Model based grouping of species across environmental gradients

We present a novel approach to the statistical analysis and prediction of multispecies data. The approach allows the simultaneous grouping and quantification of multiple species’ responses to environmental gradients. The underlying statistical model is a finite mixture model, where mixing is performed over the individual species’ responses to environmental gradients. Species with similar responses are grouped with minimal information loss. We term these groups species archetypes. Each species archetype has an associated GLM that can be used to predict distributions with appropriate measures of uncertainty. Initially, we illustrate the concept and method using artificial data and then with application to real data comprising 200 species from the Great Barrier Reef (GBR) lagoon on 13 oceanographic and geological gradients from 12°S to 24°S. The 200 species from the GBR are well represented by 15 species archetypes. The model is interpreted through maps of the probability of presence for a fine scale set of locations throughout the study area. Maps of uncertainty are also produced to provide statistical context. The presence of each species archetype was strongly influenced by oceanographic gradients, principally temperature, oxygen and salinity. The number of species in each group ranged from 4 to 34. The method has potential application to the analysis of multispecies distribution patterns and for multispecies management.     

Characterizing species abundance distributions across taxa and ecosystems using a simple maximum entropy model

The species abundance distribution (SAD) is one of themost studied patterns in ecology due to its potential insights into commonness and rarity, community assembly, and patterns of biodiversity. It is well established that communities are composed of a few common and many rare species, and numerous theoretical models have been proposed to explain this pattern. However, no attempt has been made to determine how well these theoretical characterizations capture observed taxonomic and global-scale spatial variation in the general form of the distribution. Here, using data of a scope unprecedented in community ecology, we show that a simple maximum entropy model produces a truncated log-series distribution that can predict between 83% and 93% of the observed variation in the rank abundance of species across 15 848 globally distributed communities including birds, mammals, plants, and butterflies. This model requires knowledge of only the species richness and total abundance of the community to predict the full abundance distribution, which suggests that these factors are sufficient to understand the distribution for most purposes. Since geographic patterns in richness and abundance can often be successfully modeled, this approach should allow the distribution of commonness and rarity to be characterized, even in locations where empirical data are unavailable.     

An evaluation of environmental factors affecting species distributions

Many different models can be built to explain the distributions of species. Often there is no single model that is clearly better than the alternatives, and this leads to uncertainty over which environmental factors are limiting species’ distributions. We investigated the support for different environmental factors by determining the drop in model performance when selected predictors were excluded from the model building process. We used a paired t-test over 37 plant species so that an environmental factor was only deemed significant if it consistently improved the results for multiple species. Geology and winter minimum temperatures were found to be the environmental factors with the most support, with a significant drop in model performance when either of these factors was excluded. However, there was less support for summer maximum temperature, as other environmental factors could combine to produce similar model performance. Our method of evaluating environmental factors using multiple species will not be capable of detecting predictors that are only important for one or two species, but it is difficult to distinguish these from spurious correlations. The strength of the method is that it increases inference for factors that consistently affect the distributions of many species. We discourage the assessment of models against predefined benchmarks, such as an area under the curve (AUC) of more than 0.7, as many alternative models for the same species produce similar results. Therefore, the benchmarks do not provide any indication of how the performance of the selected model compares to alternative models, and they provide weak inference to accept any selected model.     

Estimating species occurrence, abundance, and detection probability using zero-inflated distributions

Researchers have developed methods to account for imperfect detection of species with either occupancy (presence absence) or count data using replicated sampling. We show how these approaches can be combined to simultaneously estimate occurrence, abundance, and detection probability by specifying a zero-inflated distribution for abundance. This approach may be particularly appropriate when patterns of occurrence and abundance arise from distinct processes operating at differing spatial or temporal scales. We apply the model to two data sets: (1) previously published data for a species of duck, Anas platyrhynchos, and (2) data for a stream fish species, Etheostoma scotti. We show that in these cases, an incomplete-detection zero-inflated modeling approach yields a superior fit to the data than other models. We propose that zero-inflated abundance models accounting for incomplete detection be considered when replicate count data are available.     

