Does scale matter? A systematic review of incorporating biological realism when predicting changes in species distributions

Background There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species’ responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Objectives Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. Data sources and study eligibility criteria We systematically reviewed SDM studies published from 2003–2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. Synthesis methods and limitations We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. Results There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. Conclusions We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis

Does scale matter? A systematic review of incorporating biological realism when predicting changes in species distributions

Background There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species’ responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Objectives Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. Data sources and study eligibility criteria We systematically reviewed SDM studies published from 2003–2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. Synthesis methods and limitations We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. Results There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. Conclusions We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis

Vegetation effects on coastal foredune initiation: Wind tunnel experiments and field validation for three dune-building plants

As the land-sea interface, foredunes buffer upland habitats with plants acting as ecosystem engineers shaping topography, and thereby affecting storm response and recovery. However, many ecogeomorphic feedbacks in coastal foredune formation and recovery remain uncertain in this dynamic environment. We carried out a series of wind tunnel experiments testing how the morphology, density, and configuration of three foredune pioneer dune building plant species influence the most basic stage of dune initiation — nebkha formation around individual plants. We established monocultures of native Ammophila breviligulata and Panicum amarum and invasive Carex kobomugi in 1 m × 1 m planter boxes of sand to simulate approximate natural and managed densities and planting configurations on the US Mid-Atlantic coast. We subjected each box to constant 8.25 m/s wind for 30 min in a moveable-bed unilateral-flow wind tunnel with an unvegetated upwind sand bed. We quantified resulting topography with sub-millimeter precision and related it to plant morphology, density, and configuration. Plant morphology, density, and configuration all influenced the resulting topography. Larger plants produced larger nebkha with greater relief, height, and sand volume. However, nebkha area, height, and planform shape varied among species, and taller plants did not necessarily produce taller nebkha. The erect grasses, Ammophila and Panicum, produced more elongated, high-relief nebkha compared to the low-lying Carex, which produced lower and more symmetrical equant nebkha. A staggered planting configuration produced greater net sediment accumulation than non-staggered. We validated these results against high-resolution field topographies of foredune nebkha and found strong agreement between the datasets. Our results provide species-specific parameters useful in designing foredune plantings and beach management and can be used to parameterize vegetation in models of foredune evolution associated with different plant species. By first understanding the underlying ecogeomorphic feedbacks involved in nebkha formation, we can more effectively scale up to forecast coastal foredune evolution and recovery

Asymmetric Biotic Interactions and Abiotic Niche Differences Revealed by a Dynamic Joint Species Distribution Model

A species’ distribution and abundance are determined by abiotic conditions and biotic interactions with other species in the community. Most species distribution models correlate the occurrence of a single species with environmental variables only, and leave out biotic interactions. To test the importance of biotic interactions on occurrence and abundance, we compared a multivariate spatiotemporal model of the joint abundance of two invasive insects that share a host plant, hemlock woolly adelgid (HWA; Adelges tsugae) and elongate hemlock scale (EHS; Fiorina externa), to independent models that do not account for dependence among co‐occurring species. The joint model revealed that HWA responded more strongly to abiotic conditions than EHS. Additionally, HWA appeared to predispose stands to subsequent increase of EHS, but HWA abundance was not strongly dependent on EHS abundance. This study demonstrates how incorporating spatial and temporal dependence into a species distribution model can reveal the dependence of a species’ abundance on other species in the community. Accounting for dependence among co‐occurring species with a joint distribution model can also improve estimation of the abiotic niche for species affected by interspecific interactions

Towards mapping biodiversity from above: Can fusing lidar and hyperspectral remote sensing predict taxonomic, functional, and phylogenetic tree diversity in temperate forests?

