The thermal environment limits species ranges through its influence on physiology and resource distributions
and thus affects species richness patterns over broad spatial scales. Understanding how temperature drives
species richness patterns is particularly important in the context of global change and for effective conservation
planning. Landsat 8's Thermal Infrared Sensor (TIRS) allows direct mapping of temperature at moderate spatial
resolutions (100 m, downscaled by the USGS to 30 m), overcoming limitations inherent in coarse interpolated
weather station data that poorly capture fine-scale temperature patterns over broad areas. TIRS data thus offer
the unique opportunity to understand how the thermal environment influences species richness patterns. Our
aim was to develop and assess the ability of TIRS-based temperature metrics to predict patterns of winter bird
richness across the conterminous United States during winter, a period of marked temperature stress for birds.
We used TIRS data from 2013-2018 to derive metrics of relative temperature and intra-seasonal thermal heterogeneity.
To quantify winter bird richness across the conterminous US, we tabulated the richness only for
resident bird species, i.e., those species that do not move between the winter and breeding seasons, from the
North American Breeding Bird Survey, the most extensive survey of birds in the US. We expected that relative
temperature and thermal heterogeneity would have strong positive associations with winter bird richness because
colder temperatures heighten temperature stress for birds, and thermal heterogeneity is a proxy for
thermal niches and potential thermal refugia that can support more species. We further expected that both the
strength of the effects and the relative importance of these variables would be greater for species with greater
climate sensitivity, such as small-bodied species and climate-threatened species (i.e., those with large discrepancies
between their current and future distributions following projected climate change). Consistent with
our predictions, relative temperature and thermal heterogeneity strongly positively influenced winter bird
richness patterns, with statistical models explaining 37.3% of the variance in resident bird richness. Thermal
heterogeneity was the strongest predictor of small-bodied and climate-threatened species in our models, whereas
relative temperature was the strongest predictor of large-bodied and climate-stable species. Our results demonstrate
the important role that the thermal environment plays in governing winter bird richness patterns and
highlight the previously underappreciated role that intra-seasonal thermal heterogeneity may have in supporting
high winter bird species richness. Our findings thus illustrate the exciting potential for TIRS data to guide
conservation planning in an era of global change.
The thermal environment limits species ranges through its influence on physiology and resource distributions
Habitat loss is the primary driver of biodiversity decline worldwide, but the effects of fragmentation (the spatial
arrangement of remaining habitat) are debated. We tested the hypothesis that forest fragmentation sensitivity—
affected by avoidance of habitat edges—should be driven by historical exposure to, and therefore species’
evolutionary responses to disturbance. Using a database containing 73 datasets collected worldwide (encompassing
4489 animal species), we found that the proportion of fragmentation-sensitive species was nearly three times
as high in regions with low rates of historical disturbance compared with regions with high rates of disturbance
(i.e., fires, glaciation, hurricanes, and deforestation). These disturbances coincide with a latitudinal gradient
in which sensitivity increases sixfold at low versus high latitudes. We conclude that conservation efforts to limit
edges created by fragmentation will be most important in the world’s tropical forests.
While walking through a forest in spring we often marvel at the vivid greenness, listen to birdsong, and mind our steps in order not to get into a spider’s web. Enjoying the moment, we usually do not think about the complexity of this environment, nor the intertwined relations among all of its elements. However, what slips our attention is not going unrecognized by Maia Persche – a Master’s candidate in the SILVIS lab. In her research, Maia seeks to discern the role of topography in the timing of vegetation growth onset within forest, and to understand how topographic position potentially shapes songbird habitat.
To gain insight into these questions, Maia undertook the challenging tasks of measuring tree phenology, and conducting invertebrate and bird surveys in her study area in the Baraboo Hills of Southern Wisconsin. In order to relate these data to each other, each type of survey was carried out at the same 70 locations during narrow time windows throughout the season. Tree phenology surveys occurred in April and May, and invertebrate and bird surveys were repeated throughout the bird breeding season, or until the end of July. At each location, additional data was collected on temperature, tree species composition, and site characteristics. Over the course of two field seasons, she detected 53 insectivorous bird species, and tracked the seasonal abundance of common invertebrate orders (Lepidoptera, Araneae, Hemiptera, Hymenoptera, Diptera and Coleoptera).
