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Fluctuating water depths affect American alligator ( Alligator mississippiensis ) body condition in the Everglades, Florida, USA

Successful restoration of wetland ecosystems requires knowledge of wetland hydrologic patterns and an understanding of how those patterns affect wetland plant and animal populations.Within the Everglades, Florida, USA restoration, an applied science strategy including conceptual ecological models linking drivers to indicators is being used to organize current scientific understanding to support restoration efforts. A key driver of the ecosystem affecting the distribution and abundance of organisms is the timing, distribution, and volume of water flows that result in water depth patterns across the landscape. American alligators (Alligator mississippiensis) are one of the ecological indicators being used to assess Everglades restoration because they are a keystone species and integrate biological impacts of hydrological operations through all life stages. Alligator body condition (the relative fatness of an animal) is one of the metrics being used and targets have been set to allow us to track progress. We examined trends in alligator body condition using Fulton’s K over a 15 year period (2000–2014) at seven different wetland areas within the Everglades ecosystem, assessed patterns and trends relative to restoration targets, and related those trends to hydrologic variables. We developed a series of 17 a priori hypotheses that we tested with an information theoretic approach to identify which hydrologic factors affect alligator body condition. Alligator body condition was highest throughout the Everglades during the early 2000s and is approximately 5–10% lower now (2014). Values have varied by year, area, and hydrology. Body condition was positively correlated with range in water depth and fall water depth. Our top model was the “Current” model and included variables that describe current year hydrology (spring depth, fall depth, hydroperiod, range, interaction of range and fall depth, interaction of range and hydroperiod). Across all models, interaction between range and fall water depth was the most important variable (relative weight of 1.0) followed by spring and fall water depths (0.99), range (0.96), hydroperiod (0.95) and interaction between range and hydroperiod (0.95). Our work provides additional evidence that restoring a greater range in annual water depths is important for improvement of alligator body condition and ecosystem function. This information can be incorporated into both planning and operations to assist in reaching Everglades restoration goals.

Florida↗

Mapping and monitoring Mount Graham red squirrel habitat with Lidar and Landsat imagery

The Mount Graham red squirrel ( Tamiasciurus hudsonicus grahamensis ) is an endemic subspecies located in the Pinaleño Mountains of southeast Arizona. Living in a conifer forest on a sky-island surrounded by desert, the Mount Graham red squirrel is one of the rarest mammals in North America. Over the last two decades, drought, insect infestations, and fire destroyed much of its habitat. A federal recovery team is working on a plan to recover the squirrel and detailed information is necessary on its habitat requirements and population dynamics. Toward that goal I developed and compared three probabilistic models of Mount Graham red squirrel habitat with a geographic information system and logistic regression. Each model contained the same topographic variables (slope, aspect, elevation), but the Landsat model contained a greenness variable (Normalized Difference Vegetation Index) extracted from Landsat, the Lidar model contained three forest-inventory variables extracted from lidar, while the Hybrid model contained Landsat and lidar variables. The Hybrid model produced the best habitat classification accuracy, followed by the Landsat and Lidar models, respectively. Landsat-derived forest greenness was the best predictor of habitat, followed by topographic (elevation, slope, aspect) and lidar (tree height, canopy bulk density, and live basal area) variables, respectively. The Landsat model's probabilities were significantly correlated with all 12 lidar variables, indicating its utility for habitat mapping. While the Hybrid model produced the best classification results, only the Landsat model was suitable for creating a habitat time series or habitat–population function between 1986 and 2013. The techniques I highlight should prove valuable in the development of Landsat- or lidar-based habitat models range wide.

Arizona↗

NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms

The 2017–2027 National Academies' Decadal Survey, Thriving on Our Changing Planet , recommended Surface Biology and Geology (SBG) as a “Designated Targeted Observable” (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380–2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3–5 μm; TIR: 8–12 μm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algorithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. This effort synthesizes the findings of more than 130 scientists.

