Showing papers in "Ecosphere in 2019"

Grasslands—more important for ecosystem services than you might think

Abstract: Extensively managed grasslands are recognized globally for their high biodiversity and their social and cultural values. However, their capacity to deliver multiple ecosystem services (ES) as parts of agricultural systems is surprisingly understudied compared to other production systems. We undertook a comprehensive overview of ES provided by natural and semi-natural grasslands, using southern Africa (SA) and northwest Europe as case studies, respectively. We show that these grasslands can supply additional non-agricultural services, such as water supply and flow regulation, carbon storage, erosion control, climate mitigation, pollination, and cultural ES. While demand for ecosystems services seems to balance supply in natural grasslands of SA, the smaller areas of semi-natural grasslands in Europe appear to not meet the demand for many services. We identified three bundles of related ES from grasslands: water ES including fodder production, cultural ES connected to livestock production, and population-based regulating services (e.g., pollination and biological control), which also linked to biodiversity. Greenhouse gas emission mitigation seemed unrelated to the three bundles. The similarities among the bundles in SA and northwestern Europe suggest that there are generalities in ES relations among natural and semi-natural grassland areas. We assessed trade-offs and synergies among services in relation to management practices and found that although some trade-offs are inevitable, appropriate management may create synergies and avoid trade-offs among many services. We argue that ecosystem service and food security research and policy should give higher priority to how grasslands can be managed for fodder and meat production alongside other ES. By integrating grasslands into agricultural production systems and land-use decisions locally and regionally, their potential to contribute to functional landscapes and to food security and sustainable livelihoods can be greatly enhanced. (Less)

Wind erosion and dust from US drylands: a review of causes, consequences, and solutions in a changing world

Abstract: Erosion by wind is one of the principal processes associated with land degradation in drylands and is a significant concern to land managers and policymakers globally. In the drylands of North America, millions of tons of soil are lost to wind erosion annually. Of the 60 million ha in the United States identified as most vulnerable to wind erosion (arid and dominated by fine sandy soils), 64% are managed by federal agencies (37 million ha). Here we review the drivers and consequences of wind erosion and dust emissions on drylands in the United States, with an emphasis on actionable responses available to policymakers and practitioners. We find that while dryland soils are often relatively stable when intact, disturbances including fire, domestic livestock grazing, and off‐highway vehicles can increase horizontal eolian flux by an order of magnitude, in some cases as much as 40‐fold. A growing body of literature documents the large‐scale impacts of deposited dust changing the albedo of mountain snow cover and in some cases reducing regional water supplies by ~5%. Predicted future increases in aridity and extreme weather events, including drought, will likely increase wind erosion and consequent dust generation. Under a drier and more variable future climate, new and existing soil‐ and vegetation‐disturbing practices may interact in synergistic ways, with dire consequences for environments and society that are unforeseen to many but fairly predictable given current scientific understanding. Conventional restoration and reclamation approaches, which often entail surface disturbance and rely on adequate moisture to prevent erosion, also carry considerable erosion risk especially under drought conditions. Innovative approaches to dryland restoration that minimize surface disturbance may accomplish restoration or reclamation goals while limiting wind erosion risk. Finally, multidisciplinary and multijurisdictional approaches and perspectives are necessary to understand the complex processes driving dust emissions and provide timely, context‐specific information for mitigating the drivers and impacts of wind erosion and dust.

Tree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale

Abstract: Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10-40% per century under current climate and 20-170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics.

Evaluating the popularity of R in ecology

Abstract: The programming language R is widely used in many fields. We explored the extent of reported R use in the field of ecology using the Web of Science and text mining. We analyzed the frequencies of R packages reported in more than 60,000 peer‐reviewed articles published in 30 ecology journals during a 10‐yr period ending in 2017. The number of studies reported using R as their primary tool in data analysis increased linearly from 11.4% in 2008 to 58.0% in 2017. The top 10 packages reported were lme4, vegan, nlme, ape, MuMIn, MASS, mgcv, ade4, multcomp, and car. The increasing popularity of R has most likely furthered open science in ecological research because it can improve reproducibility of analyses and captures workflows when scripts and codes are included and shared. These findings may not be entirely unique to R because there are other programming languages used by ecologists, but they do strongly suggest that given the relatively high frequency of reported use of R, it is a significant component of contemporary analytics in the field of ecology.

