size across space and time which offers statistical power for many color research questions. This study shows that CS photographs contain data that lines up closely with controlled measurements within the visual spectrum if the sample size is large enough, highlighting the potential of CS photographs for both interspecific and intraspecific ecological or biological questions. With regard to analyzing color in CS photographs, we suggest, as a starting point, to measure multiple random points within the ROI of each photograph for both patterned and unpatterned patches and approach the recommended sample size of 12–14 photographs per species for interspecific studies. Overall, this study provides groundwork in analyzing the reliability of a novel method, which can propel the field of studying color forward.

     

Interacting forces of predation and fishing affect species’ maturation size

1. Fishing is a strong selective force and is supposed to select for earlier maturation at smaller body size. However, the extent to which fishing‐induced evolution is shaping ecosystems remains debated. This is in part because it is challenging to disentangle fishing from other selective forces (e.g., size‐structured predation and cannibalism) in complex ecosystems undergoing rapid change.
2. Changes in maturation size from fishing and predation have previously been explored with multi‐species physiologically structured models but assumed separation of ecological and evolutionary timescales. To assess the eco‐evolutionary impact of fishing and predation at the same timescale, we developed a stochastic physiologically size‐structured food‐web model, where new phenotypes are introduced randomly through time enabling dynamic simulation of species'' relative maturation sizes under different types of selection pressures.
3. Using the model, we carried out a fully factorial in silico experiment to assess how maturation size would change in the absence and presence of both fishing and predation (including cannibalism). We carried out ten replicate stochastic simulations exposed to all combinations of fishing and predation in a model community of nine interacting fish species ranging in their maximum sizes from 10 g to 100 kg. We visualized and statistically analyzed the results using linear models.
4. The effects of fishing on maturation size depended on whether or not predation was enabled and differed substantially across species. Fishing consistently reduced the maturation sizes of two largest species whether or not predation was enabled and this decrease was seen even at low fishing intensities (F = 0.2 per year). In contrast, the maturation sizes of the three smallest species evolved to become smaller through time but this happened regardless of the levels of predation or fishing. For the four medium‐size species, the effect of fishing was highly variable with more species showing significant and larger fishing effects in the presence of predation.
5. Ultimately our results suggest that the interactive effects of predation and fishing can have marked effects on species'' maturation sizes, but that, at least for the largest species, predation does not counterbalance the evolutionary effect of fishing. Our model also produced relative maturation sizes that are broadly consistent with empirical estimates for many fish species.

     

The visual ecology of selective predation: Are unhealthy hosts less stealthy hosts?

Predators can strongly influence disease transmission and evolution, particularly when they prey selectively on infected hosts. Although selective predation has been observed in numerous systems, why predators select infected prey remains poorly understood. Here, we use a mathematical model of predator vision to test a long‐standing hypothesis about the mechanistic basis of selective predation in a Daphnia–microparasite system, which serves as a model for the ecology and evolution of infectious diseases. Bluegill sunfish feed selectively on Daphnia infected by a variety of parasites, particularly in water uncolored by dissolved organic carbon. The leading hypothesis for selective predation in this system is that infection‐induced changes in the transparency of Daphnia render them more visible to bluegill. Rigorously evaluating this hypothesis requires that we quantify the effect of infection on the visibility of prey from the predator''s perspective, rather than our own. Using a model of the bluegill visual system, we show that three common parasites, Metschnikowia bicuspidata, Pasteuria ramosa, and Spirobacillus cienkowskii, decrease the transparency of Daphnia, rendering infected Daphnia darker against a background of bright downwelling light. As a result of this increased brightness contrast, bluegill can see infected Daphnia at greater distances than uninfected Daphnia—between 19% and 33% further, depending on the parasite. Pasteuria and Spirobacillus also increase the chromatic contrast of Daphnia. These findings lend support to the hypothesis that selective predation by fish on infected Daphnia could result from the effects of infection on Daphnia''s visibility. However, contrary to expectations, the visibility of Daphnia was not strongly impacted by water color in our model. Our work demonstrates that models of animal visual systems can be useful in understanding ecological interactions that impact disease transmission.     