Remote Sensing of Environment↗

An empirical model for estimating phytoplankton productivity in estuaries

e have previously shown that primary productivity in San Francisco Bay, USA, is highly correlated with phytoplankton biomass B (chlorophyll a concentration) and an index of light avallability in the photic zone, 2, I, (photic depth times surface irradiance). To test the generality of this relation, we compiled data from San Francisco Bay and 5 other USA estuarine systems (Neuse and South Rivers, Puget Sound, Delaware Bay and Hudson River Plume), and regressed daily produclvity J' P (mg C m-2 d-') against the composite parameter B Z, I,. Regressions for each estuary were significant and typically over 80 % of the varialon in P was correlated with variations in B Z,I,. Moreover, the pooled data (n = 211) from 4 estuaries where methodologies were comparable fell along one regression line (r2= 0.82), indicating that primary productivity can be estimated in a diversity of estuarine waters from simple measures of phytoplankton biomass and hght availability. This implies that physiological variabhty (e. g. responses to variations in nutrient availabhty, temperature, sahnity, photoperiod) is a secondary control on phytoplankton production in nutrient-rich estuaries, and that one empirical function can be used to estimate seasonal variations in productivity or to map productivity along estuarine gradients of phytoplankton biomass and turbidity.

Marine Ecology Progress Series↗

Performance of four turbulence closure models implemented using a generic length scale method

A two-equation turbulence model (one equation for turbulence kinetic energy and a second for a generic turbulence length-scale quantity) proposed by Umlauf and Burchard [J. Marine Research 61 (2003) 235] is implemented in a three-dimensional oceanographic model (Regional Oceanographic Modeling System; ROMS v2.0). These two equations, along with several stability functions, can represent many popular turbulence closures, including the k-kl (Mellor-Yamada Level 2.5), k-??, and k-?? schemes. The implementation adds flexibility to the model by providing an unprecedented range of turbulence closure selections in a single 3D oceanographic model and allows comparison and evaluation of turbulence models in an otherwise identical numerical environment. This also allows evaluation of the effect of turbulence models on other processes such as suspended-sediment distribution or ecological processes. Performance of the turbulence models and sediment-transport schemes is investigated with three test cases for (1) steady barotropic flow in a rectangular channel, (2) wind-induced surface mixed-layer deepening in a stratified fluid, and (3) oscillatory stratified pressure-gradient driven flow (estuarine circulation) in a rectangular channel. Results from k-??, k-??, and gen (a new closure proposed by Umlauf and Burchard [J. Marine Research 61 (2003) 235]) are very similar for these cases, but the k-kl closure results depend on a wall-proximity function that must be chosen to suit the flow. Greater variations appear in simulations of suspended-sediment concentrations than in salinity simulations because the transport of suspended-sediment amplifies minor variations in the methods. The amplification is caused by the added physics of a vertical settling rate, bottom stress dependent resuspension, and diffusive transport of sediment in regions of well mixed salt and temperature. Despite the amplified sensitivity of sediment to turbulence models in the estuary test case, the four closures investigated here all generated estuarine turbidity maxima that were similar in their shape, location, and concentrations.

Ocean Modelling↗

Beyond reducing fire hazard: fuel treatment impacts on overstory tree survival

Fuel treatment implementation in dry forest types throughout the western United States is likely to increase in pace and scale in response to increasing incidence of large wildfires. While it is clear that properly implemented fuel treatments are effective at reducing hazardous fire potential, there are ancillary ecological effects that can impact forest resilience either positively or negatively depending on the specific elements examined, as well as treatment type, timing, and intensity. In this study, we use overstory tree growth responses, measured seven years after the most common fuel treatments, to estimate forest health. Across the five species analyzed, observed mortality and future vulnerability were consistently low in the mechanical-only treatment. Fire-only was similar to the control for all species except Douglas-fir, while mechanical-plus-fire had high observed mortality and future vulnerability for white fir and sugar pine. Given that overstory trees largely dictate the function of forests and services they provide (e.g., wildlife habitat, carbon sequestration, soil stability) these results have implications for understanding longer-term impacts of common fuel treatments on forest resilience.