Review: Toward management of urban ponds for freshwater biodiversity

Abstract: Many cities around the world are expanding and this trend in urbanization is expected to sharply increase over coming decades. At the same time, the integration of green and blue spaces is widely promoted in urban development, potentially offering numerous benefits for biodiversity. This is particularly relevant for urban waterbodies, a type of ecosystem present in most cities. However, site managers often lack the knowledge base to promote biodiversity in these waterbodies, which are generally created to provide other ecosystem services. To address this, our review presents guidelines for promoting biodiversity in urban ponds. We found a total of 516 publications indexed in ISI Web of Sciences related to this topic, of which 279 were retained for the purposes of our review. The biodiversity of urban ponds, measured by species richness, appears to be generally lower than in rural ponds; however, urban ponds often support threatened species. Furthermore, if well managed, urban ponds have the potential to support a much greater biodiversity than they currently do. Indeed, this review shows that a range of urban factors can impair or promote pond biodiversity, including many that can easily be controlled by site managers. Local factors include design (surface area, pond depth, banks and margins, shade, shoreline irregularity), water quality (conductivity, nutrients, heavy metals), and hydroperiod and biotic characteristics (stands of vegetation, fish, invasive species). Important regional factors include several indicators of urbanization (roads, buildings, density of population, impervious surfaces, car traffic), and the presence of other wetlands or green spaces in the surrounding landscape. We considered each of these factors and their potential impact on freshwater biodiversity. Taking into account the management measures listed in the publications reviewed, we have proposed a framework for the management of urban ponds, with guidelines to promote biodiversity and other ecosystem services, and to avoid ecosystem disservices or the creation of ecological traps. At the city scale, the biodiversity of a pondscape benefits from a high diversity of pond types, differing in their environmental characteristics and management.

Climate will increasingly determine post-fire tree regeneration success in low-elevation forests, Northern Rockies, USA

Abstract: Climate change is expected to cause widespread shifts in the distribution and abundance of plant species through direct impacts on mortality, regeneration, and survival. At landscape scales, climate impacts will be strongly mediated by disturbances, such as wildfire, which catalyze shifts in species distributions through widespread mortality and by shaping the post-disturbance environment. We examined the potential for regional shifts in low-elevation tree species in response to wildfire and climate warming in low-elevation, dry mixed-conifer forests of the northern Rocky Mountains, USA. We analyzed interactions among climate and wildfire on post-fire tree seedling regeneration 5–13 yr post-fire at 177 sites burned in 21 large wildfires during two years with widespread regional burning. We used generalized additive mixed models to quantify how the density of Douglas-fir and ponderosa pine seedlings varied as a function of climate normals (30-yr mean temperature, precipitation, soil moisture, and evapotranspiration) and fire (tree survivorship, burn severity, and seed source availability). Mean summer temperature was the most important predictor of post-fire seedling densities for both ponderosa pine and Douglas-fir. Seed availability was also important in determining Douglas-fir regeneration. As mean summer temperature continues to increase, however, seed availability will become less important for determining post-fire regeneration. Above a mean summer temperature of 17°C, Douglas-fir regeneration is predicted to be minimal regardless of how close a seed source is to a site. The majority (82%) of our sampled sites are predicted to exceed a mean summer temperature of 17°C by mid-century, suggesting significant declines in seedling densities and potential forest loss. Our results highlight mechanisms linking climate change to shifts in the distribution of two widely dominant tree species in western North America. Under a warming climate, we expect post-fire tree regeneration in these low-elevation forests to become increasingly unsuccessful. Such widespread regeneration failures would have important implications for ecosystem processes and forest resilience, particularly as wildfires increase in response to climate warming.