Agent‐based modeling of the effects of forest dynamics,selective logging,and fragment size on epiphyte communities

1. Forest canopies play a crucial role in structuring communities of vascular epiphytes by providing substrate for colonization, by locally varying microclimate, and by causing epiphyte mortality due to branch or tree fall. However, as field studies in the three‐dimensional habitat of epiphytes are generally challenging, our understanding of how forest structure and dynamics influence the structure and dynamics of epiphyte communities is scarce.
2. Mechanistic models can improve our understanding of epiphyte community dynamics. We present such a model that couples dispersal, growth, and mortality of individual epiphytes with substrate dynamics, obtained from a three‐dimensional functional–structural forest model, allowing the study of forest–epiphyte interactions. After validating the epiphyte model with independent field data, we performed several theoretical simulation experiments to assess how (a) differences in natural forest dynamics, (b) selective logging, and (c) forest fragmentation could influence the long‐term dynamics of epiphyte communities.
3. The proportion of arboreal substrate occupied by epiphytes (i.e., saturation level) was tightly linked with forest dynamics and increased with decreasing forest turnover rates. While species richness was, in general, negatively correlated with forest turnover rates, low species numbers in forests with very‐low‐turnover rates were due to competitive exclusion when epiphyte communities became saturated. Logging had a negative impact on epiphyte communities, potentially leading to a near‐complete extirpation of epiphytes when the simulated target diameters fell below a threshold. Fragment size had no effect on epiphyte abundance and saturation level but correlated positively with species numbers.
4. Synthesis: The presented model is a first step toward studying the dynamic forest–epiphyte interactions in an agent‐based modeling framework. Our study suggests forest dynamics as key factor in controlling epiphyte communities. Thus, both natural and human‐induced changes in forest dynamics, for example, increased mortality rates or the loss of large trees, pose challenges for epiphyte conservation.

     

Aggressive mimicry in a coral reef fish: The prey's view

Since all forms of mimicry are based on perceptual deception, the sensory ecology of the intended receiver is of paramount importance to test the necessary precondition for mimicry to occur, that is, model‐mimic misidentification, and to gain insight in the origin and evolutionary trajectory of the signals. Here we test the potential for aggressive mimicry by a group of coral reef fishes, the color polymorphic Hypoplectrus hamlets, from the point of view of their most common prey, small epibenthic gobies and mysid shrimp. We build visual models based on the visual pigments and spatial resolution of the prey, the underwater light spectrum and color reflectances of putative models and their hamlet mimics. Our results are consistent with one mimic‐model relationship between the butter hamlet H. unicolor and its model the butterflyfish Chaetodon capistratus but do not support a second proposed mimic‐model pair between the black hamlet H. nigricans and the dusky damselfish Stegastes adustus. We discuss our results in the context of color morphs divergence in the Hypoplectrus species radiation and suggest that aggressive mimicry in H. unicolor might have originated in the context of protective (Batesian) mimicry by the hamlet from its fish predators rather than aggressive mimicry driven by its prey.     

Robust and simplified machine learning identification of pitfall trap‐collected ground beetles at the continental scale

1. Insect populations are changing rapidly, and monitoring these changes is essential for understanding the causes and consequences of such shifts. However, large‐scale insect identification projects are time‐consuming and expensive when done solely by human identifiers. Machine learning offers a possible solution to help collect insect data quickly and efficiently.
2. Here, we outline a methodology for training classification models to identify pitfall trap‐collected insects from image data and then apply the method to identify ground beetles (Carabidae). All beetles were collected by the National Ecological Observatory Network (NEON), a continental scale ecological monitoring project with sites across the United States. We describe the procedures for image collection, image data extraction, data preparation, and model training, and compare the performance of five machine learning algorithms and two classification methods (hierarchical vs. single‐level) identifying ground beetles from the species to subfamily level. All models were trained using pre‐extracted feature vectors, not raw image data. Our methodology allows for data to be extracted from multiple individuals within the same image thus enhancing time efficiency, utilizes relatively simple models that allow for direct assessment of model performance, and can be performed on relatively small datasets.
3. The best performing algorithm, linear discriminant analysis (LDA), reached an accuracy of 84.6% at the species level when naively identifying species, which was further increased to >95% when classifications were limited by known local species pools. Model performance was negatively correlated with taxonomic specificity, with the LDA model reaching an accuracy of ~99% at the subfamily level. When classifying carabid species not included in the training dataset at higher taxonomic levels species, the models performed significantly better than if classifications were made randomly. We also observed greater performance when classifications were made using the hierarchical classification method compared to the single‐level classification method at higher taxonomic levels.
4. The general methodology outlined here serves as a proof‐of‐concept for classifying pitfall trap‐collected organisms using machine learning algorithms, and the image data extraction methodology may be used for nonmachine learning uses. We propose that integration of machine learning in large‐scale identification pipelines will increase efficiency and lead to a greater flow of insect macroecological data, with the potential to be expanded for use with other noninsect taxa.