Based on only a portion of measurements collected, Maia has already drawn some interesting preliminary conclusions. Trees leafed out slightly later in stream gorges than in uplands, and although invertebrate biomass was related to tree phenology, it did not appear to follow a predictable yearly pattern. However, sheltered stream gorges supporteded high invertebrate biomass during the mid- and late summer. This could be important for double-brooded bird species that still have active nests in July and can be limited by food availability in some habitats. Overall, stream gorges supported the highest bird species richness, perhaps due to stable food resources or habitat complexity. Also, a strong association has become evident between particular tree species and invertebrate orders, suggesting that tree composition may be more important than topographic context for some folivorous invertebrates.
Under shifting climate conditions in deciduous forests, it is important to identify areas where habitat quality for species is likely to remain high. To assess bird territory quality in different topographic situations, Maia used feather growth bar analysis for a few widely distributed forest species (Wood Thrush, Red-eyed Vireo, and Ovenbird). She captured birds throughout her study area using mist nets, playback calls, and bird models. She then banded the birds, took structural measurements, and pulled one tail feather. Growth bars, or horizontal bands along the feather, correspond to diet richness of the bird while the feather was growing, and will be used to assess social dominance and habitat quality. Although this approach provides a detailed look at habitat quality, it is also the most difficult to carry out in the field.
Maia has collected a large amount of data, and analyzing the relationships among different factors and trophic levels is somewhat daunting, but she approaches it with great enthusiasm. Maia is currently working to determine how bird territory density varies according to topographic context. It is definitively worth staying tuned to see what new results Maia uncovers!
The Caucuses region (encompassing parts of Russia, Georgia, Armenia and Azerbaijan) has experienced extreme political upheavals. The collapse of the Soviet Union meant that the four countries became sovereign. Their powerful neighbors — Russia, Iran and Turkey – maintained strong geopolitical interests in the newly independent nations of Georgia, Armenia and Azerbaijan. As a result, the Caucasus has experienced four armed conflicts since 1991. In light of such extreme social and political disruption, Johanna wanted to know how cropland and forests had changed.
From previous research, some by former SILVIS lab members Drs. Mihai Nita and Catalina Munteanu, we know that some areas in Eastern Europe saw rapid cropland abandonment after the USSR collapsed. Other areas experienced forest clearing during the soviet era, and forest regrowth afterwards. Why do countries that are ostensibly similar geopolitically show such a wide range of land use outcomes?
“I want to make a clear link between land use and socio-political changes, but to do that you first have to describe where and when the land use changes have taken place.” Johanna says. To do that, she used Landsat imagery from 1987 to 2015 and mapped changes in land use and land cover.
Johanna found that there was some cropland abandonment in the Caucasus, particularly during the transition period in the 1990s and the time of armed conflicts. However, the cropland abandonment rate is far lower than the one apparent in eastern European countries that also experienced the breakdown of the Soviet Union. She has also found that forest as stayed surprisingly steady during the study period in the Caucasus.
Her findings are rather surprising, since we expect political instability to interfere with cropland, and to make forests vulnerable for illegal harvesting. But in the Caucasus, Johanna explains, the steep, inaccessible terrain may have protected the forests from large clear cuts; even though the extracting of single valuable trees is widespread. Cropland, on the other hand is related to demand for food: cultivation continued wherever possible, unless we find armed conflicts in the region.
“What I can say is that land use patterns and outcomes are extremely dependent on the local context, especially in such a diverse region like the Caucasus” Johanna cautioned.