Thermal Imaging in Plant and Ecosystem Ecology: Applications and Challenges

Abstract: Temperature is a primary environmental control on ecological systems and processes at a range of spatial and temporal scales. The surface temperature of organisms is often more relevant for ecological processes than air temperature, which is much more commonly measured. Surface temperature influences—and is influenced by—a range of biological, physical, and chemical processes, providing a unique view of temperature effects on ecosystem function. Furthermore, surface temperatures vary markedly over a range of temporal and spatial scales and may diverge from air temperature by 40°C or more. Surface temperature measurements have been challenging due to sensor and computational limitations but are now feasible at high spatial and temporal resolutions using thermal imaging. Thus, significant advances in our understanding of plant and ecosystem thermal regimes and their functional consequences are now possible. Thermal measurements may be used to address many ecological questions, such as the thermal controls on plant and ecosystem metabolism and the impact of heat waves and drought. Further advances in this area will require interdisciplinary collaborations among practitioners in fields ranging from physiology to ecosystem ecology to remote sensing and geospatial analysis. In this overview, we demonstrate the feasibility, utility, and potential of thermal imaging for measuring vegetation surface temperatures across a range of scales and from measurement, analysis, and synthesis perspectives.

Living on the edge: Trailing edge forests at risk of fire-facilitated conversion to non-forest

Abstract: Forests are an incredibly important resource across the globe, yet they are threatened by climate change through stressors such as drought, insect outbreaks, and wildfire. Trailing edge forests—those areas expected to experience range contractions under a changing climate—are of particular concern because of the potential for abrupt conversion to non‐forest. However, due to plant‐climate disequilibrium, broad‐scale forest die‐off and range contraction in trailing edge forests are unlikely to occur over short timeframes (<~25–50 yr) without a disturbance catalyst (e.g., wildfire). This underscores that explicit attention to both climate and disturbance is necessary to understand how the distribution of forests will respond to climate change. As such, we first identify the expected location of trailing edge forests in the intermountain western United States by mid‐21st century. We then identify those trailing edge forests that have a high probability of stand‐replacing fire and consider such sites to have an elevated risk of fire‐facilitated transition to non‐forest. Results show that 18% of trailing edge forest and 6.6% of all forest are at elevated risk of fire‐facilitated conversion to non‐forest in the intermountain western United States by mid‐21st century. This estimate, however, assumes that fire burns under average weather conditions. For a subset of the study area (the southwestern United States), we were able to incorporate expected fire severity under extreme weather conditions. For this spatial subset, we found that 61% of trailing edge forest and 30% of all forest are at elevated risk of fire‐facilitated conversion to non‐forest under extreme burning conditions. However, due to compounding error in our process that results in unknowable uncertainty, we urge caution in a strict interpretation of these estimates. Nevertheless, our findings suggest the potential for transformed landscapes in the intermountain western United States that will affect ecosystem services such as watershed integrity, wildlife habitat, wood production, and recreation.

The freshwater biome gradient framework: predicting macroscale properties based on latitude, altitude, and precipitation

Abstract: Understanding global ecological patterns and processes, from biogeochemical to biogeographical, requires broad‐scale macrosystems context for comparing and contrasting ecosystems. Climate gradients (precipitation and temperature) and other continental‐scale patterns shape freshwater environments due to their influences on terrestrial environments and their direct and indirect effects on the abiotic and biotic characteristics of lakes, streams, and wetlands. We combined literature review, analyses of open access data, and logical argument to assess abiotic and biotic characters of freshwater systems across gradients of latitude and elevation that drive precipitation, temperature, and other variability. We explored the predictive value of analyzing patterns in freshwater ecosystems at the global macrosystems scale. We found many patterns based on climate, particularly those dependent upon hydrologic characteristics and linked to characteristics of terrestrial biomes. For example, continental waters of dry areas will generally be widely dispersed and have higher probability of drying and network disconnection, greater temperatures, greater inorganic turbidity, greater salinity, and lower riparian canopy cover relative to areas with high precipitation. These factors will influence local community composition and ecosystem rates. Enough studies are now available at the continental or global scale to start to characterize patterns under a coherent conceptual framework, though considerable gaps exist in the tropics and less developed regions. We present illustrative global‐scale trends of abiotic, biotic, and anthropogenic impacts in freshwater ecosystems across gradients of precipitation and temperature to further understanding of broad‐scale trends and to aid prediction in the face of global change. We view freshwater systems as occurring across arrays of multiple gradients (including latitude, altitude, and precipitation) rather than areas with specific boundaries. While terrestrial biomes capture some variability along these gradients that influence freshwaters, other features such as, slope, geology, and historical glaciation also influence freshwaters. Our conceptual framework is not so much a single hypothesis as a way to logically characterize patterns in freshwaters at scales relevant to (1) evolutionary processes that give rise to freshwater biodiversity, (2) regulatory units that influence freshwater ecosystems, and (3) the current scope of anthropogenic impacts on freshwaters and the vital ecosystem services they provide.