     

Ultraviolet components offer minimal contrast enhancement to an aposematic signal

Aposematic and sexual signals are often characterized by bright, highly contrasting colors. Many species can see colors beyond the human visible spectrum, and ultraviolet (UV) reflection has been found to play an important role in communication and sexual selection. However, the role of UV in aposematic signals is poorly explored. Poison frogs frequently produce high‐contrast signals that have been linked to both aposematism and intraspecific communication. Yet despite considerable efforts studying interspecific and intraspecific diversity in color, poison frogs are not known to perceive UV, and UV reflection of the integument has not been described. We report UV‐reflective spots in a population of Oophaga sylvatica and quantify the effect of UV on visual contrast with models of avian vision. We found that the frogs are highly contrasting, but UV had a minimal effect on signal saliency. These data highlight the importance of considering UV reflectance within aposematic signals, but that UV should not necessarily be regarded as an independent signal.     

Drivers of diversity and community structure of bees in an agroecological region of Zimbabwe

1. Worldwide bees provide an important ecosystem service of plant pollination. Climate change and land‐use changes are among drivers threatening bee survival with mounting evidence of species decline and extinction. In developing countries, rural areas constitute a significant proportion of the country''s land, but information is lacking on how different habitat types and weather patterns in these areas influence bee populations.
2. This study investigated how weather variables and habitat‐related factors influence the abundance, diversity, and distribution of bees across seasons in a farming rural area of Zimbabwe. Bees were systematically sampled in five habitat types (natural woodlots, pastures, homesteads, fields, and gardens) recording ground cover, grass height, flower abundance and types, tree abundance and recorded elevation, temperature, light intensity, wind speed, wind direction, and humidity. Zero‐inflated models, censored regression models, and PCAs were used to understand the influence of explanatory variables on bee community composition, abundance, and diversity.
3. Bee abundance was positively influenced by the number of plant species in flower (p < .0001). Bee abundance increased with increasing temperatures up to 28.5°C, but beyond this, temperature was negatively associated with bee abundance. Increasing wind speeds marginally decreased probability of finding bees.
4. Bee diversity was highest in fields, homesteads, and natural woodlots compared with other habitats, and the contributions of the genus Apis were disproportionately high across all habitats. The genus Megachile was mostly associated with homesteads, while Nomia was associated with grasslands.
5. Synthesis and applications. Our study suggests that some bee species could become more proliferous in certain habitats, thus compromising diversity and consequently ecosystem services. These results highlight the importance of setting aside bee‐friendly habitats that can be refuge sites for species susceptible to land‐use changes.