During the Pleistocene, red fox (Vulpes vulpes) populations in North America were isolated in glacial refugia
and diverged into 3 major lineages: the Nearctic-Eastern subclade of eastern Canada, the Nearctic-Mountain
subclade of the western mountains, and the Holarctic clade of Alaska. Following glacial retreats, these genetically
distinct populations of foxes expanded into newly available habitat. Along with subsequent translocation from fur
farms, these expansions have resulted in red foxes now occupying most of the continent. The origin of foxes that
colonized the Great Lakes Region, however, remains unknown. Furthermore, it is unclear whether contemporary
populations inhabiting this region are the result of natural range expansion or if foxes released from fur farms
colonized the landscape in the 1900s. To determine the origin of red foxes in the Great Lakes Region, we collected
genetic samples from 3 groups: 1) contemporary wild foxes, 2) historical wild foxes collected before fur farming,
and 3) fur-farmed foxes from a contemporary fur farm. We constructed a network of mtDNA haplotypes to identify
phylogeographic relationships between the 3 sample groups, and examined genetic signatures of fur-farmed
foxes via the androgen receptor gene (AR) associated with tame phenotypes. Historical wild foxes demonstrated
natural colonization from all 3 major North American lineages, which converged within the Great Lakes Region,
and contemporary wild foxes maintained the historically high genetic diversity. Most contemporary wild foxes
also matched haplotypes of fur-farmed foxes; however, AR was not useful in distinguishing fur-farm origins
in samples of contemporary wild foxes. Our results show that geographically disparate populations naturally
merged in the Great Lakes Region before fur-farmed foxes were introduced. Due to the historically high genetic
diversity in the Great Lakes Region, any introductions from fur farms likely contributed to, but did not create, the
genetic structure observed in this region.
This is a publication uploaded with a php script
Ph.D. student Kristin Brunk works in the old-growth redwoods of central California to understand the efficacy of current management for Steller’s Jays (Cyanocitta stelleri) and the implications of this management for the federally threatened Marbled Murrelet (Brachyramphus marmoratus). Both are native bird species in the redwoods, but Steller’s Jays are a synanthropic species, meaning they benefit from associating with humans, while Marbled Murrelet populations have severely declined. As populations of Steller’s Jays have increased, they have threatened the viability of Marbled Murrelet populations mainly through nest predation. Nowhere has this threat been more dire than in protected campground areas in remnant patches of old-growth forest. These areas have Steller’s Jay populations that are twice as high as in non-human dominated forests, and these campground areas also represent 60% of all remaining Marbled Murrelet nesting habitat in central California.
Murrelet reproduction is naturally slow, as adults only produce one chick per year, but in central California where Steller’s Jay populations are subsidized by human foods, about 80% of Marbled Murrelet nests fail, due mostly to predation. Reducing corvid predation would help boost murrelet reproduction, which is believed to offer the highest probability of Marbled Murrelet population recovery in central California. In 2013, in an attempt to combat corvid predation, California State Parks implemented multiple non-lethal strategies to manage Steller’s Jays. These included improving trash management, deploying noxious murrelet mimic eggs to create taste aversion to murrelet eggs in corvids, and the “Crumb Clean” campaign, an effort to educate campers about the harm of feeding corvids and eliminate corvid access to camper food. The crumb clean campaign requires campers to properly store or dispose of all foodstuffs in their camp. Through the elimination of this food source in the campgrounds, the hope is that jay populations will decrease, allowing more murrelet nests to succeed. Brunk’s research focuses on comparing jay density, home range size, body condition, and diet between pre- and post-management jay populations to determine if these management strategies have been successful.
Brunk focuses her work within the campgrounds of Big Basin Redwoods State Park by capturing Steller’s Jays in mist nets. Once she has captured a jay, Brunk takes a tail feather sample to determine the bird’s body condition and a flight feather sample to determine what the bird has been eating. Body condition is determined by measuring feather growth bars, and Brunk deciphers how much human food the jays eat by performing stable isotope analyses on flight feather samples. Each jay is also banded with a unique color combination, so individuals can be identified without re-capturing them, and males are fitted with a backpack-mounted radio-transmitter. By tracking birds with radio-transmitters, Brunk is able to understand how jay home range sizes have changed since management started. Despite a perpetual battle of wits with the extremely intelligent Steller’s Jays, Brunk has successfully banded about 85% of the jays in her study area.
