Interactions between multiple anthropogenic environmental changes can
drive non-additive effects in ecological systems, and the non-additive
effects can in turn be amplified or dampened by spatial covariation
among environmental changes. We investigated the combined effects of
night-time warming and light pollution on pea aphids and two predatory
ladybeetle species. As expected, neither night-time warming nor light pollution
changed the suppression of aphids by the ladybeetle species that
forages effectively in darkness. However, for the more-visual predator,
warming and light had non-additive effects in which together they
caused much lower aphid abundances. These results are particularly relevant
for agriculture near urban areas that experience both light
pollution and warming from urban heat islands. Because warming and
light pollution can have non-additive effects, predicting their possible
combined consequences over broad spatial scales requires knowing how
they co-occur. We found that night-time temperature change since 1949
covaried positively with light pollution, which has the potential to increase
their non-additive effects on pea aphid control by 70% in US alfalfa. Our
results highlight the importance of non-additive effects of multiple
environmental factors on species and food webs, especially when these
factors co-occur.
File: Miller2017_LightPollution_ProcB.pdf
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Identifying which species are at greatest risk, what makes them vulnerable, and where they
are distributed are central goals for conservation science. While knowledge of which factors
influence extinction risk is increasingly available for some taxonomic groups, a deeper
understanding of extinction correlates and the geography of risk remains lacking. Here, we
develop a predictive random forest model using both geospatial and mammalian species'
trait data to uncover the statistical and geographic distributions of extinction correlates. We
also explore how this geography of risk may change under a rapidly warming climate. We
found distinctive macroecological relationships between species-level risk and extinction
correlates, including the intrinsic biological traits of geographic range size, body size and
taxonomy, and extrinsic geographic settings such as seasonality, habitat type, land use and
human population density. Each extinction correlate exhibited ranges of values that were
especially associated with risk, and the importance of different risk factors was not geographically
uniform across the globe. We also found that about 10% of mammals not currently
recognized as at-risk have biological traits and occur in environments that predispose
them towards extinction. Southeast Asia had the most actually and potentially threatened
species, underscoring the urgent need for conservation in this region. Additionally, nearly
40% of currently threatened species were predicted to experience rapid climate change at
0.5 km/year or more. Biological and environmental correlates of mammalian extinction risk
exhibit distinct statistical and geographic distributions. These results provide insight into
species-level patterns and processes underlying geographic variation in extinction risk.
They also offer guidance for future conservation research focused on specific geographic
regions, or evaluating the degree to which species-level patterns mirror spatial variation in
the pressures faced by populations within the ranges of individual species. The added
impacts from climate change may increase the susceptibility of at-risk species to extinction
and expand the regions where mammals are most vulnerable globally.
File: Davidson2017_MammalExtinct_Plos1.pdf
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Conservation priorities that are based on species distribution,
endemism, and vulnerability may underrepresent biologically
unique species as well as their functional roles and evolutionary
histories. To ensure that priorities are biologically comprehensive,
multiple dimensions of diversity must be considered. Further,
understanding how the different dimensions relate to one another
spatially is important for conservation prioritization, but the
relationship remains poorly understood. Here, we use spatial
conservation planning to (i) identify and compare priority regions
for global mammal conservation across three key dimensions of
biodiversity—taxonomic, phylogenetic, and traits—and (ii) determine
the overlap of these regions with the locations of threatened
species and existing protected areas. We show that priority areas
for mammal conservation exhibit low overlap across the three
dimensions, highlighting the need for an integrative approach
for biodiversity conservation. Additionally, currently protected
areas poorly represent the three dimensions of mammalian biodiversity.
We identify areas of high conservation priority among
and across the dimensions that should receive special attention
for expanding the global protected area network. These highpriority
areas, combined with areas of high priority for other taxonomic
groups and with social, economic, and political considerations,
provide a biological foundation for future conservation
planning efforts.