     

Spatial structure of reproductive success infers mechanisms of ungulate invasion in Nearctic boreal landscapes

1. Landscape change is a key driver of biodiversity declines due to habitat loss and fragmentation, but spatially shifting resources can also facilitate range expansion and invasion. Invasive populations are reproductively successful, and landscape change may buoy this success.
2. We show how modeling the spatial structure of reproductive success can elucidate the mechanisms of range shifts and sustained invasions for mammalian species with attendant young. We use an example of white‐tailed deer (deer; Odocoileus virginianus) expansion in the Nearctic boreal forest, a North American phenomenon implicated in severe declines of threatened woodland caribou (Rangifer tarandus).
3. We hypothesized that deer reproductive success is linked to forage subsidies provided by extensive landscape change via resource extraction. We measured deer occurrence using data from 62 camera traps in northern Alberta, Canada, over three years. We weighed support for multiple competing hypotheses about deer reproductive success using multistate occupancy models and generalized linear models in an AIC‐based model selection framework.
4. Spatial patterns of reproductive success were best explained by features associated with petroleum exploration and extraction, which offer early‐seral vegetation resource subsidies. Effect sizes of anthropogenic features eclipsed natural heterogeneity by two orders of magnitude. We conclude that anthropogenic early‐seral forage subsidies support high springtime reproductive success, mitigating or exceeding winter losses, maintaining populations.
5. Synthesis and Applications. Modeling spatial structuring in reproductive success can become a key goal of remote camera‐based global networks, yielding ecological insights into mechanisms of invasion and range shifts to inform effective decision‐making for global biodiversity conservation.

     

A modified niche model for generating food webs with stage‐structured consumers: The stabilizing effects of life‐history stages on complex food webs

1. Almost all organisms grow in size during their lifetime and switch diets, trophic positions, and interacting partners as they grow. Such ontogenetic development introduces life‐history stages and flows of biomass between the stages through growth and reproduction. However, current research on complex food webs rarely considers life‐history stages. The few previously proposed methods do not take full advantage of the existing food web structural models that can produce realistic food web topologies.
2. We extended the niche model developed by Williams and Martinez (Nature, 2000, 404, 180–183) to generate food webs that included trophic species with a life‐history stage structure. Our method aggregated trophic species based on niche overlap to form a life‐history structured population; therefore, it largely preserved the topological structure of food webs generated by the niche model. We applied the theory of allometric predator–prey body mass ratio and parameterized an allometric bioenergetic model augmented with biomass flow between stages via growth and reproduction to study the effects of a stage structure on the stability of food webs.
3. When life‐history stages were linked via growth and reproduction, more food webs persisted, and persisting food webs tended to retain more trophic species. Topological differences between persisting linked and unlinked food webs were small to modest. The slopes of biomass spectra were lower, and weak interaction links were more prevalent in the linked food webs than the unlinked ones, suggesting that a life‐history stage structure promotes characteristics that can enhance stability of complex food webs.
4. Our results suggest a positive relationship between the complexity and stability of complex food webs. A life‐history stage structure in food webs may play important roles in dynamics of and diversity in food webs.

     

Age‐specific habitat preference,carrying capacity,and landscape structure determine the response of population spatial variability to fishing‐driven age truncation

1. Understanding the mechanisms underlying spatial variability of exploited fish is critical for the sustainable management of fish stocks. Empirical studies suggest that size‐selective fishing can elevate fish population spatial variability (i.e., more heterogeneous distribution) through age truncation, making the population less resilient to changing environment. However, species differ in how their spatial variability responds to age truncation and the underlying mechanisms remain unclear.
2. We hypothesize that age‐specific habitat preference, together with environmental carrying capacity and landscape structure, determines the response of population spatial variability to fishing‐induced age truncation. To test these hypotheses, we design an individual‐based model of an age‐structured fish population on a two‐dimensional landscape under size‐selective fishing. Individual fish reproduces and survives, and moves between habitats according to age‐specific habitat preference and density‐dependent habitat selection.
3. Population spatial variability elevates with increasing age truncation, and the response is stronger for populations with stronger age‐specific habitat preference. On a gradient landscape, reducing carrying capacity elevates the relative importance of density dependence in habitat selection, which weakens the response of spatial variability to age truncation for populations with strong age‐specific habitat preference. On a fragmented landscape, both populations with strong and weak age‐specific habitat preferences are restricted at local optimal habitats, and reducing carrying capacity weakens the responses of spatial variability to age truncation for both populations.
4. Synthesis and applications. We demonstrate that to track and predict the changes in population spatial variability under exploitation, it is essential to consider the interactive effects of age‐specific habitat preference, carrying capacity, and landscape structure. To improve spatial management in fisheries, it is crucial to enhance empirical and theoretical developments in the methodology to quantify age‐specific habitat preference of marine fish, and to understand how climatic change influences carrying capacity and landscape continuity.