In addition to her research, Brunk is also incredibly active in education and outreach throughout her study area. She gives talks at Big Basin Campfire Programs to educate the public about Marbled Murrelets and Steller’s Jays. Brunk conducts banding demonstrations so campers can see exactly how she captures the jays, and they can often participate in the release of banded jays. And as she walks through the campgrounds tracking birds with radio-transmitters, she frequently answers campers’ questions about the giant metal antenna she is carrying. Brunk works hard to foster good relationships with the other users of her study area and is passionate about sharing her work to promote better public understanding of management initiatives such as the crumb clean campaign.
Brunk plans to complete one more field season in 2019, but her research is far from over. Brunk is also working to evaluate a Habitat Conservation Plan (HCP) and its effectiveness at conserving Marbled Murrelet habitat on private land. Habitat Conservation Plans are a commonly used management strategy, with over 1000 HCPs currently active, but the efficacy of these plans has not been well-tested. Brunk hopes to determine if HCPs are an effective management technique, using the Marbled Murrelet as a case study. Overall, Brunk’s research aims to understand the effectiveness of management strategies and conservation of federally threatened species. Ultimately, what she discovers will be used directly in adaptive management strategies that will be paramount in preventing the extinction of the Marbled Murrelet. Along the way, Brunk hopes to uncover strategies and techniques that will apply to the conservation of other species in the future.
Humans are rapidly transforming the Earth’s ecosystems, with profound consequences for biodiversity. To predict how species will respond to rapidly changing environments, biodiversity science needs better datasets of biodiversity patterns and species distribution. Dr. Laura Farwell is part of a team on a mission to advance and broaden the use of Landsat satellite data for biodiversity science by characterizing habitat heterogeneity at a medium resolution (30 m), across the conterminous U.S.
Ecological processes influence patterns of species diversity at multiple scales, and landscape grain strongly affects habitat niches and thus biodiversity potential. Vertebrate species in particular tend to select habitat based on parameters acting at multiple scales. For example, several bird species might strongly prefer large patches of primary forests at broader scales, but at a finer scale habitat selection might be strongly influenced by the amount of heterogeneity within habitat patches. Habitat heterogeneity can also influence species diversity patterns as a result of specialization by certain species on different habitat types. And in general, high heterogeneity increases opportunities for species coexistence. It has been hypothesized that avian diversity is strongly influenced by local scale ecosystem patterns. Vegetation structure is one example of a local scale characteristic that many birds seem to key in on, particularly for nest site selection. But collecting these types of data on the ground is logistically difficult and time consuming. If we can characterize habitat heterogeneity using remotely sensed images, this can potentially be a powerful tool for biodiversity science, allowing rapid classification of vegetation, as well as inference about habitat quality and ecological niches.
A set of indices collectively called image texture holds promise for meeting this need. These indices characterize the amount and pattern of contrast in the tonal values of adjacent pixels, a product of the unique spectral signature of different plant species and combinations within the area covered by the pixels. First-order image texture measures differences in spectral values within a defined neighborhood (e.g., a 3×3 window) surrounding each pixel. More advanced image texture analysis involves 2nd-order texture measures based on a spectral value co-occurrence matrix (GLCM) or local indicators of spatial autocorrelation. It has previously been shown that image texture measures are powerful predictors of avian species richness, in an upper Midwestern U.S. grassland-savanna-woodland system, and in a desert- ecosystem. Building on what has been learned in previous studies, Laura will calculate two 1st-order textures (range and standard deviation), two 2nd-order textures (contrast and angular second moment), plus one local indicator of spatial autocorrelation (the G* statistic).
A strength of Laura’s project is the use of Landsat data at 30 m resolution as the basis of texture measures, as this resolution is relevant to many animal species. Laura will characterize image texture across the entire conterminous U.S. She will calculate texture of two different Landsat products- NDVI (which indicates vegetation greenness) and the SWIR band (which highlights leaf and soil moisture content). She will also calculate texture of the cumulative Dynamic Habitat Index currently being derived by PhD student Elena Razenkova, which characterizes plant productivity.
Dynamic Habitat Indices (DHI) have been used to understand and predict patterns of species richness across the globe, but Elena Razenkova has found a new application for these new remotely sensed measures of productivity. Elena found that DHI was correlated with Moose abundance over the last three decades in the former USSR and current Russia.
