1. Understanding how ecosystem engineers influence other organisms has long been a goal of ecologists. Woodpeckers select nesting sites with high food availability and will excavate and then abandon multiple cavities throughout their lifetime. These cavities are crucial to secondary cavity nesting birds (SCB) that are otherwise limited by the availability of naturally occurring cavities. 2. Our study examined the influence of food resources on the nest site location and home-range size of woodpeckers, and the subsequent influence of woodpeckers on the nesting success of SCB. 3. Using five years of avian point count data to locate golden-fronted woodpeckers (GFWO), we correlated insect availability with GFWO home range size, determined differences in insect availability between GFWO occupied and unoccupied sites, and compared nesting success for the GFWO and common SCB in south Texas. We used model averaging to fit species-specific logistic regression models to predict nest success based on cavity metrics across all species. 4. Sites occupied by GFWO had a higher biomass of insects in orders Coleoptera, Hymenoptera, and Orthoptera than unoccupied sites, and there was a negative correlation between the availability of these insect orders and home-range size. GFWO nest success increased with vegetation cover and lower levels of tree decay. SCB had higher levels of nesting success in abandoned GFWO, and in trees with lower levels of nest tree decay. 5. Our results suggest that SCB may be drawn to nest in abandoned woodpecker cavities where they have higher rates of nest success compared to natural cavities. Additionally, the prevalence for GFWO to excavate cavities in trees with lower levels of decay contradicts previous literature, and may indicate a novel temperature trade-off, with live trees requiring more energy to excavate, but providing increased protection from high breeding season temperatures in arid and semi-arid areas.
Understanding genetic variation and structure, adaptive genetic variation and its relationship with environmental factors is of great significance to understand how plants adapt to climate change and design effective conservation and management strategies. The objective of this study was to (I) investigate the genetic diversity and structure by AFLP markers in 36 populations of R. aureum from northeast China, (Ⅱ) reveal the relative contribution of geographical and environmental impacts on the distribution and genetic diﬀerentiation of R. aureum; (Ⅲ) identify outlier loci under selection and evaluate the association between outlier loci and environmental factors and (Ⅳ) exactly calculate development trend of population of R. aureum，as it is confronted with severe climate change and to provide information for designing eﬀective conservation and management strategies. We found high genetic variation (I = 0.584) and diﬀerentiation among populations (ΦST = 0.711) and moderate levels of genetic diversity within populations of R. aureum. A significant relationship between genetic distance and environmental distance was identified, which suggested that the differentiation of diﬀerent populations was the caused by environmental factors. Using BayeScan and Dfdist, 42 outlier loci identified and most of the outlier loci are associated with climate or relief factors, suggesting that these loci are linked to genes that are involved in the adaptability of R. aureum to environment. Species distribution models (SDM) showed that climate warming will cause a significant reduction of suitable area for R. aureum especially under the RCP 85 scenario. Our results help to understand the potential response of R. auruem to climatic changes, and provide new perspectives for R. auruem resource management and conservation strategies.
How and why species range size varies along spatial gradients is fundamental yet controversial topics in biogeography. To advance our understanding on these questions and to provide insight into biological conservation, we assessed the elevational variations in vascular plants range size for different life form and biogeographical affinities, and explored the main drivers underlying above variations in the longest valley in China's Himalayas---the Gyirong Valley. Elevational range sizes of vascular plants were documented by 96 sampling plots along 12 elevational bands of 300-m ranging from 1800 to 5400 m above sea level. We assessed the elevational variations in range size by averaging the range size of all species within each elevational band. We then related range size to climate, disturbance, competition factors and the mid-domain effect, and explored the relative importance of aforementioned factors in explaining the range size variations using the Random Forest model. Total 545 vascular plants were documented by our sampling plots along the elevational gradient. Out of 545 plants, 158, 387, 337 and 112 were woody, herbaceous, temperate and tropical species respectively. Range size of each groups of vascular plants shown uniform increasing trends along the elevational gradient which are in accordance with the prediction of Rapoport's rule. Climate was the main driver for the increasing trends of vascular plants range size in the Gyirong Valley. Climate variability hypothesis and mean climate condition hypothesis were both supported to jointly explain such climate-range size relationship. Our results reinforce previous notion that Rapoport's rule applies to where the influence of climate is most pronounced, and call for close attention to the impact of climate change in order to prevent range contraction and even extinction under global warming.