Ecological Applications↗

Biological soil crusts in ecological restoration: Emerging research and perspectives

Drylands encompass over 40% of terrestrial ecosystems and face significant anthropogenic degradation causing a loss of ecosystem integrity, services, and deterioration of social‐ecological systems. To combat this degradation, some dryland restoration efforts have focused on the use of biological soil crusts (biocrusts): complex communities of cyanobacteria, algae, lichens, bryophytes, and other organisms living in association with the top millimeters of soil. Biocrusts are common in many ecosystems and especially drylands. They perform a suite of ecosystem functions: stabilizing soil surfaces to prevent erosion, contributing carbon through photosynthesis, fixing nitrogen, and mediating the hydrological cycle in drylands. Biocrusts have emerged as a potential tool in restoration; developing methods to implement effective biocrust restoration has the potential to return many ecosystem functions and services. Although culture‐based approaches have allowed researchers to learn about the biology, physiology, and cultivation of biocrusts, transferring this knowledge to field implementation has been more challenging. A large amount of research has amassed to improve our understanding of biocrust restoration, leaving us at an opportune time to learn from one another and to join approaches for maximum efficacy. The articles in this special issue improve the state of our current knowledge in biocrust restoration, highlighting efforts to effectively restore biocrusts through a variety of different ecosystems, across scales and utilizing a variety of lab and field methods. This collective work provides a useful resource for the scientific community as well as land managers.

Restoration Ecology↗

Changes in habitat availability for outmigrating juvenile salmon (Oncorhychus spp.) following estuary restoration

The restoration of the Nisqually River Delta (Washington, U.S.A.) represents one of the largest efforts toward reestablishing the ecosystem function and resilience of modified habitat in the Puget Sound, particularly for anadromous salmonid species. The opportunity for outmigrating salmon to access and benefit from the expansion of available tidal habitat can be quantified by several physical attributes, which are related to the ecological and physiological responses of juvenile salmon. We monitored a variety of physical parameters to measure changes in opportunity potential from historic, pre-restoration, and post-restoration habitat conditions at several sites across the delta. These parameters included channel morphology, water quality, tidal elevation, and landscape connectivity. We conducted fish catch surveys across the delta to determine if salmon was utilizing restored estuary habitat. Overall major channel area increased 42% and major channel length increased 131% from pre- to post-restoration conditions. Furthermore, the results of our tidal inundation model indicated that major channels were accessible up to 75% of the time, as opposed to 30% pre-restoration. Outmigrating salmon utilized this newly accessible habitat as quickly as 1 year post-restoration. The presence of salmon in restored tidal channels confirmed rapid post-restoration increases in opportunity potential on the delta despite habitat quality differences between restored and reference sites.

Washington↗

Effects of nitrogen deposition and empirical nitrogen critical loads for ecoregions of the United States

Human activity in the last century has led to a significant increase in nitrogen (N) emissions and atmospheric deposition. This N deposition has reached a level that has caused or is likely to cause alterations to the structure and function of many ecosystems across the United States. One approach for quantifying the deposition of pollution that would be harmful to ecosystems is the determination of critical loads. A critical load is defined as the input of a pollutant below which no detrimental ecological effects occur over the long-term according to present knowledge. The objectives of this project were to synthesize current research relating atmospheric N deposition to effects on terrestrial and freshwater ecosystems in the United States, and to estimate associated empirical N critical loads. The receptors considered included freshwater diatoms, mycorrhizal fungi, lichens, bryophytes, herbaceous plants, shrubs, and trees. Ecosystem impacts included: (1) biogeochemical responses and (2) individual species, population, and community responses. Biogeochemical responses included increased N mineralization and nitrification (and N availability for plant and microbial uptake), increased gaseous N losses (ammonia volatilization, nitric and nitrous oxide from nitrification and denitrification), and increased N leaching. Individual species, population, and community responses included increased tissue N, physiological and nutrient imbalances, increased growth, altered root : shoot ratios, increased susceptibility to secondary stresses, altered fire regime, shifts in competitive interactions and community composition, changes in species richness and other measures of biodiversity, and increases in invasive species. The range of critical loads for nutrient N reported for U.S. ecoregions, inland surface waters, and freshwater wetlands is 1-39 kg N.ha -1.yr -1, spanning the range of N deposition observed over most of the country. The empirical critical loads for N tend to increase in the following sequence for different life forms: diatoms, lichens and bryophytes, mycorrhizal fungi, herbaceous plants and shrubs, and trees. The critical load approach is an ecosystem assessment tool with great potential to simplify complex scientific information and communicate effectively with the policy community and the public. This synthesis represents the first comprehensive assessment of empirical critical loads of N for major ecoregions across the United States. ?? 2011 by the Ecological Society of America.