     

Using Delaunay triangulation to sample whole‐specimen color from digital images

1. Color variation is one of the most obvious examples of variation in nature, but biologically meaningful quantification and interpretation of variation in color and complex patterns are challenging. Many current methods for assessing variation in color patterns classify color patterns using categorical measures and provide aggregate measures that ignore spatial pattern, or both, losing potentially important aspects of color pattern.
2. Here, we present Colormesh, a novel method for analyzing complex color patterns that offers unique capabilities. Our approach is based on unsupervised color quantification combined with geometric morphometrics to identify regions of putative spatial homology across samples, from histology sections to whole organisms. Colormesh quantifies color at individual sampling points across the whole sample.
3. We demonstrate the utility of Colormesh using digital images of Trinidadian guppies (Poecilia reticulata), for which the evolution of color has been frequently studied. Guppies have repeatedly evolved in response to ecological differences between up‐ and downstream locations in Trinidadian rivers, resulting in extensive parallel evolution of many phenotypes. Previous studies have, for example, compared the area and quantity of discrete color (e.g., area of orange, number of black spots) between these up‐ and downstream locations neglecting spatial placement of these areas. Using the Colormesh pipeline, we show that patterns of whole‐animal color variation do not match expectations suggested by previous work.
4. Colormesh can be deployed to address a much wider range of questions about color pattern variation than previous approaches. Colormesh is thus especially suited for analyses that seek to identify the biologically important aspects of color pattern when there are multiple competing hypotheses or even no a priori hypotheses at all.

     

Modeling the demography of species providing extended parental care: A capture–recapture multievent model with a case study on polar bears (Ursus maritimus)

1. In species providing extended parental care, one or both parents care for altricial young over a period including more than one breeding season. We expect large parental investment and long‐term dependency within family units to cause high variability in life trajectories among individuals with complex consequences at the population level. So far, models for estimating demographic parameters in free‐ranging animal populations mostly ignore extended parental care, thereby limiting our understanding of its consequences on parents and offspring life histories.
2. We designed a capture–recapture multievent model for studying the demography of species providing extended parental care. It handles statistical multiple‐year dependency among individual demographic parameters grouped within family units, variable litter size, and uncertainty on the timing at offspring independence. It allows for the evaluation of trade‐offs among demographic parameters, the influence of past reproductive history on the caring parent''s survival status, breeding probability, and litter size probability, while accounting for imperfect detection of family units. We assess the model performance using simulated data and illustrate its use with a long‐term dataset collected on the Svalbard polar bears (Ursus maritimus).
3. Our model performed well in terms of bias and mean square error and in estimating demographic parameters in all simulated scenarios, both when offspring departure probability from the family unit occurred at a constant rate or varied during the field season depending on the date of capture. For the polar bear case study, we provide estimates of adult and dependent offspring survival rates, breeding probability, and litter size probability. Results showed that the outcome of the previous reproduction influenced breeding probability.
4. Overall, our results show the importance of accounting for i) the multiple‐year statistical dependency within family units, ii) uncertainty on the timing at offspring independence, and iii) past reproductive history of the caring parent. If ignored, estimates obtained for breeding probability, litter size, and survival can be biased. This is of interest in terms of conservation because species providing extended parental care are often long‐living mammals vulnerable or threatened with extinction.

