A model integrating longshore and cross-shore processes for predicting long-term shoreline responses to climate change

We present a shoreline change model for coastal hazard assessment and management planning. The model, CoSMoS-COAST (Coastal One-line Assimilated Simulation Tool), is a transect-based, one-line model that predicts short-term and long-term shoreline response to climate change in the 21st century. The proposed model represents a novel, modular synthesis of process-based models of coastline evolution due to longshore and cross-shore transport by waves and sea level rise. Additionally, the model uses an extended Kalman filter for data assimilation of historical shoreline positions to improve estimates of model parameters and thereby improve confidence in long-term predictions. We apply CoSMoS-COAST to simulate sandy shoreline evolution along 500 km of coastline in Southern California, which hosts complex mixtures of beach settings variably backed by dunes, bluffs, cliffs, estuaries, river mouths, and urban infrastructure, providing applicability of the model to virtually any coastal setting. Aided by data assimilation, the model is able to reproduce the observed signal of seasonal shoreline change for the hindcast period of 1995–2010, showing excellent agreement between modeled and observed beach states. The skill of the model during the hindcast period improves confidence in the model’s predictive capability when applied to the forecast period (2010–2100) driven by GCM-projected wave and sea level conditions. Predictions of shoreline change with limited human intervention indicate that 31% to 67% of Southern California beaches may become completely eroded by 2100 under sea level rise scenarios of 0.93 to 2.0 m

Low interannual precipitation has a greater negative effect than seedling herbivory on the population dynamics of a short-lived shrub, Schiedea obovata

Climate projections forecast more extreme interannual climate variability over time, with an increase in the severity and duration of extreme drought and rainfall events. Based on bioclimatic envelope models, it is projected that changing precipitation patterns will drastically alter the spatial distributions and density of plants and be a primary driver of biodiversity loss. However, many other underlying mechanisms can impact plant vital rates (i.e., survival, growth, and reproduction) and population dynamics. In this study, we developed a size-dependent integral projection model (IPM) to evaluate how interannual precipitation and mollusk herbivory influence the dynamics of a Hawaii endemic short-lived shrub, Schiedea obovata (Caryophyllaceae). Assessing how wet season precipitation effects population dynamics it critical, as it is the timeframe when most of the foliar growth occurs, plants flower and fruit, and seedlings establish. Temporal variation in wet season precipitation had a greater effect than mollusk herbivory on S. obovata population growth rate , and the impact of interannual precipitation on vital rates shifted across plant ontogeny. Furthermore, wet season precipitation influenced multiple vital rates in contrasting ways and the effect of precipitation on the survival of larger vegetative and reproductively mature individuals contributed the most to variation in the population growth rate. Among all combination of wet season precipitation and herbivory intensities, the only scenario that led to a growing population was when high wet precipitation was associated with low herbivory. Our study highlights the importance of evaluating how abiotic factors and plant–consumer interactions influence an organism across its life cycle to fully understand the underpinning mechanisms that structure its spatial and temporal distribution and abundance. Our results also illustrate that for short-lived species, like S. obovata, seedling herbivory can have less of an effect on the dynamics of plant populations than decreased interannual precipitation

The soil and plant biogeochemistry sampling design for The National Ecological Observatory Network

Human impacts on biogeochemical cycles are evident around the world, from changes to forest structure and function due to atmospheric deposition, to eutrophication of surface waters from agricultural effluent, and increasing concentrations of carbon dioxide (CO2) in the atmosphere. The National Ecological Observatory Network (NEON) will contribute to understanding human effects on biogeochemical cycles from local to continental scales. The broad NEON biogeochemistry measurement design focuses on measuring atmospheric deposition of reactive mineral compounds and CO2 fluxes, ecosystem carbon (C) and nutrient stocks, and surface water chemistry across 20 eco‐climatic domains within the United States for 30 yr. Herein, we present the rationale and plan for the ground‐based measurements of C and nutrients in soils and plants based on overarching or “high‐level” requirements agreed upon by the National Science Foundation and NEON. The resulting design incorporates early recommendations by expert review teams, as well as recent input from the larger natural sciences community that went into the formation and interpretation of the requirements, respectively. NEON\u27s efforts will focus on a suite of data streams that will enable end‐users to study and predict changes to biogeochemical cycling and transfers within and across air, land, and water systems at regional to continental scales. At each NEON site, there will be an initial, one‐time effort to survey soil properties to 1 m (including soil texture, bulk density, pH, baseline chemistry) and vegetation community structure and diversity. A sampling program will follow, focused on capturing long‐term trends in soil C, nitrogen (N), and sulfur stocks, isotopic composition (of C and N), soil N transformation rates, phosphorus pools, and plant tissue chemistry and isotopic composition (of C and N). To this end, NEON will conduct extensive measurements of soils and plants within stratified random plots distributed across each site. The resulting data will be a new resource for members of the scientific community interested in addressing questions about long‐term changes in continental‐scale biogeochemical cycles, and is predicted to inspire further process‐based research