The koala, Phascolarctos cinereus, is an iconic Australian wildlife species, but faces rapid decline in South-East Queensland (SEQLD). For conservation planning, estimating koala populations is crucial. Systematic surveys are the most common approach to estimate koala populations, but such surveys are restricted to small geographic areas, they are costly and conducted infrequently. Public interest and participation in the collection of koala sightings is increasing in popularity, but such data is generally not used for population estimation. We used incidental sightings of koalas reported by members of the public from 1997-2013 in SEQLD to estimate the yearly spatio-temporal koala sightings density. For this, a spatio-temporal point process model was developed accounting for observed koala density, spatio-temporal detection bias and clustering. The density of koalas varied throughout the study period due to the heterogeneous nature of koala habitat in SEQLD, with density estimates ranging between 0.005 to 8.9 koalas per km2. The percentage of land areas with very low sightings densities (0-0.25 koalas per km2) remained similar throughout the study period representing in average (SD) 68.3% (0.06) of the total study area. However, land areas with more koalas per km2 showed larger annual variations, with koala mean (SD) densities of 0.25-0.5, 0.5-1, 1-2, 2-5 and > 5 koalas per km2 representing 16.8% (0.21), 13.8% (0.25), 0.7% (0.20), 0.3% (0.13), and 0.2% (0.1) of the study area in South-East Queensland, respectively.We did find that clustering of koala sightings was not prominently different between the mating and non-mating seasons of koalas. While acknowledging the limitations associated sightings data, we developed a statistical model that addressed the spatio-temporal bias associated with observed koala sightings and provided long-term relative koala density estimates for one of the largest koala populations of Australia.
The evolutionary origins and hybridization patterns of Canis species in North America has been hotly debated for the past 30 years. Disentangling ancestry and timing of hybridization in Great Lakes wolves, eastern Canadian wolves, red wolves, and eastern coyotes is most often partitioned into a 2-species model that assigns all ancestry to grey wolves and/or coyotes, and a 3-species model that includes a third, North American evolved eastern wolf genome. The proposed models address recent or sometimes late Holocene hybridization events but have largely ignored Pleistocene era opportunities for hybridization that may have impacted the current mixed genomes in eastern Canada and the United States. Here, we re-analyze contemporary and ancient mitochondrial DNA genomes with Bayesian phylogenetic analyses to more accurately estimate divergence dates among lineages. We combine that with a review of the literature on Late Pleistocene Canis distributions to illuminate opportunities for ancient hybridization events between extinct Beringian grey wolves (C. lupus) and extinct large wolf-like coyotes (C. latrans orcutti) that we propose as a potentially unrecognized source of introgressed genomic variation within contemporary Canis genomes. These events speak to the potential origins of contemporary genomes and provide a new perspective on Canis ancestry, but do not influence/negate current conservation priorities of dwindling wolf populations with unique genomic signatures and key ecologically critical roles.
1. 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 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 utilise this technology in their research/management practices. 2. We investigated the ability of both consumer (AUD$65,000) mounted on drones to detect rabbit burrows (warrens) and entrances in the landscape as compared to visual assessment. 3. Both types of imager and visual inspection detected active rabbit warrens when vegetation was scarce. The presence of vegetation was a significant factor in detecting entrances (P<0.001, α=0.05). The consumer imager did not detect as many warren entrances as either the professional imager or visual inspection (P=0.009, 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 Hz rate was the key factor in image quality and subsequent false positive detections. This feature should be considered when selecting imagers. 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.