Ecological Applications↗

Testing the hierarchy of predictability in grassland restoration across a gradient of environmental severity

Ecological restoration is critical for recovering degraded ecosystems but is challenged by variable success and low predictability. Understanding which outcomes are more predictable and less variable following restoration can improve restoration effectiveness. Recent theory asserts that the predictability of outcomes would follow an order from most to least predictable from coarse to fine community properties (physical structure > taxonomic diversity > functional composition > taxonomic composition) and that predictability would increase with more severe environmental conditions constraining species establishment. We tested this “hierarchy of predictability” hypothesis by synthesizing outcomes along an aridity gradient with 11 grassland restoration projects across the United States. We used 1829 vegetation monitoring plots from 227 restoration treatments, spread across 52 sites. We fit generalized linear mixed-effects models to predict six indicators of restoration outcomes as a function of restoration characteristics (i.e., seed mixes, disturbance, management actions, time since restoration) and used variance explained by models and model residuals as proxies for restoration predictability. We did not find consistent support for our hypotheses. Physical structure was among the most predictable outcomes when the response variable was relative abundance of grasses, but unpredictable for total canopy cover. Similarly, one dimension of taxonomic composition related to species identities was unpredictable, but another dimension of taxonomic composition indicating whether exotic or native species dominated the community was highly predictable. Taxonomic diversity (i.e., species richness) and functional composition (i.e., mean trait values) were intermittently predictable. Predictability also did not increase consistently with aridity. The dimension of taxonomic composition related to the identity of species in restored communities was more predictable (i.e., smaller residuals) in more arid sites, but functional composition was less predictable (i.e., larger residuals), and other outcomes showed no significant trend. Restoration outcomes were most predictable when they related to variation in dominant species, while those responding to rare species were harder to predict, indicating a potential role of scale in restoration predictability. Overall, our results highlight additional factors that might influence restoration predictability and add support to the importance of continuous monitoring and active management beyond one-time seed addition for successful grassland restoration in the United States.

Continental United States↗

Hidden legacies: Investigating buried pre-colonial stream corridors in the Mid-Atlantic Coastal Plain, Maryland, USA

Within the Mid-Atlantic United States, widespread landscape disturbance during European colonization resulted in erosion and subsequent storage of legacy sediments within river valleys and floodplains, altering their form, function, and flora. Previous studies of precolonial river corridors have influenced river restoration designs and targets throughout the region, but the generalizability of these studies into other physiographic settings, such as the Coastal Plain, is unknown. Therefore, our study investigated the physical form and riparian vegetation of pre-colonial stream corridors located within the Coastal Plain of Anne Arundel County, Maryland, documenting changes from pre- to colonial and postcolonial time periods. Our study provides evidence of buried, precolonial riparian ecosystems with dates ranging between 750 years to 8000 years Before Present. These valley bottom ecosystems were likely a dynamic patch mosaic, largely dominated by dense Alnus (alder) scrub swamps with variable Poaceae (grass) and Cyperaceae (sedge) dominated meadows and both multi-threaded and single-threaded channel forms. These precolonial floodplains are buried by vast amounts of legacy sediment to the extent that pre-colonial sediments are largely not exposed in the modern valley bottom. Notably, the Coastal Plain precolonial corridors investigated in this study contrast to studies in the Piedmont physiographic region with precolonial sediments exposed in streambanks and with precolonial ecosystems described as herbaceous stream-wetlands. Our findings provide critical historical context as to the magnitude of alteration for modern stream channels and suggest an alternative precolonial ecosystem which can be used to inform restoration designs, management targets, and reestablishment of channel functional processes in areas of the Mid-Atlantic Coastal Plain.