     

Plotting receiver operating characteristic and precision–recall curves from presence and background data

1. The receiver operating characteristic (ROC) and precision–recall (PR) plots have been widely used to evaluate the performance of species distribution models. Plotting the ROC/PR curves requires a traditional test set with both presence and absence data (namely PA approach), but species absence data are usually not available in reality. Plotting the ROC/PR curves from presence‐only data while treating background data as pseudo absence data (namely PO approach) may provide misleading results.
2. In this study, we propose a new approach to calibrate the ROC/PR curves from presence and background data with user‐provided information on a constant c, namely PB approach. Here, c defines the probability that species occurrence is detected (labeled), and an estimate of c can also be derived from the PB‐based ROC/PR plots given that a model with good ability of discrimination is available. We used five virtual species and a real aerial photography to test the effectiveness of the proposed PB‐based ROC/PR plots. Different models (or classifiers) were trained from presence and background data with various sample sizes. The ROC/PR curves plotted by PA approach were used to benchmark the curves plotted by PO and PB approaches.
3. Experimental results show that the curves and areas under curves by PB approach are more similar to that by PA approach as compared with PO approach. The PB‐based ROC/PR plots also provide highly accurate estimations of c in our experiment.
4. We conclude that the proposed PB‐based ROC/PR plots can provide valuable complements to the existing model assessment methods, and they also provide an additional way to estimate the constant c (or species prevalence) from presence and background data.

     

Hot stuff in the bushes: Thermal imagers and the detection of burrows in vegetated sites

1. Thermal imaging technology is a developing field in wildlife management. Most thermal imaging work in wildlife science has been limited to larger ungulates and surface‐dwelling mammals. Little work has been undertaken on the use of thermal imagers to detect fossorial animals and/or their burrows. Survey methods such as white‐light spotlighting can fail to detect the presence of burrows (and therefore the animals within), particularly in areas where vegetation obscures burrows. Thermal imagers offer an opportunity to detect the radiant heat from these burrows, and therefore the presence of the animal, particularly in vegetated areas. Thermal imaging technology has become increasingly available through the provision of smaller, more cost‐effective units. Their integration with drone technology provides opportunities for researchers and land managers to utilize this technology in their research/management practices.
2. We investigated the ability of both consumer (<AUD$20,000) and professional imagers (>AUD$65,000) mounted on drones to detect rabbit burrows (warrens) and entrances in the landscape as compared to visual assessment.
3. Thermal imagery and visual inspection detected active rabbit warrens when vegetation was scarce. The presence of vegetation was a significant factor in detecting entrances (p < .001, α = 0.05). The consumer imager did not detect as many warren entrances as either the professional imager or visual inspection (p = .009, α = 0.05). Active warren entrances obscured by vegetation could not be accurately identified on exported imagery from the consumer imager and several false‐positive detections occurred when reviewing this footage.
4. We suggest that the exportable frame rate (Hz) was the key factor in image quality and subsequent false‐positive detections. This feature should be considered when selecting imagers and suggest that a minimum export rate of 30 Hz is required. Thermal imagers are a useful additional tool to aid in identification of entrances for active warrens and professional imagers detected more warrens and entrances than either consumer imagers or visual inspection.

     

Linking behavioral states to landscape features for improved conservation management

1. A central theme for conservation is understanding how animals differentially use, and are affected by change in, the landscapes they inhabit. However, it has been challenging to develop conservation schemes for habitat‐specific behaviors.
2. Here we use behavioral change point analysis to identify behavioral states of golden eagles (Aquila chrysaetos) in the Sonoran and Mojave Deserts of the southwestern United States, and we identify, for each behavioral state, conservation‐relevant habitat associations.
3. We modeled behavior using 186,859 GPS points from 48 eagles and identified 2,851 distinct segments comprising four behavioral states. Altitude above ground level (AGL) best differentiated behavioral states, with two clusters of short‐distance movement behaviors characterized by low AGL (state 1 AGL = 14 m (median); state 2 AGL = 11 m) and two associated with longer‐distance movement behaviors and characterized by higher AGL (state 3 AGL = 108 m; state 4 AGL = 450 m).
4. Behaviors such as perching and low‐altitude hunting were associated with short‐distance movements in updraft‐poor environments, at higher elevations, and over steeper and more north‐facing terrain. In contrast, medium‐distance movements such as hunting and transiting were over gentle and south‐facing slopes. Long‐distance transiting occurred over the desert habitats that generate the best updraft.
5. This information can guide management of this species, and our approach provides a template for behavior‐specific habitat associations for other species of management concern.