Accurate determination of animal diets is difficult. Methods such as molecular barcoding or metagenomics offer a promising approach, allowing quantitative and sensitive detection of different taxa. Here we show that rapid and inexpensive diet quantification is possible through metagenomic sequencing with the portable Oxford Nanopore Technologies (ONT) MinION. Using an amplification-free approach, we profiled the stomach contents from 24 wild-caught rats. We conservatively identified diet items from over 50 taxonomic orders, ranging across nine phyla, including plants, vertebrates, invertebrates, and fungi. This highlights the wide range of taxa that can be identified using this simple approach. We calibrated the accuracy of this method by comparing the characteristics of reads matching the ground-truth host genome (rat) to those matching diet items, and show that at the family-level, taxon assignments are approximately 97.5% accurate. Some inaccuracies may arise from database biases; we suggest a way to mitigate for database biases when using metagenomic approaches. Finally, we implemented a constrained ordination analysis and show that we can identify the sampling location of an individual rat within tens of kilometres based on diet content alone. This work establishes proof-of-principle for long-read metagenomic methods in quantitative diet analysis. We show that diet content can be quantified even with limited expertise, using a simple, amplification free workflow and a relatively inexpensive and accessible next generation sequencing method. Continued increases in the accuracy and throughput of ONT sequencing, along with improved genomic databases, suggests that a metagenomic approach for quantification of animal diets will become an important method in the future.
White-tailed bumblebee species, Bombus cryptarum, B. lucorum, B. magnus and B. terrestris are known to be very similar in their morphological characters across the majority of their ranges. This hampers assessment of their status and trends because reliable identification is difficult. In this study, we use a combination of characters and methods to assess how ecologists and citizen scientists can reliably and quickly separate these four species occurring in the Netherlands. Bumblebees (queens, workers and males) were sampled from 10 locations across the Netherlands and specimens were identified based on COI sequence data. Next, the same specimens where scored for morphological traits. We show that a combination of easy to recognise characteristics can separate some specimens of the species depending on caste and sex. Bombus magnus males and queens and B. lucorum males were most reliably separated from the other species using morphological characters. Workers of all four species cannot be separated completely using morphological characters alone. This is the first time standard morphological characters and ecological data has been used to study the differences between the white-tailed bumblebees in the Netherlands. Based on our findings we need to conclude that the status of these bumblebee species in the Netherlands is uncertain due to possible misidentifications in the past and present. People who wish to work with these species should be careful in species identification based on morphology.
Senna didymobotrya is invasive native flowering shrubs mainly grow in Africa. Climate change thought to facilitates the introduction and spread of invasive alien species. The present study aimed at examining the present and future invasion of S. didymobotrya under the changing climatic using species distribution modeling. The mean AUC and TSS value of the model was (95%) and (81%), respectively, which put the model under an excellent category. Our result showed under the current climatic conditions 18.11% of the continent is suitable for S. didymobotrya invasion. Eastern African countries are found the most suitable habitat for S. didymobotrya invasion followed by southern African countries. The total highly suitable area for the species is 3.4% and 3.17% in 2050s under RCP4.5 and RCP8.5, respectively. In the 2070s, the highly suitable area is predicted as 3.18 % and 2.73% in RCP4.5 and RCP8.5, respectively. An area with the category of low to moderate suitability under RCP 4.5 and RCP8.5 in the 2050s is projected as 17.4 % and 20.5 % and this area is increased in the 2070s to19.11% and 22.82 for the RCP 4.5 and RCP 8.5, respectively. The results of this study showed a substantial contraction in the high suitability areas, but a large increase in the low and moderately suitable habitat. Despite the contraction in highly suitable areas, countries which are found suitable in the present climatic condition remains suitable for S. didymobotrya establishment. Our ensemble predicted a significant increase in the vulnerability of habitat for invasion under the future climatic scenarios. Our study suggests the future biodiversity conservation strategy and policy direction should focus on the means and strategy of limiting the rate of expansion of invasion and distribution in different ecosystem types, hence reduce the expected harm in the ecosystem services.