Rates of species introduction to a remote oceanic island

The introduction of species to areas beyond the limits of their natural distributions has a major homogenizing influence, making previously distinct biotas more similar. The scale of introductions has frequently been commented on, but their rate and spatial pervasiveness have been less well quantified. Here, we report the findings of a detailed study of pterygote insect introductions to Gough Island, one of the most remote and supposedly pristine temperate oceanic islands, and estimate the rate at which introduced species have successfully established. Out of 99 species recorded from Gough Island, 71 are established introductions, the highest proportion documented for any Southern Ocean island. Estimating a total of approximately 233 landings on Gough Island since first human landfall, this equates to one successful establishment for every three to four landings. Generalizations drawn from other areas suggest that this may be only one-tenth of the number of pterygote species that have arrived at the island, implying that most landings may lead to the arrival of at least one alien. These rates of introduction of new species are estimated to be two to three orders of magnitude greater than background levels for Gough Island, an increase comparable to that estimated for global species extinctions (many of which occur on islands) as a consequence of human activities

Terrestrial ecosystem production: A process model based on global satellite and surface data

This paper presents a modeling approach aimed at seasonal resolution of global climatic and edaphic controls on patterns of terrestrial ecosystem production and soil microbial respiration. We use satellite imagery (Advanced Very High Resolution Radiometer and International Satellite Cloud Climatology Project solar radiation), along with historical climate (monthly temperature and precipitation) and soil attributes (texture, C and N contents) from global (1°) data sets as model inputs. The Carnegie‐Ames‐Stanford approach (CASA) Biosphere model runs on a monthly time interval to simulate seasonal patterns in net plant carbon fixation, biomass and nutrient allocation, litterfall, soil nitrogen mineralization, and microbial CO2 production. The model estimate of global terrestrial net primary production is 48 Pg C yr^(−1) with a maximum light use efficiency of 0.39 g C MJ^(−1) PAR. Over 70% of terrestrial net production takes place between 30°N and 30°S latitude. Steady state pools of standing litter represent global storage of around 174 Pg C (94 and 80 Pg C in nonwoody and woody pools, respectively), whereas the pool of soil C in the top 0.3 m that is turning over on decadal time scales comprises 300 Pg C. Seasonal variations in atmospheric CO_2 concentrations from three stations in the Geophysical Monitoring for Climate Change Flask Sampling Network correlate significantly with estimated net ecosystem production values averaged over 50°–80° N, 10°–30° N, and 0°–10° N

The environmental impact of climate change adaptation on land use and water quality

Encouraging adaptation is an essential aspect of the policy response to climate change1. Adaptation seeks to reduce the harmful consequences and harness any beneficial opportunities arising from the changing climate. However, given that human activities are the main cause of environmental transformations worldwide2, it follows that adaptation itself also has the potential to generate further pressures, creating new threats for both local and global ecosystems. From this perspective, policies designed to encourage adaptation may conflict with regulation aimed at preserving or enhancing environmental quality. This aspect of adaptation has received relatively little consideration in either policy design or academic debate. To highlight this issue, we analyse the trade-offs between two fundamental ecosystem services that will be impacted by climate change: provisioning services derived from agriculture and regulating services in the form of freshwater quality. Results indicate that climate adaptation in the farming sector will generate fundamental changes in river water quality. In some areas, policies that encourage adaptation are expected to be in conflict with existing regulations aimed at improving freshwater ecosystems. These findings illustrate the importance of anticipating the wider impacts of human adaptation to climate change when designing environmental policies

Nitrogen addition and ecosystem functioning: Both species abundances and traits alter community structure and function