Maryland↗

Fish mortality and physicochemistry in a managed floodplain wetland

Patterns of fish mortality and associated physicochemical factors were studied during late spring in a managed wetland canal along the lower Missouri River, Missouri. Mean dawn dissolved oxygen was lower and mean un-ionized ammonia and turbidity were higher during the fish kill than before or after the kill, or than was observed in a nearby wetland canal where no fish kill occurred. Dissolved oxygen at dawn and un-ionized ammonia concentrations were at critically low and high levels respectively, so that both likely contributed to the fish mortality. Timing and magnitude of observed carcasses suggested that Ameiurus melas Rafinesques was the most tolerant species for the sizes observed compared to Ictiobuscyprinellus Valenciennes, Lepomis macrochirus Rafinesque, Cyprinus carpio Linneaus, and Lepomis cyanellus Rafinesque. Decreasing mean lengths of fish carcasses during the fish kill for C.carpio, L. cyanellus , and A. melas , indicate that smaller fishes may have been more tolerant of harsh environmental conditions than larger individuals of the same species. Differential mortalities among species and sizes during drawdowns in actively managed wetland pools may have intentional and unintentional ramifications on wetland and riverine fish community structure, fish-avian interactions, and implementing an ecosystem management perspective to restoring more naturalized river floodplain wetland functions. Late summer and early autumn draining of managed wetlands might be used to benefit a wider diversity of wildlife and fishes.

Wetlands Ecology and Management↗

Restoring dryland water cycles for precipitation feedback and climate stability; a review

Drylands across the globe are experiencing intensifying water scarcity, land degradation, and hydroclimatic extremes. This review integrates evidence from multidecadal field studies, hydrologic monitoring, geomorphic and ecological assessments, remote sensing, and land–atmosphere science to evaluate how restoration influences key components of the terrestrial water cycle. Low-tech natural infrastructure in dryland streams (NIDS)—including check dams, leaky weirs, one-rock dams, and gabions—has emerged as a promising but under-synthesized nature-based solution for restoring hydrologic function in these environments. We describe the mechanisms through which these interventions modify runoff detention, infiltration, sediment and alluvial storage, shallow-groundwater recharge, vegetation recovery, and surface-energy partitioning, and we summarize outcomes across diverse dryland settings. Findings consistently show increased water residence time, enhanced soil-moisture storage, expanded riparian vegetation, extended flow duration, and shifts toward greater latent-heat flux—producing localized cooling and strengthened ecohydrological feedbacks. Building on these localized effects, we articulate a hypothesis that links the spatial extent of restoration, the density of NIDS per unit drainage area, and the magnitude of the latent-to-sensible-heat contrast generated by wetter post-rainfall conditions. Specifically, we hypothesize that when NIDS are implemented at densities permitted by topography and across areas large enough to maintain elevated soil moisture after storm events, the resulting increases in latent heat flux, surface cooling, and boundary-layer moistening may enhance moisture convergence and boundary-layer development, potentially increasing the likelihood or stability of convective precipitation, analogous to how reductions in these processes have contributed to regional drought intensification. These land–atmosphere feedbacks remain untested at scale but represent an important research Frontier. By integrating hydrologic, geomorphic, ecological, and atmospheric perspectives, this review provides a comprehensive framework for considering how low-tech, landscape-scale interventions can strengthen watershed resilience and contribute to climate-relevant nature-based solutions.

Arizona↗

Different data for different goals: Exploring trade-offs and synergies in the use of spatial data inputs to optimize conservation action in sagebrush ecosystems