A comprehensive approach to analyzing community dynamics using rank abundance curves

Abstract: Univariate and multivariate methods are commonly used to explore the spatial and temporal dynamics of ecological communities, but each has limitations, including oversimplification or abstraction of communities. Rank abundance curves (RACs) potentially integrate these existing methodologies by detailing species-level community changes. Here, we had three goals: first, to simplify analysis of community dynamics by developing a coordinated set of R functions, and second, to demystify the relationships among univariate, multivariate, and RACs measures, and examine how each is influenced by the community parameters as well as data collection methods. We developed new functions for studying temporal changes and spatial differences in RACs in an update to the R package library(“codyn”), alongside other new functions to calculate univariate and multivariate measures of community dynamics. We also developed a new approach to studying changes in the shape of RAC curves. The R package update presented here increases the accessibility of univariate and multivariate measures of community change over time and difference over space. Next, we use simulated and real data to assess the RAC and multivariate measures that are output from our new functions, studying (1) if they are influenced by species richness and evenness, temporal turnover, and spatial variability and (2) how the measures are related to each other. Lastly, we explore the use of the measures with an example from a long-term nutrient addition experiment. We find that the RAC and multivariate measures are not sensitive to species richness and evenness and that all the measures detail unique aspects of temporal change or spatial differences. We also find that species reordering is the strongest correlate of a multivariate measure of compositional change and explains most community change observed in long-term nutrient addition experiment. Overall, we show that species reordering is potentially an understudied determinant of community changes over time or differences between treatments. The functions developed here should enhance the use of RACs to further explore the dynamics of ecological communities.

Investigating the consequences of climate change under different land-use regimes: a novel experimental infrastructure

Abstract: Climate change and land-use change are considered as the most important threats to ecosystems. Both factors can be expected to have interacting influences on ecosystem functions directly and indirectly via changes in biodiversity. Knowledge about these interactions is limited due to a lack of experiments which investigate climate change effects under different land-use scenarios. Among the processes involved in ecosystem responses to global change, in particular, those occurring in soils or related to biotic interactions and microevolution were underinvestigated in previous experiments. Examinations of these relationships require spatial and temporal scales which go beyond those realized in the majority of ecological field experiments. We introduce a new research facility, the Global Change Experimental Facility (GCEF), which was designed to investigate the consequences of a future climate scenario for ecosystem functioning in different land-use types on large field plots (400 m). Climate manipulation is based on projections for the period of 2070–2100 with an increased temperature and a changed precipitation pattern consisting of reduced precipitation in summer and increased precipitation in spring and autumn. We subject five different land-use types (two farming systems, three grasslands), differing in land-use intensity, to ambient and future climatic conditions. The use of automated roofs and side panels to passively increase night temperatures results in an average increase in daily mean temperature by 0.55°C accompanied by a stronger increase in minimum temperatures (up to 1.14°C in average) with longer frost-free periods and an increase in growing degree days by 5.2%. The combined use of mobile roofs and irrigation systems allows the reduction (in summer by ~20%) and increase in rainfall (in spring and autumn by ~10%) according to future scenarios superimposed on the ambient variation in precipitation. The large plot size and the technical configuration allow the establishment of realistic land-use scenarios and long-term observations of responses of ecosystem functions and community dynamics on relevant temporal and spatial scales. Thus, the GCEF provides a well-suited platform for the interdisciplinary research on the consequences of climate change under different land-use scenarios.