Moose are important for subsistence, culture, and ecosystem function across much of the boreal region of the northern hemisphere. Like many species that occur at high latitudes, they experience population fluctuations from year to year, which can be difficult to predict. Elena used a long-term data set of Moose winter track counts in the former USSR and Russia from 1981 to 2010 to determine how Moose abundance has fluctuated over time.
Elena hypothesized that changes in ecosystem productivity from year to year may contribute to changes in Moose populations; however, because Moose occupy such a broad geographic area, measuring productivity on the ground would be a difficult task. NASA’s earth observing satellite-mounted MODIS (Moderate Resolution Imaging Spectroradiometer), collects data on Earth’s environmental conditions over time, which can be used to develop Dynamic Habitat Indices going back decades.
Dynamic Habitat Indices provide summaries of vegetation productivity over time, which is correlated with the richness of animal species in a given area. Vegetation productivity is also thought to affect the reproduction and survival of many animal species, leading to changes in their abundance over time. Dynamic habitat indices include cumulative productivity, minimum productivity, and variation in productivity, making them a comprehensive data source to test whether Moose abundance is correlated with productivity over the last 30 years in the USSR and Russia.
Elena found that DHI along with other environmental data such as climate, explained 79% of the variation in moose abundance in the different administrative regions of the USSR and Russia. The predictive power of the DHI model decreased somewhat from the 1980s to the 2000s, suggesting a possible role for increases in human-induced changes in Moose abundance, corresponding to the breakup of the USSR.
Elena’s research demonstrates an exciting new use for DHI: understanding and predicting the abundance of individual animal species. This may have important applications in determining animal abundance over time and across broad spatial extents. Elena hopes to look at patterns of abundance of several other animal species to determine if DHI is an equally important predictor of abundance among different taxonomic and functional groups. DHI could also serve as a helpful resource to predict how the abundance of some animal species will change in response to global changes that affect vegetation productivity and seasonality.
This is a publication uploaded with a php script
Many animal and plant species found in areas where they did not occur in the past. These newcomers are known as invasive species. The consequences of having a new species could benefit the system by bringing new ecosystem services to the areas such as new pollinators for crops. Unfortunately in many cases the new species can have negative impacts at the community level by competing with local species and even displacing them. Diana is particularly interested in a species that has had mainly negative consequences for other species in places wherever it was introduced, the mongoose. Mongooses ( Herpestes auropunctatus) are native from India, and were introduced to Caribbean and Pacific islands at the end of the 20th century. These predators were brought into the area to control rats (another invasive) that were affecting sugarcane plantations. However, mongooses didn’t only eat rats it also local island species such as birds, amphibians and reptiles. Therefore this new species caused the decline and extinction of local species without eradicating the rat problem.
Local and federal agencies have tried to remove or reduce populations of mongoose from the islands but have failed because mongoose populations grew rapidly. Although they are omnivorous, mongooses keep predate especially local populations of ground nesting birds and marine tortoises among other species. However, there is little knowledge of the extent of the problem: how mongooses behave, its biology in the island, which species is eating the most or how the populations are related within and between islands.
Diana is studying mongooses in Puerto Rico from multiple angles, to have a bigger picture of the problem. She wants to know where the mongooses populations are and how well connected the populations are to each other. She considers that populations that are connected are more difficult to manage, because removed mongooses will be easily replaced by individuals of adjacent connected populations. Diana will use molecular techniques to identify these connection patterns and how are natural or artificial barriers and other habitat features in the landscape limiting mongoose dispersal. She also wants to know what are preferred prey species of different populations of mongoose. By using stable isotopes, she will track the source of food of mongooses.
Ultimately, Diana will have a sense of how the overall island community of wildlife species is assembled, having this predator already stablished from over a century. This information will be useful for wildlife managers and biologist who will know how the mongoose is distributed and prioritize areas to control the populations. With information about the trophic position and links of this predator, she will provide the base for research questions related to novel animal community assemblies and resilience after species introductions.