Seabirds, particularly Procellariiformes, are highly mobile organisms with a great capacity for long dispersal, though simultaneously showing high philopatry, two conflicting characteristics that may lead to contrasted patterns of genetic population structure. Landmasses were suggested to explain differentiation patterns observed in seabirds, but philopatry, isolation-by-distance, segregation between breeding and non-breeding zones, and oceanographic conditions (sea surface temperatures) may also contribute to differentiation patterns. No study has simultaneously contrasted the multiple factors contributing to the diversification of seabird species, especially in the grey zone of speciation. We conducted a multi-locus phylogeographic study on a widespread shearwater species complex (Puffinus lherminieri/bailloni), showing highly homogeneous morphology. We sequenced three mitochondrial and six nuclear markers on all extant populations (five nominal lineages, 13 populations). We found sharp differentiation among populations separated by the African continent with both mitochondrial and nuclear markers, while only mitochondrial markers allowed characterizing the five nominal lineages. No differentiation could be detected within these five lineages, questioning the strong level of philopatry showed by these shearwaters. Finally, we propose that Atlantic populations likely originated from the Indian Ocean. Within the Atlantic, a stepping-stone process accounts for the current distribution. Based on our divergence times estimates, we suggest that the observed pattern of differentiation mostly resulted from variation in sea surface temperatures.
We argue the advantages of field-based learning experiences for undergraduates, the societal imperative for training the next generation of field biologists, and the opportunity to increase the reach of field education dictate that we must meet the challenges of delivering field experiences in the context of a distanced educational environment. We report on our experiences as faculty and students in a spring 2020 Field Ornithology course adapted for remote delivery with an example of a student-centered framework for supporting independent field study. Feedback from students and instructors in this course indicate that remote field instruction is both possible and desirable. We suggest that an instruction model involving guided, independent field study can yield strong learning outcomes and promote self-directed inquiry. Based on reflections of the challenges and successes of our experiences, we provide an prompts for a for assessing the feasibility and desirability of proceeding with field-based education in a distanced environment with an emphasis on supporting student success.
Scientific activities including university classes, wet lab research activities, fieldwork, and seminars/conferences have been cancelled in response to the ongoing COVID-19 pandemics. While the public health priority was to contain and mitigate the outbreak, the science sector swiftly adopted technologies to stay connected and continue the scientific activities as much as possible. Creativity, ingenuity, and resilience abound in the science community manifested in successful examples of truly global activities such as seminar series and conferences. While these platforms were initially concerned with maintaining the continuum of science education and dissemination, they attracted participants beyond the boundaries of their respective institutions and countries and thereby increased the equity. While the communities and countries are easing the societal restrictions and the scientific community returns to on-site work, it is important to learn the lessons and ensure equity in science education and dissemination moving forward.
Distance learning has been a means to provide an education to those who are unable to participate in on-campus, face-to face classes. Teams of instructional design specialists that focus on online education put significant effort into course development. This planned process is very different from emergency remote education in response to a crisis. In early 2020, it was discovered that an extremely contagious respiratory illness termed COVID-19 had spread to every corner of the earth. As of mid-March 2020, the need to transition from face-to-face classroom instruction to exclusively online education landed on the doorstep of America’s universities. COVID-19 has catalyzed a transition in the ecology of American education for all students, but especially the underserved and minoritized. Ecology, by definition, is concerned with the interactions of an organism and its environment. The circumstances of the pandemic have caused vast and rapid change in both the internal and external environments of the organisms (e.g., students) and the systems in which they reside (e.g., U. S. educational systems). The purpose of this paper is to provide some considerations for instructors who find themselves “thrown into teaching remotely,” and help them think about how best to create sustainable systems, broaden participation and build capacity in a more equitable and inclusive manner.
The forest people around the world through their indigenous knowledge contribute to the sustainable management of forests. This article argues that the Sheka people in southwestern Ethiopia by their ecological knowledge, values, and spiritual use could manage the Ororo tree (Ekebergia capensis). The Ororo tree (Ekebergia capensis) is one of the most important endemic tree species in the Sheka zone southwestern Ethiopia and, at the same time, one of the most endangered species. Data collected on the indigenous ecological knowledge of the Sheka people and how the Ororo tree could be managed and conserved through the DEDO culture documented and the spiritual connection between the Ororo trees and the Sheka people traditional belief system measured. The findings revealed that through their traditional forest-related knowledge, the Sheka people conserve and manage a single larger tree called Ororo. The Ororo tree is a special type of tree that has cultural and spiritual attachments that are presently non-existent. This unique forest conservation practice has been referred to as the DEDO culture. The culture of DEDO comes up with worshiping around the Ororo tree. Thus, the culture of DEDO played an important role in maintaining the conservation of the DEDO sacred tree (Ororo) and biodiversity therein. Over time, the DEDO sacred tree (Ororo) conservation culture has been decline, and various factors have contributed to the decline of this useful ecological knowledge.