The missing fire: Quantifying human exclusion of wildfire in Pacific Northwest forests, USA

Abstract: Western U.S. wildfire area burned has increased dramatically over the last half‐century. How contemporary extent and severity of wildfires compare to the pre‐settlement patterns to which ecosystems are adapted is debated. We compared large wildfires in Pacific Northwest forests from 1984 to 2015 to modeled historic fire regimes. Despite late twentieth‐century increases in area burned, we show that Pacific Northwest forests have experienced an order of magnitude less fire over 32 yr than expected under historic fire regimes. Within fires that have burned, severity distributions are disconnected from historical references. From 1984 to 2015, 1.6 M ha burned; this is 13.3–18.9 M ha less than expected. Deficits were greatest in dry forest ecosystems adapted to frequent, low‐severity fire, where 7.2–10.3 M ha of low‐severity fire was missing, compared to a 0.2–1.1 M ha deficit of high‐severity fire. When these dry forests do burn, we observed that 36% burned with high‐severity compared to 6–9% historically. We found smaller fire deficits, 0.3–0.6 M ha, within forest ecosystems adapted to infrequent, high‐severity fire. However, we also acknowledge inherent limitations in evaluating contemporary fire regimes in ecosystems which historically burned infrequently and for which fires were highly episodic. The magnitude of contemporary fire deficits and disconnect in burn severity compared to historic fire regimes have important implications for climate change adaptation. Within forests characterized by low‐ and mixed‐severity historic fire regimes, simply increasing wildfire extent while maintaining current trends in burn severity threatens ecosystem resilience and will potentially drive undesirable ecosystem transformations. Restoring natural fire regimes requires management that facilitates much more low‐ and moderate‐severity fire.

Wild bee diversity increases with local fire severity in a fire-prone landscape

Abstract: As wildfire activity increases in many regions of the world, it is imperative that we understand how key components of fire-prone ecosystems respond to spatial variation in fire characteristics. Pollinators provide a foundation for ecological communities by assisting in the reproduction of native plants, yet our understanding of how pollinators such as wild bees respond to variation in fire severity is limited, particularly for forest ecosystems. Here, we took advantage of a natural experiment created by a largescale, mixed-severity wildfire to provide the first assessment of how wild bee communities are shaped by fire severity in mixed-conifer forest. We sampled bees in the Douglas Fire Complex, a 19,000-ha fire in southern Oregon, USA, to evaluate how bee communities responded to local-scale fire severity. We found that fire severity served a strong driver of bee diversity: 20 times more individuals and 11 times more species were captured in areas that experienced high fire severity relative to areas with the lowest fire severity. In addition, we found pronounced seasonality in the local bee community, with more individuals and more species captured during late summer, especially in severely burned regions of the landscape. Two critical habitat components for maintaining bee populations—flowering plants and boring insect exit holes used by cavity-nesting bees—also increased with fire severity. Although we detected shifts in the relative abundance of several bee and plant genera along the fire severity gradient, the two most abundant bee genera (Bombus and Halictus) responded positively to high fire severity despite differences in their typical foraging ranges. Our study demonstrates that within a large wildfire mosaic, severely burned forest contained the most diverse wild bee communities. This finding has particularly important implications for biodiversity in fire-prone areas given the expected expansion of wildfires in the coming decades.

Multigenerational migration of fall armyworm, a pest insect

Abstract: Multigenerational insect migration commonly expands poleward, but meteorological influences are not clearly understood. We coupled biological and physical processes for the agricultural and invasive pest Spodoptera frugiperda (fall armyworm), by modeling its seasonal migration, and comparing simulated migrations to observed captures, and population genetic markers, at a continental scale. Simulations corroborated the spatial distribution and mixing of Texas and Florida source populations defined by genetic haplotypes. Positive relationships were found between first weeks of simulated and observed immigration, and between genetic and simulated metrics. The capacity to project biotic-, migratory-, and meteorology-induced shifts in insect distributions will aid strategic implementation of crop protection measures and economic analyses of host-resistant germplasm deployment in response to a warming climate.