Ecosystems worldwide continue to experience rapid rates of habitat and species loss. Management actions to conserve and restore functional habitats are needed to reduce these declines, but funding and resources for such actions are limited. Spatial conservation prioritization (SCP) can facilitate strategic decision-making for targeted conservation planning and delivery, but complexities arise when management objectives include multiple wildlife species and ecological or management constraints, all of which can be further complicated by data uncertainty and existing conservation plans. The Prioritizing Restoration of Sagebrush Ecosystems Tool (PReSET), an R package-based decision-support tool, supports strategic ecosystem management planning across the sagebrush biome by using SCP. We adapted PReSET to better address the needs of multiple wildlife species, evaluate the effects of different ecological or management constraints on conservation outcomes, assess the influence of data uncertainty, and integrate existing conservation plans. Specifically, we developed optimization problems to identify priority sagebrush protection and restoration across the state of Wyoming, USA, and evaluated the efficacy and trade-offs of various approaches to problem design. We evaluated trade-offs in targeting multiple species compared to a single species, including using greater sage-grouse as a potential umbrella species to benefit other sagebrush-dependent wildlife. We then evaluated multi-species protection and restoration problems aimed at minimizing the risks of inadequate connectivity, climate change, and restoration failure, and accounted for data uncertainty to assess relationships between risk aversion of managers and conservation outcomes. We also developed optimization problems within conservation areas identified by an existing sagebrush conservation plan to evaluate the efficacy of guiding local-scale conservation delivery within more broadly defined conservation areas. Our results demonstrate how SCP methods can leverage novel spatial data to develop targeted decision-support resources that can facilitate landscape conservation planning and improve management outcomes across a wide array of systems and species.

Wyoming↗

Seasonal movements and habitat use of Potamodromous Rainbow Trout across a complex Alaska riverscape

Potamodromous Rainbow Trout Oncorhynchus mykiss are an important ecological and recreational resource in freshwater ecosystems of Alaska, and increased human development, hydroelectric projects, and reduced escapement of Chinook Salmon Oncorhynchus tshawytscha may threaten their populations. We used aerial and on-the-ground telemetry tracking, a digital landscape model, and resource selection functions to characterize seasonal movements and habitat use of 232 adult (>400 mm FL) Rainbow Trout across the complex, large (31,221 km 2 ) Susitna River basin of south-central Alaska during 2003–2004 and 2013–2014. We found that fish overwintered in main-stem habitats near tributary mouths from November to April. After ice-out in May, fish ascended tributaries up to 51 km to spawn and afterward moved downstream to lower tributary reaches, assumedly to intercept egg and flesh subsidies provided by spawning salmonids in July and August. Fish transitioned back to main-stem overwintering habitats at the onset of autumn when salmonid spawning waned. Fidelity to tributaries where fish were initially tagged varied across seasons but was high (>0.75) in three out of four drainages. Model-averaged resource selection functions suggested that Rainbow Trout habitat use varied seasonally; fish selected low-gradient, sinuous, main-stem stream reaches in the winter, reaches with suitably sized substrate during spawning, larger reaches during the feeding season prior to the arrival of spawning salmonids, and reaches with high Chinook Salmon spawning habitat potential following the arrival of adult fish. We found little difference in movement patterns between males and females among a subset of fish for which sex was determined using genetic analysis. As most Rainbow Trout undertake extensive movements within and among tributaries and make use of a variety of seasonal habitats to complete their life histories, it will be critical to take a basinwide approach to their management (i.e., habitat protection and angling bag limits) in light of anticipated land-use changes.

Alaska↗

Carrying capacity of a population diffusing in a heterogeneous environment

The carrying capacity of the environment for a population is one of the key concepts in ecology and it is incorporated in the growth term of reaction-diffusion equations describing populations in space. Analysis of reaction-diffusion models of populations in heterogeneous space have shown that, when the maximum growth rate and carrying capacity in a logistic growth function vary in space, conditions exist for which the total population size at equilibrium (i) exceeds the total population that which would occur in the absence of diffusion and (ii) exceeds that which would occur if the system were homogeneous and the total carrying capacity, computed as the integral over the local carrying capacities, was the same in the heterogeneous and homogeneous cases. We review here work over the past few years that has explained these apparently counter-intuitive results in terms of the way input of energy or another limiting resource (e.g., a nutrient) varies across the system. We report on both mathematical analysis and laboratory experiments confirming that total population size in a heterogeneous system with diffusion can exceed that in the system without diffusion. We further report, however, that when the resource of the population in question is explicitly modeled as a coupled variable, as in a reaction-diffusion chemostat model rather than a model with logistic growth, the total population in the heterogeneous system with diffusion cannot exceed the total population size in the corresponding homogeneous system in which the total carrying capacities are the same.