Aim: Rapid global change is impacting the diversity of tree species and essential ecosystem functions and services of forests. It is therefore critical to understand and predict how the diversity of tree species is spatially distributed within and among forest biomes. Satellite remote sensing platforms have been used for decades to map forest structure and function but are limited in their capacity to monitor change by their relatively coarse spatial resolution and the complexity of scales at which different dimensions of biodiversity are observed in the field. Recently, airborne remote sensing platforms making use of passive high spectral resolution (i.e., hyperspectral) and active lidar data have been operationalized, providing an opportunity to disentangle how biodiversity patterns vary across space and time from field observations to larger scales. Most studies to date have focused on single sites and/or one sensor type; here we ask how multiple sensor types from the National Ecological Observatory Network’s Airborne Observation Platform (NEON AOP) perform across multiple sites in a single biome at the NEON field plot scale (i.e., 40 m × 40 m).Location: Eastern USA.Time period: 2017– 2018.Taxa studied: Trees.Methods: With a fusion of hyperspectral and lidar data from the NEON AOP, we as-sess the ability of high resolution remotely sensed metrics to measure biodiversity variation across eastern US temperate forests. We examine how taxonomic, functional, and phylogenetic measures of alpha diversity vary spatially and assess to what degree remotely sensed metrics correlate with in situ biodiversity metrics.Results: Models using estimates of forest function, canopy structure, and topographic diversity performed better than models containing each category alone. Our results show that canopy structural diversity, and not just spectral reflectance, is critical to predicting biodiversity.Main conclusions: We found that an approach that jointly leverages spectral properties related to leaf and canopy functional traits and forest health, lidar derived estimates of forest structure, fine-resolution topographic diversity, and careful consideration of biogeographical differences within and among biomes is needed to accurately map biodiversity variation from above

Potential ecological impacts of climate intervention by reflecting sunlight to cool Earth

As the effects of anthropogenic climate change become more severe, several approaches for deliberate climate intervention to reduce or stabilize Earth’s surface temperature have been proposed. Solar radiation modification (SRM) is one potential approach to partially counteract anthropogenic warming by reflecting a small proportion of the incoming solar radiation to increase Earth’s albedo. While climate science research has focused on the predicted climate effects of SRM, almost no studies have investigated the impacts that SRM would have on ecological systems. The impacts and risks posed by SRM would vary by implementation scenario, anthropogenic climate effects, geographic region, and by ecosystem, community, population, and organism. Complex interactions among Earth’s climate system and living systems would further affect SRM impacts and risks. We focus here on stratospheric aerosol intervention (SAI), a well-studied and relatively feasible SRM scheme that is likely to have a large impact on Earth’s surface temperature. We outline current gaps in knowledge about both helpful and harmful predicted effects of SAI on ecological systems. Desired ecological outcomes might also inform development of future SAI implementation scenarios. In addition to filling these knowledge gaps, increased collaboration between ecologists and climate scientists would identify a common set of SAI research goals and improve the communication about potential SAI impacts and risks with the public. Without this collaboration, forecasts of SAI impacts will overlook potential effects on biodiversity and ecosystem services for humanity

Invasive Congeners Differ in Successional Impacts across Space and Time

Invasive species can alter the succession of ecological communities because they are often adapted to the disturbed conditions that initiate succession. The extent to which this occurs may depend on how widely they are distributed across environmental gradients and how long they persist over the course of succession. We focus on plant communities of the USA Pacific Northwest coastal dunes, where disturbance is characterized by changes in sediment supply, and the plant community is dominated by two introduced grasses – the long-established Ammophila arenaria and the currently invading A. breviligulata. Previous studies showed that A. breviligulata has replaced A. arenaria and reduced community diversity. We hypothesize that this is largely due to A. breviligulata occupying a wider distribution across spatial environmental gradients and persisting in later-successional habitat than A. arenaria. We used multi-decadal chronosequences and a resurvey study spanning 2 decades to characterize distributions of both species across space and time, and investigated how these distributions were associated with changes in the plant community. The invading A. breviligulata persisted longer and occupied a wider spatial distribution across the dune, and this corresponded with a reduction in plant species richness and native cover. Furthermore, backdunes previously dominated by A. arenaria switched to being dominated by A. breviligulata, forest, or developed land over a 23-yr period. Ammophila breviligulata likely invades by displacing A. arenaria, and reduces plant diversity by maintaining its dominance into later successional backdunes. Our results suggest distinct roles in succession, with A. arenaria playing a more classically facilitative role and A. breviligulata a more inhibitory role. Differential abilities of closely-related invasive species to persist through time and occupy heterogeneous environments allows for distinct impacts on communities during succession