Long-term population dynamics of dreissenid mussels (Dreissena polymorpha and D. rostriformis): a cross-system analysis

Abstract: Deutsche Forschungsgemeinschaft (DFG) [JE 288/8-1]; G.E. Hutchinson Chair at the Cary Institute of Ecosystem Studies (DLS); NSF-LTREB grants [DEB-1556246]; NSF-OPUS grant [DEB-1456532]; DFG [JE 288/9-1, JE 288/9-2]; USGS [G14AC000263]; US EPA [GL00E01184]; Cornell Agricultural Experiment Station [NYC-0226747]; New York State Department of Environmental Conservation grants; NSF [1517823]; Belarusian Republican Foundation for Fundamental Research; Mercator Fellowship; [TaMOP-4.2.2.A-11/1/KONV-2012-0038]; [GINOP-2.3.2-15-2016-00019]

Contributions of fire refugia to resilient ponderosa pine and dry mixed-conifer forest landscapes

Abstract: Altered fire regimes can drive major and enduring compositional shifts or losses of forest ecosystems. In western North America, ponderosa pine and dry mixed‐conifer forest types appear increasingly vulnerable to uncharacteristically extensive, high‐severity wildfire. However, unburned or only lightly impacted forest stands that persist within burn mosaics—termed fire refugia—may serve as tree seed sources and promote landscape recovery. We sampled tree regeneration along gradients of fire refugia proximity and density at 686 sites within the perimeters of 12 large wildfires that occurred between 2000 and 2005 in the interior western United States. We used generalized linear mixed‐effects models to elucidate statistical relationships between tree regeneration and refugia pattern, including a new metric that incorporates patch proximity and proportional abundance. These relationships were then used to develop a spatially explicit landscape simulation model. We found that regeneration by ponderosa pine and obligate‐seeding mixed‐conifer tree species assemblages was strongly and positively predicted by refugia proximity and density. Simulation models revealed that for any given proportion of the landscape occupied by refugia, small patches produced greater landscape recovery than large patches. These results highlight the disproportionate importance of small, isolated islands of surviving trees, which may not be detectable with coarse‐scale satellite imagery. Findings also illustrate the interplay between patch‐scale resistance and landscape‐scale resilience: Disturbance‐resistant settings (fire refugia) can entrain resilience (forest regeneration) across the burn matrix. Implications and applications for land managers and conservation practitioners include strategies for the promotion and maintenance of fire refugia as components of resilient forest landscapes.

Light environment drives the shallow-to-mesophotic coral community transition

Abstract: Light quality is a crucial physical factor driving coral distribution along depth gradients. Currently, a 30 m depth limit, based on SCUBA regulations, separates shallow and deep mesophotic coral ecosystems (MCEs). This definition, however, fails to explicitly accommodate environmental variation. Here, we posit a novel definition for a regional or reef-to-reef outlook of MCEs based on the light vs. coral community–structure relationship. A combination of physical and ecological methods enabled us to clarify the ambiguity in relation to the mesophotic definition. To characterize coral community structure with respect to the light environment, we conducted wide-scale spatial studies at five sites along shallow and MCEs of the Gulf of Eilat/Aqaba (0–100 m depth). Surveys were conducted by technical-diving and drop-cameras, in addition to one year of light spectral measurements. We quantify two distinct coral assemblages: shallow (<40 m) and MCEs (40–100 m), exhibiting markedly different relationships with light. The depth ranges and morphology of 47 coral genera were better explained by light than depth, mainly, due to photosynthetically active radiation (PAR) and ultraviolet radiation (UVR) (1% at 76 and 36 m, respectively). Branching coral species were found mainly at shallower depths, that is, down to 36 m. Among the abundant upper-mesophotic specialist corals, Leptoseris glabra, Euphyllia paradivisa, and Alveopora spp. were found strictly between 40 and 80 m depth. The only lower-mesophotic specialist, Leptoseris fragilis, was found deeper than 80 m. We suggest that shallow coral genera are light-limited below a level of 1.25% surface PAR and that the optimal PAR for mesophotic communities is at 7.5%. This study contributes to moving MCE ecology from a descriptive phase into identifying key ecological and physiological processes structuring MCE coral communities. Moreover, it may serve as a model enabling the description of a coral zonation worldwide on the basis of light quality data.