     

Spatial capture–recapture with random thinning for unidentified encounters

1. Spatial capture–recapture (SCR) models have increasingly been used as a basis for combining capture–recapture data types with variable levels of individual identity information to estimate population density and other demographic parameters. Recent examples are the unmarked SCR (or spatial count model), where no individual identities are available and spatial mark–resight (SMR) where individual identities are available for only a marked subset of the population. Currently lacking, though, is a model that allows unidentified samples to be combined with identified samples when there are no separate classes of “marked” and “unmarked” individuals and when the two sample types cannot be considered as arising from two independent observation models. This is a common scenario when using noninvasive sampling methods, for example, when analyzing data on identified and unidentified photographs or scats from the same sites.
2. Here we describe a “random thinning” SCR model that utilizes encounters of both known and unknown identity samples using a natural mechanistic dependence between samples arising from a single observation model. Our model was fitted in a Bayesian framework using NIMBLE.
3. We investigate the improvement in parameter estimates by including the unknown identity samples, which was notable (up to 79% more precise) in low‐density populations with a low rate of identified encounters. We then applied the random thinning SCR model to a noninvasive genetic sampling study of brown bear (Ursus arctos) density in Oriental Cantabrian Mountains (North Spain).
4. Our model can improve density estimation for noninvasive sampling studies for low‐density populations with low rates of individual identification, by making use of available data that might otherwise be discarded.

     

Thermal ecology and baseline energetic requirements of a large‐bodied ectotherm suggest resilience to climate change

1. Most studies on how rising temperatures will impact terrestrial ectotherms have focused on single populations or multiple sympatric species. Addressing the thermal and energetic implications of climatic variation on multiple allopatric populations of a species will help us better understand how a species may be impacted by altered climates.
2. We used eight years of thermal and behavioral data collected from four populations of Pacific rattlesnakes (Crotalus oreganus) living in climatically distinct habitat types (inland and coastal) to determine the field‐active and laboratory‐preferred body temperatures, thermoregulatory metrics, and maintenance energetic requirements of snakes from each population.
3. Physical models showed that thermal quality was best at coastal sites, but inland snakes thermoregulated more accurately despite being in more thermally constrained environments. Projected increases of 1 and 2°C in ambient temperature result in an increase in overall thermal quality at both coastal and inland sites.
4. Population differences in modeled standard metabolic rate estimates were driven by body size and not field‐active body temperature, with inland snakes requiring 1.6× more food annually than coastal snakes.
5. All snakes thermoregulated with high accuracy, suggesting that small increases in ambient temperature are unlikely to impact the maintenance energetic requirements of individual snakes and that some species of large‐bodied reptiles may be robust to modest thermal perturbations under conservative climate change predictions.

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Targeted and passive environmental DNA approaches outperform established methods for detection of quagga mussels,Dreissena rostriformis bugensis in flowing water

1. The early detection of invasive non‐native species (INNS) is important for informing management actions. Established monitoring methods require the collection or observation of specimens, which is unlikely at the beginning of an invasion when densities are likely to be low. Environmental DNA (eDNA) analysis is a highly promising technique for the detection of INNS—particularly during the early stages of an invasion.
2. Here, we compared the use of traditional kick‐net sampling with two eDNA approaches (targeted detection using both conventional and quantitative PCR and passive detection via metabarcoding with conserved primers) for detection of quagga mussel, Dreissena rostriformis bugensis, a high priority INNS, along a density gradient on the River Wraysbury, UK.
3. All three molecular tools outperformed traditional sampling in terms of detection. Conventional PCR and qPCR both had 100% detection rate in all samples and outperformed metabarcoding when the target species was at low densities. Additionally, quagga mussel DNA copy number (qPCR) and relative read count (metabarcoding) were significantly influenced by both mussel density and distance from source population, with distance being the most significant predictor.
4. Synthesis and application. All three molecular approaches were more sensitive than traditional kick‐net sampling for the detection of the quagga mussel in flowing water, and both qPCR and metabarcoding enabled estimates of relative abundance. Targeted approaches were more sensitive than metabarcoding, but metabarcoding has the advantage of providing information on the wider community and consequently the impacts of INNS.