Biophysical feedback mediates effects of invasive grasses on coastal dune shape

Vegetation at the aquatic–terrestrial interface can alter landscape features through its growth and interactions with sediment and fluids. Even similar species may impart different effects due to variation in their interactions and feedbacks with the environment. Consequently, replacement of one engineering species by another can cause significant change in the physical environment. Here we investigate the species-specific ecological mechanisms influencing the geomorphology of U.S. Pacific Northwest coastal dunes. Over the last century, this system changed from open, shifting sand dunes with sparse vegetation (including native beach grass, Elymus mollis), to densely vegetated continuous foredune ridges resulting from the introduction and subsequent invasions of two nonnative grass species (Ammophila arenaria and Ammophila breviligulata), each of which is associated with different dune shapes and sediment supply rates along the coast. Here we propose a biophysical feedback responsible for differences in dune shape, and we investigate two, non-mutually exclusive ecological mechanisms for these differences: (1) species differ in their ability to capture sand and (2) species differ in their growth habit in response to sand deposition. To investigate sand capture, we used a moveable bed wind tunnel experiment and found that increasing tiller density increased sand capture efficiency and that, under different experimental densities, the native grass had higher sand capture efficiency compared to the Ammophila congeners. However, the greater densities of nonnative grasses under field conditions suggest that they have greater potential to capture more sand overall. We used a mesocosm experiment to look at plant growth responses to sand deposition and found that, in response to increasing sand supply rates, A. arenaria produced higher-density vertical tillers (characteristic of higher sand capture efficiency), while A. breviligulata and E. mollis responded with lower-density lateral tiller growth (characteristic of lower sand capture efficiency). Combined, these experiments provide evidence for a species-specific effect on coastal dune shape. Understanding how dominant ecosystem engineers, especially nonnative ones, differ in their interactions with abiotic factors is necessary to better parameterize coastal vulnerability models and inform management practices related to both coastal protection ecosystem services and ecosystem restoration.Keywords: invasive species, ecosystem engineer, wind tunnel, sediment deposition, foredune, Elymus mollis, Ammophila arenaria, ecomorphology, ecosystem service, geomorphology, sediment transport, Ammophila breviligulat

Towards connecting biodiversity and geodiversity across scales with satellite remote sensing

Issue Geodiversity (i.e., the variation in Earth\u27s abiotic processes and features) has strong effects on biodiversity patterns. However, major gaps remain in our understanding of how relationships between biodiversity and geodiversity vary over space and time. Biodiversity data are globally sparse and concentrated in particular regions. In contrast, many forms of geodiversity can be measured continuously across the globe with satellite remote sensing. Satellite remote sensing directly measures environmental variables with grain sizes as small as tens of metres and can therefore elucidate biodiversity–geodiversity relationships across scales. Evidence We show how one important geodiversity variable, elevation, relates to alpha, beta and gamma taxonomic diversity of trees across spatial scales. We use elevation from NASA\u27s Shuttle Radar Topography Mission (SRTM) and c. 16,000 Forest Inventory and Analysis plots to quantify spatial scaling relationships between biodiversity and geodiversity with generalized linear models (for alpha and gamma diversity) and beta regression (for beta diversity) across five spatial grains ranging from 5 to 100 km. We illustrate different relationships depending on the form of diversity; beta and gamma diversity show the strongest relationship with variation in elevation. Conclusion With the onset of climate change, it is more important than ever to examine geodiversity for its potential to foster biodiversity. Widely available satellite remotely sensed geodiversity data offer an important and expanding suite of measurements for understanding and predicting changes in different forms of biodiversity across scales. Interdisciplinary research teams spanning biodiversity, geoscience and remote sensing are well poised to advance understanding of biodiversity–geodiversity relationships across scales and guide the conservation of nature

Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community

It is a critical time to reflect on the National Ecological Observatory Network (NEON) science to date as well as envision what research can be done right now with NEON (and other) data and what training is needed to enable a diverse user community. NEON became fully operational in May 2019 and has pivoted from planning and construction to operation and maintenance. In this overview, the history of and foundational thinking around NEON are discussed. A framework of open science is described with a discussion of how NEON can be situated as part of a larger data constellation—across existing networks and different suites of ecological measurements and sensors. Next, a synthesis of early NEON science, based on \u3e100 existing publications, funded proposal efforts, and emergent science at the very first NEON Science Summit (hosted by Earth Lab at the University of Colorado Boulder in October 2019) is provided. Key questions that the ecology community will address with NEON data in the next 10 yr are outlined, from understanding drivers of biodiversity across spatial and temporal scales to defining complex feedback mechanisms in human–environmental systems. Last, the essential elements needed to engage and support a diverse and inclusive NEON user community are highlighted: training resources and tools that are openly available, funding for broad community engagement initiatives, and a mechanism to share and advertise those opportunities. NEON users require both the skills to work with NEON data and the ecological or environmental science domain knowledge to understand and interpret them. This paper synthesizes early directions in the community’s use of NEON data, and opportunities for the next 10 yr of NEON operations in emergent science themes, open science best practices, education and training, and community building