Spatial capture–recapture for categorically marked populations with an application to genetic capture–recapture

Abstract: Recently introduced unmarked spatial capture-recapture (SCR), spatial mark-resight (SMR), and 2-flank spatial partial identity models (SPIM) extend the domain of SCR to populations or observation systems that do not always allow for individual identity to be determined with certainty. For example, some species do not have natural marks that can reliably produce individual identities from photographs, and some methods of observation produce partial identity samples as is the case with remote cameras that sometimes produce single flank photographs. These models share the feature that they probabilistically resolve the uncertainty in individual identity using the spatial location where samples were collected. Spatial location is informative of individual identity in spatially structured populations with home range sizes smaller than the extent of the trapping array because a latent identity sample is more likely to have been produced by an individual living near the trap where it was recorded than an individual living further away from the trap. Further, the level of information about individual identity that a spatial location contains is determined by two key ecological concepts, population density and home range size. The number of individuals that could have produced a latent or partial identity sample increases as density and home range size increase because more individual home ranges will overlap any given trap. We show this uncertainty can be quantified using a metric describing the expected magnitude of uncertainty in individual identity for any given population density and home range size, the Identity Diversity Index (IDI). We then show that the performance of latent and partial identity SCR models varies as a function of this index and produces imprecise and biased estimates in many high IDI scenarios when data are sparse. We then extend the unmarked SCR model to incorporate partially identifying covariates which reduce the level of uncertainty in individual identity, increasing the reliability and precision of density estimates, and allowing reliable density estimation in scenarios with higher IDI values and with more sparse data. We illustrate the performance of this "categorical SPIM" via simulations and by applying it to a black bear data set using microsatellite loci as categorical covariates, where we reproduce the full data set estimates with only slightly less precision using fewer loci than necessary for confident individual identification. The categorical SPIM offers an alternative to using probability of identity criteria for classifying genotypes as unique, shifting the "shadow effect", where more than one individual in the population has the same genotype, from a source of bias to a source of uncertainty. We discuss the difficulties that real world data sets pose for latent identity SCR methods, most importantly, individual heterogeneity in detection function parameters, and argue that the addition of partial identity information reduces these concerns. We then discuss how the categorical SPIM can be applied to other wildlife sampling scenarios such as remote camera surveys, where natural or researcher-applied partial marks can be observed in photographs. Finally, we discuss how the categorical SPIM can be added to SMR, 2-flank SPIM, or other future latent identity.

Effects of street lighting technologies on the success and quality of pollination in a nocturnally pollinated plant

Abstract: Artificial light at night (ALAN) is an increasingly important driver of global change. Lighting directly affects plants, but few studies have investigated indirect effects mediated by interacting organisms. Nocturnal Lepidoptera are globally important pollinators, and pollen transport by moths is disrupted by lighting. Many street lighting systems are being replaced with novel, energy‐efficient lighting, with unknown ecological consequences. Using the wildflower Silene latifolia, we compared pollination success and quality at experimentally lit and unlit plots, testing two major changes to street lighting technology: in lamp type, from high‐pressure sodium lamps to light‐emitting diodes, and in lighting regime, from full‐night (FN) to part‐night (PN) lighting. We predicted that lighting would reduce pollination. S. latifolia was pollinated both diurnally and nocturnally. Contrary to our predictions, flowers under FN lighting had higher pollination success than flowers under either PN lighting or unlit controls, which did not significantly differ from each other. Lamp type, lighting regime, and distance from the light all significantly affected aspects of pollination quality. These results confirm that street lighting could affect plant reproduction through indirect effects mediated by nocturnal insects, and further highlight the possibility for novel lighting technologies to mitigate the effects of ALAN on ecosystems.