Mathematics and Computers in Modern Science - Acou↗

Impacts of climate change on biodiversity, ecosystems, and ecosystem services: technical input to the 2013 National Climate Assessment

Ecosystems, and the biodiversity and services they support, are intrinsically dependent on climate. During the twentieth century, climate change has had documented impacts on ecological systems, and impacts are expected to increase as climate change continues and perhaps even accelerates. This technical input to the National Climate Assessment synthesizes our scientific understanding of the way climate change is affecting biodiversity, ecosystems, ecosystem services, and what strategies might be employed to decrease current and future risks. Building on past assessments of how climate change and other stressors are affecting ecosystems in the United States and around the world, we approach the subject from several different perspectives. First, we review the observed and projected impacts on biodiversity, with a focus on genes, species, and assemblages of species. Next, we examine how climate change is affecting ecosystem structural elements—such as biomass, architecture, and heterogeneity—and functions—specifically, as related to the fluxes of energy and matter. People experience climate change impacts on biodiversity and ecosystems as changes in ecosystem services; people depend on ecosystems for resources that are harvested, their role in regulating the movement of materials and disturbances, and their recreational, cultural, and aesthetic value. Thus, we review newly emerging research to determine how human activities and a changing climate are likely to alter the delivery of these ecosystem services. This technical input also examines two cross-cutting topics. First, we recognize that climate change is happening against the backdrop of a wide range of other environmental and anthropogenic stressors, many of which have caused dramatic ecosystem degradation already. This broader range of stressors interacts with climate change, and complicates our abilities to predict and manage the impacts on biodiversity, ecosystems, and the services they support. The second cross-cutting topic is the rapidly advancing field of climate adaptation, where there has been significant progress in developing the conceptual framework, planning approaches, and strategies for safeguarding biodiversity and other ecological resources. At the same time, ecosystem-based adaptation is becoming more prominent as a way to utilize ecosystem services to help human systems adapt to climate change. In this summary, we present key findings of the technical input, focusing on themes that can be found throughout the report. Thus, this summary takes a more integrated look at the question of how climate change is affecting our ecological resources, the implications for humans, and possible response strategies. This integrated approach better reflects the impacts of climate in the real world, where changes in ecosystem structure or function will alter the viability of different species and the efficacy of ecosystem services. Likewise, adaptation to climate change will simultaneously address a range of conservation goals. Case studies are used to illustrate this complete picture throughout the report; a snapshot of one case study, 2011 Las Conchas, New Mexico Fire , is included in this summary.

Report↗

Estimating abiotic thresholds for sagebrush condition class in the western United States

Sagebrush ecosystems of the western United States can transition from extended periods of relatively stable conditions to rapid ecological change if acute disturbances occur. Areas dominated by native sagebrush can transition from species-rich native systems to altered states where non-native annual grasses dominate, if resistance to annual grasses is low. The non-native annual grasses provide relatively little value to wildlife, livestock, and humans and function as fuel that increases fire frequency. The more land area covered by annual grasses, the higher the potential for fire, thus reducing the potential for native vegetation to reestablish, even when applying restoration treatments. Mapping areas of stability and areas of change using machine-learning algorithms allows both the identification of dominant abiotic variables that drive ecosystem dynamics and the variables’ important thresholds. We develop a decision-tree model with rulesets that estimate three classes of sagebrush condition (i.e., sagebrush recovery, tipping point [ecosystem degradation], and stable). We find rulesets that primarily drive development of the sagebrush recovery class indicate areas of midelevations (1 602 m), warm 30-yr July temperature maximums (tmax) (30.62°C), and 30-yr March precipitation (ppt) averages equal to 26.26 mm, about 10% of the 30-yr annual ppt values. Tipping point and stable classes occur at elevations that are lower (1 505 m) and higher (1 939 m), respectively, more mesic during March and annually, and experience lower 30-yr July tmax averages. These defined variable averages can be used to understand current dynamics of sagebrush condition and to predict where future transitions may occur under novel conditions.

Arizona, California, Colorado, Idaho, Montana, Neb↗