File: Brum2017_mammals_PNAS.pdf
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Many systems and processes in ecology cannot be experimentally controlled, either because the temporal and spatial scales are
too broad, or because it would be unethical. Examples include large wildfires, alternative conservation strategies, removal of top
predators, or the introduction of invasive species. Unfortunately, many of these phenomena also do not occur randomly in time or
space, and this can lead to different biases (selection bias, unobserved variable bias) in statistical analyses. Economics has evolved
largely without experiments, and developed statistical approaches to study “quasi-experiments”, i.e., situations were changes
in time or space reveal relationships even in the absence of a controlled experiment. The goal of our paper was to compare and
evaluate four quasi-experimental statistical approaches commonly used in economics, (1) matching, (2) regression discontinuity
design, (3) difference-in-differences models, and (4) instrumental variables, in terms of their relevance for ecological research.
We contrast the strengths and weaknesses of each approach and provide a detailed tutorial to demonstrate these approaches. We
suggest that quasi-experimental methods offer great potential for investigating many phenomena and processes in ecological
and coupled human-natural systems. Furthermore, quasi-experimental methods are common in environmental policy research
and policy recommendations by ecologists may be more valuable when based on these methods.
File: Butsic2017_Quasi_BAE.pdf
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Aim: Examining the biogeography of body size is crucial for understanding how animal communities
are assembled and maintained. In tetrapods, body size varies predictably with temperature,
moisture, productivity seasonality and topographical complexity. Although millennial-scale human
pressures are known to have led to the extinction of primarily large-bodied tetrapods, human pressure
history is often ignored in studies of body size that focus on extant species. Here, we analyse
11,377 tetrapod species of the Western Hemisphere to test whether millennial-scale human pressures
have left an imprint on contemporary body mass distributions throughout the tetrapod
clade.
Location: Western Hemisphere.
Time period: Contemporary.
Major taxa studied: Tetrapods (birds, mammals, amphibians and reptiles).
Methods: We mapped the distribution of assemblage-level median tetrapod body mass at a resolution
of 110 km across the Western Hemisphere. We then generated multivariate models of
median body mass as a function of temperature, moisture, productivity seasonality and topographical
complexity, as well as two variables capturing the history of human population density and
human-induced land conversion over the past 12,000 years. We controlled for both spatial and
phylogenetic autocorrelation effects on body mass–environment relationships.
Results: Human pressures explain a small but significant portion of geographical variation in
median body mass that cannot be explained by ecological constraints alone. Overall, the median
body mass of tetrapod assemblages is lower than expected in areas with a longer history of high
human population density and land conversion, but there are important differences among tetrapod
classes.
Main conclusions: At this broad scale, the effect of human pressure history on tetrapod body
mass is low relative to that of ecology. However, ignoring spatial variation in the history of human
pressure is likely to lead to bias in studies of the present-day functional composition of tetrapod
assemblages, at least in areas that have long been influenced by humans.
File: Rapacciuolo_et_al-2017-Global_Ecology_and_Biogeography.pdf
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Satellite telemetry is a powerful tool for monitoring animal movements, and Argos transmitters have been widely used. Unfortunately, only few studies have systematically evaluated the performance of Argos satellite collars for wildlife monitoring. We tested Argos satellite telemetry transmitters at two power levels in Southern Russia (five transmitters at 0.5 W and three at 1 W). Performance metrics were derived from the number and accuracy of location estimates and the number of days on which collars transmitted or failed to transmit data. Our results suggest that the performance of Argos collars in our study region was poor. At the power level of 0.5 W, 55% of the sessions resulted in at least one transmission, but only 21% provided a location estimate. The percentage of successful sessions did not increase much after setting the power level to 1.0 W (63%), but the increase in the number of location estimates was considerable (54%). At either power level, the majority of the location estimates were in the low quality classes though (80% nonstandard locations with 0.5 Wand 45% with 1 W). Positional accuracies were 0.5, 0.7, 1.5, and 4.6 km for location classes 3, 2, 1, and 0, respectively. For nonstandard location classes A and B, positional accuracies were 2.1 and 18.3 km. Careful testing of transmitters is recommended before deployment, as the location of the study area can seriously affect performance.