Inherent in climate change experiments is the assumption that researchers seek to understand the impacts of contemporary climate change and not the impacts of changes in the abiotic environment that are not predicted to occur. In general, climate warming is expected to be asymmetrical, with a mean increase in temperature that is driven more by warming at night rather than during the day. However, climate warming experiments tend to disproportionately increase daytime temperatures. If day and night warming have different effects on ecosystems, the mismatch in timing may produce misleading inference about the effects of climate change. To better understand how the timing of warming affects species and their interactions, we examined a food chain of lady beetles, aphids and host plants within environmental chambers programmed to simulate four w treatments (ambient, constant warming, day warming, and night warming). Our results show that the timing of warming influences predators and their interactions with prey in several ways. In plant-only treatments, all warming treatments increased plant above-ground biomass. When aphids were added, the positive direct effect of warming on plants disappeared, and night-warming indirectly reduced plant biomass more than the day- and constant-warming treatments. Although our feeding trial experiments found that lady beetles in day-warming treatments consumed the most aphids in a 24 hour period, predators generated a trophic cascade in only the night warming treatment. Our results contributes to mounting evidence predators can mediate the effects of climate warming and that these predators are affected by day and night warming differently.
Seed predators have the potential to act as agents of natural selection that influence seed traits. Accordingly, plants deploy a variety of mechanisms (e.g. resistance and tolerance strategy) to lessen the impact of predation on seed crop or on an individual seed. In this study, we found a novel mechanism (i.e. cloning strategy) in a tropical plant species in countering animal predation. We found both rodent damaged and human artificially damaged seed fragments of a large-seeded tree Garcinia xanthochymus in the Xishuangbanna tropical forest of China could develop into seedlings in both field and laboratory conditions. G. xanthochymus seed has no endosperm in seeds, and its seed tissue own strong capacity of differentiation and cloning. Seed damage would negatively affect seedling growth and germination, but the seed germination rate was remarkably high. Our study suggests that, as a novel strategy countering animal predation, seed cloning would play a significant role in stabilizing the mutualism between plant and animals.
In district Haripur, KPk, Pakistan Treepie Dendrocitta vagabunda parvula (Latham, 1790) (Passeriformes: Corvidae), is a widespread resident bird commonly found. Feeding and Food habits of Treepie were studied by direct focal observation method analysis of gut content and faecal matter. Treepie prefers tree and cultivation areas insects for foraging activities, feeding on animal and plant is an omnivore items ranging from vertebrate species to invertebrate. Feeding upon like red palm weevil, grasshopper, cockroaches, banana stem weevil, nestlings of squirrel and house rat, it feeds up on many pests of agricultural crops Treepie is an important biocontrol agent in the agro ecosystem of the region
Manual assessment of flower abundance of different flowering plant species in grasslands is a time consuming process. We present an automated approach to determine the flower abundance in grasslands from drone images using a deep learning (Faster R-CNN) object detection approach, which is trained and evaluated on data of five flights and two sites. Our deep learning network is able to identify and classify individual flowers. The novel method allows generating spatially explicit maps of flower abundance that meets or exceeds the accuracy of the manually counted extrapolation method and is less labor intensive. The results are very good for some types of flowers with precision and recall being close to or higher than $90\ \%$. Other flowers are detected poorly due to reasons such as lack of enough training data, appearance changes due to phenology or flowers being too small to be reliably distinguishable on the aerial images. The method is able to give precise estimates of the abundance of many flowering plant species. The collection of more training data will allow better predictions in the future for the flowers that are not well predicted yet. The developed pipeline can be applied to any sort of aerial object detection problems.