Greenhouse gas emissions from urban ponds are driven by nutrient status and hydrology

Abstract: Inland waters emit significant quantities of greenhouse gases (GHGs) such as methane (CH4) and carbon dioxide (CO2) to the atmosphere. On a global scale, these emissions are large enough that their contribution to climate change is now recognized by the Intergovernmental Panel on Climate Change. Much of the past focus on GHG emissions from inland waters has focused on lakes, reservoirs, and rivers, and the role of small, artificial waterbodies such as ponds has been overlooked. To investigate the spatial variation in GHG fluxes from artificial ponds, we conducted a synoptic survey of forty urban ponds in a Swedish city. We measured dissolved concentrations of CH4 and CO2, and made complementary measurements of water chemistry. We found that CH4 concentrations were greatest in high-nutrient ponds (measured as total phosphorus and total organic carbon). For CO2, higher concentrations were associated with silicon and calcium, suggesting that groundwater inputs lead to elevated CO2. When converted to diffusive GHG fluxes, mean emissions were 30.3 mg CH4.m-2 .d-1 and 752 mg CO2.m-2 .d-1 . Although these fluxes are moderately high on an areal basis, upscaling them to all Swedish urban ponds gives an emission of 8336 t CO2eq/yr (+/-1689) equivalent to 0.1% of Swedish agricultural GHG emissions. Artificial ponds could be important GHG sources in countries with larger proportions of urban land.

Wolverines in winter: Indirect habitat loss and functional responses to backcountry recreation

Abstract: Outdoor recreation is increasingly recognized to impact nature and wildlife, yet few studies have examined recreation within large natural landscapes that are critical habitat to some of our most rare and potentially disturbance-sensitive species. Over six winters (2010–2015) and four study areas (>1.1 million ha) in Idaho, Wyoming, and Montana, we studied the responses of wolverines (Gulo gulo) to backcountry winter recreation. We fit Global Positioning System (GPS) collars to 24 individual wolverines and acquired >54,000 GPS locations over 39 animal-years during winter (January–April). Simultaneously, we monitored winter recreation, collecting ~6000 GPS tracks (~200,000 km) from backcountry recreationists. We combined the GPS tracks with trail use counts and aerial recreation surveys to map the extent and relative intensity of motorized and non-motorized recreation. We integrated our wolverine and backcountry recreation data to (1) assess patterns of wolverine habitat selection and (2) evaluate the effect of backcountry recreation on wolverine habitat relationships. We used resource selection functions to model habitat selection of male and female wolverines within their home ranges. We first modeled habitat selection for environmental covariates to understand male and female habitat use then incorporated winter recreation covariates. We assessed the potential for indirect habitat loss from winter recreation and tested for functional responses of wolverines to differing levels and types of recreation. Motorized recreation occurred at higher intensity across a larger footprint than non-motorized recreation in most wolverine home ranges. Wolverines avoided areas of both motorized and non-motorized winter recreation with off-road recreation eliciting a stronger response than road-based recreation. Female wolverines exhibited stronger avoidance of off-road motorized recreation and experienced higher indirect habitat loss than male wolverines. Wolverines showed negative functional responses to the level of recreation exposure within the home range, with female wolverines showing the strongest functional response to motorized winter recreation. We suggest indirect habitat loss, particularly to females, could be of concern in areas with higher recreation levels. We speculate that the potential for backcountry winter recreation to affect wolverines may increase under climate change if reduced snow pack concentrates winter recreationists and wolverines in the remaining areas of persistent snow cover.

The plant diversity sampling design for The National Ecological Observatory Network

Abstract: National Science Foundation (NSF); NSF [EF-1029808, EF-1138160, DBI-0752017]; USDA CSREES/NRI [2008-35615-04666]; USGS Ecosystems and Climate and Land use Change Programs