Increased nutrient inputs can cause shifts in plant community composition and plant functional traits, both of which affect ecosystem function. We studied community- and species-level leaf functional trait changes in a full factorial nitrogen (N), phosphorus (P), and potassium (K) fertilization experiment in a semi-arid grassland. Nitrogen was the only nutrient addition to significantly affect leaf functional traits, and N addition increased community-weighted specific leaf area (SLA) by 19%, leaf chlorophyll content by 34%, height by 26%, and leaf dry matter content (LDMC) decreased by 11% while leaf thickness and toughness did not change significantly. At the species level, most species contributed to the community-weighted trait and increased in SLA, chlorophyll, height, and LDMC with N addition. These intraspecific changes in functional traits account for 51–71% of the community-level changes in SLA, chlorophyll, plant height, and LDMC. The remaining change is due to species abundance changes; the two most abundant species (Bouteloua gracilis and Carex filifolia) decreased in abundance with N addition while subdominant species increased in abundance. We also found annual variation in SLA, chlorophyll, plant height, and LDMC to be as important in influencing traits as N addition, likely due to differences in precipitation. Aboveground net primary productivity (ANPP) did not change significantly with N addition. However, N addition caused a 34% increase in leaf area index (LAI) and a 67% increase in canopy chlorophyll density. We demonstrate that nitrogen-induced changes in both functional traits and species abundances magnify ANPP changes in LAI and canopy chlorophyll density. Therefore, ANPP underestimates N addition-induced ecosystem-level changes in the canopy vegetation

Invasion speeds for structured populations in fluctuating environments

We live in a time where climate models predict future increases in environmental variability and biological invasions are becoming increasingly frequent. A key to developing effective responses to biological invasions in increasingly variable environments will be estimates of their rates of spatial spread and the associated uncertainty of these estimates. Using stochastic, stage-structured, integro-difference equation models, we show analytically that invasion speeds are asymptotically normally distributed with a variance that decreases in time. We apply our methods to a simple juvenile-adult model with stochastic variation in reproduction and an illustrative example with published data for the perennial herb, \emph{Calathea ovandensis}. These examples buttressed by additional analysis reveal that increased variability in vital rates simultaneously slow down invasions yet generate greater uncertainty about rates of spatial spread. Moreover, while temporal autocorrelations in vital rates inflate variability in invasion speeds, the effect of these autocorrelations on the average invasion speed can be positive or negative depending on life history traits and how well vital rates ``remember'' the past

Global-scale changes to extreme ocean wave events due to anthropogenic warming

Extreme surface ocean waves are often primary drivers of coastal flooding and erosion over various time scales. Hence, understanding future changes in extreme wave events owing to global warming is of socio-economic and environmental significance. However, our current knowledge of potential changes in high-frequency (defined here as having return periods of less than 1 year) extreme wave events are largely unknown, despite being strongly linked to coastal hazards across time scales relevant to coastal management. Here, we present global climate-modeling evidence, based on the most comprehensive multi-method, multi-model wave ensemble, of projected changes in a core set of extreme wave indices describing high-frequency, extra-tropical storm-driven waves. We find changes in high-frequency extreme wave events of up to ∼50%-100% under RCP8.5 high-emission scenario; which is nearly double the expected changes for RCP4.5 scenario, when globally integrated. The projected changes exhibit strong inter-hemispheric asymmetry, with strong increases in extreme wave activity across the tropics and high latitudes of the Southern Hemisphere region, and a widespread decrease across most of the Northern Hemisphere. We find that the patterns of projected increase across these extreme wave events over the Southern Hemisphere region resemble their historical response to the positive anomaly of the Southern Annular Mode. Our findings highlight that many countries with low-adaptive capacity are likely to face increasing exposure to much more frequent extreme wave events in the future

Compared to conventional, ecological intensive management promotes beneficial proteolytic soil microbial communities for agro-ecosystem functioning under climate change-induced rain regimes

Projected climate change and rainfall variability will affect soil microbial communities, biogeochemical cycling and agriculture. Nitrogen (N) is the most limiting nutrient in agroecosystems and its cycling and availability is highly dependent on microbial driven processes. In agroecosystems, hydrolysis of organic nitrogen (N) is an important step in controlling soil N availability. We analyzed the effect of management (ecological intensive vs. conventional intensive) on N-cycling processes and involved microbial communities under climate change-induced rain regimes. Terrestrial model ecosystems originating from agroecosystems across Europe were subjected to four different rain regimes for 263 days. Using structural equation modelling we identified direct impacts of rain regimes on N-cycling processes, whereas N-related microbial communities were more resistant. In addition to rain regimes, management indirectly affected N-cycling processes via modifications of N-related microbial community composition. Ecological intensive management promoted a beneficial N-related microbial community composition involved in N-cycling processes under climate change-induced rain regimes. Exploratory analyses identified phosphorus-associated litter properties as possible drivers for the observed management effects on N-related microbial community composition. This work provides novel insights into mechanisms controlling agro-ecosystem functioning under climate change