File: Dubinin2010_Article_PerformanceAndAccuracyOfArgosT.pdf
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Maintaining habitat and its connectivity is amajor conservation goal, especially for large carnivores. Assessments
of habitat connectivity are typically based on the output of habitat suitability models to first map potential habitat,
and then identify where corridors exist. This requires separating habitat from non- habitat, thus one must
choose specific thresholds for both habitat suitability and the minimum patch size that can be occupied. The selection
of these thresholds is often arbitrary, and the effects of threshold choice on assessments of connectivity
are largely unknown. We sought to quantify howhabitat-suitability and patch-size thresholds influence connectivity
assessments for jaguars (Panthera onca) in the Sierra Gorda Biosphere Reserve in central Mexico. We
modeled potential habitat for jaguars using the species distribution modeling algorithm Maxent, and assessed
potential habitat connectivity with the landscape connectivity software Conefor Sensinode. We repeated these
analyses for 45 combinations of habitat suitability based thresholds and minimum patch sizes. Our results indicated
that the thresholds influenced connectivity assessments greatly, and different combinations of the two
thresholds yielded vastly different map configurations of suitable habitat for jaguars.We developed an approach
to identify the pair of thresholds that bestmatched the jaguar occurrence points based on the connectivity scores.
Among the combinations that we tested, a threshold of 0.3 for habitat suitability and 2 km2 for minimum patch
size produced the best fit (area under the curve=0.9). Surprisingly, we found lowsuitable habitat for jaguars in
most of the core areas of the reserve according to our best potential habitatmodel, but highly suitable areas in the
buffer zones and just outside of the reserve. We conclude that the best and most connected potential areas for
jaguar habitat are in the central eastern part of the Sierra Gorda. More broadly, landscape connectivity analyses
appears to be highly sensitive to the thresholds used to identify suitable habitat, and we recommend conducting
sensitivity analyses as introduced here to identify the optimal combination of thresholds.
File: RamirezetaljaguarBioCons2016.pdf
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In many developing countries, high rates of
deforestation and biodiversity loss make conservation
efforts urgent. Improving existing land-use plans can
be an option for enhancing biodiversity conservation.
We showcase an approach to enhancing an existing
forest land-use plan using widely available data and
spatial tools, focusing on Argentina’s Southern Yungas
ecoregion. We mapped the distribution of wilderness
areas and species and habitats of conservation concern,
assessed their representation in the land-use plan and
quantified potential changes in habitat availability
and forest connectivity. Wilderness comprised 48%
of the study area, and the highest concentrations
of elements of conservation concern were in the
north. In the current land-use plan, wilderness areas
often occur in regions where logging and grazing are
allowed, and a large proportion of the forest with
the highest conservation value (43%) is under some
level of human influence. Furthermore, we found
that deforestation being legally allowed in the landuse
plan could reduce forest connectivity and habitat
availability substantially. We recommend updating
the current land-use plan by considering human
influence and elements of conservation concern. More
broadly, we demonstrate that widely available spatial
datasets and straightforward approaches can improve
the usefulness of existing land-use plans so that they
more fully incorporate conservation goals.
File: Martinuzzi2018_enhancing_biodiversity_conservation_EnvCons.pdf
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Land-use is transforming habitats across the globe, thereby threatening wildlife. Large mammals are especiall affected because they require large tracts of intact habitat and functioning corridors between core habita areas. Accurate land-cover data is critical to identify core habitat areas and corridors, and medium resolution sensor such as Landsat 8 provide opportunities to map land cover for conservation planning. Here, we used all availabl Landsat 8 imagery from launch through December 2014 to identify large mammal corridors and assess thei quality across the Caucasus Mountains (N700,000 km ). Specifically, we tested the usefulness of seasonal imag composites (spring, summer, fall, and winter) and a range of image metrics (e.g., mean and median reflectanc across all clear observations) to map nine land-cover classes with a Random Forest classifier. Using image composite from all four seasons yielded markedly higher overall accuracy than using single-season composites (8 increase) and the inclusion of image metrics further improved the classification significantly. Our final land-cove map had an overall accuracy of 85%. Using our land-cover map, we parameterized connectivity models for thre generic large mammal groups and identified wildlife corridors and bottlenecks within corridors with cost-distanc modeling and circuit theory. Corridors were numerous (in total, 85, 131, and 132 corridors for our thre mammal groups, respectively), but often had bottlenecks or high average cost along the least-cost path, indicatin limited functioning. Our findings highlight the potential of Landsat 8 composites to support connectivity analyse across large areas, and thus to contribute to conservation planning, and serve as an early warning system fo biodiversity loss in areas where on-the-ground monitoring is challenging, such as in the Caucasus.
File: Bleyhl_etal_2017_RSE.pdf
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