Grassland root communities: species distributions and how they are linked to aboveground abundance

There is little comprehensive information on the distribution of root systems among coexisting species, despite the expected importance of those distributions in determining the composition and diversity of plant communities. This gap in knowledge is particularly acute for grasslands, which possess large numbers of species with morphologically indistinguishable roots. In this study we adapted a molecular method, fluorescent fragment length polymorphism, to identify root fragments and determine species root distributions in two grasslands in Yellowstone National Park (YNP). Aboveground biomass was measured, and soil cores (2 cm in diameter) were collected to depths of 40 cm and 90 cm in an upland, dry grassland and a mesic, slope-bottom grassland, respectively, at peak foliar expansion. Cores were subdivided, and species that occurred in each 10-cm interval were identified. The results indicated that the average number of species in 10-cm intervals (31 cm3) throughout the sampled soil profile was 3.9 and 2.8 species at a dry grassland and a mesic grassland, respectively. By contrast, there was an average of 6.7 and 14.1 species per 0.5 m2, determined by the presence of shoot material, at dry and mesic sites, respectively. There was no relationship between soil depth and number of species per 10-cm interval in either grassland, despite the exponential decline of root biomass with soil depth at both sites. There also was no relationship between root frequency (i.e., the percentage of samples in which a species occurred) and soil depth for the vast majority of species at both sites. The preponderance of species were distributed throughout the soil profile at both sites. Assembly analyses indicated that species root occurrences were randomly assorted in all soil intervals at both sites, with the exception that Festuca idahoensis segregated from Artemisia tridentata and Pseudoroegnaria spicata in 10-20 cm soil at the dry grassland. Root frequency throughout the entire sampled soil profile was positively associated with shoot biomass among species. Together these results indicated the importance of large, well-proliferated root systems in establishing aboveground dominance. The findings suggest that spatial belowground segregation of species probably plays a minor role in fostering resource partitioning and species coexistence in these YNP grasslands.     

Null model analysis of species associations using abundance data

The influence of negative species interactions has dominated much of the literature on community assembly rules. Patterns of negative covariation among species are typically documented through null model analyses of binary presence/absence matrices in which rows designate species, columns designate sites, and the matrix entries indicate the presence (1) or absence (0) of a particular species in a particular site. However, the outcome of species interactions ultimately depends on population-level processes. Therefore, patterns of species segregation and aggregation might be more clearly expressed in abundance matrices, in which the matrix entries indicate the abundance or density of a species in a particular site. We conducted a series of benchmark tests to evaluate the performance of 14 candidate null model algorithms and six covariation metrics that can be used with abundance matrices. We first created a series of random test matrices by sampling a metacommunity from a lognormal species abundance distribution. We also created a series of structured matrices by altering the random matrices to incorporate patterns of pairwise species segregation and aggregation. We next screened each algorithm-index combination with the random and structured matrices to determine which tests had low Type I error rates and good power for detecting segregated and aggregated species distributions. In our benchmark tests, the best-performing null model does not constrain species richness, but assigns individuals to matrix cells proportional to the observed row and column marginal distributions until, for each row and column, total abundances are reached. Using this null model algorithm with a set of four covariance metrics, we tested for patterns of species segregation and aggregation in a collection of 149 empirical abundance matrices and 36 interaction matrices collated from published papers and posted data sets. More than 80% of the matrices were significantly segregated, which reinforces a previous meta-analysis of presence/absence matrices. However, using two of the metrics we detected a significant pattern of aggregation for plants and for the interaction matrices (which include plant-pollinator data sets). These results suggest that abundance matrices, analyzed with an appropriate null model, may be a powerful tool for quantifying patterns of species segregation and aggregation.     

Frequency, not relative abundance, of temperate tree species varies along climate gradients in eastern North America

There have been many attempts to model the impacts of climate change on the distributions of temperate tree species, but empirical analyses of the effects of climate on the distribution and abundance of tree species have lagged far behind the models. Here, we used forest inventory data to characterize variation in adult tree abundance along climate gradients for the 24 most common tree species in the northeastern United States. The two components of our measure of species abundance--local frequency vs. relative abundance--showed dramatically different patterns of variation along gradients of mean annual temperature and precipitation. Local frequency (i.e., the percentage of plots in a given climate in which a species occurred) varied strongly for all 24 species, particularly as a function of temperature. Relative abundance when present in a plot, on the other hand, was effectively constant for most species right up to their estimated climatic range limits. Although the range limits for both temperature and precipitation were quite broad for all of the species, the range of climates within which a species was common (i.e., high frequency) was much narrower. Because frequency in sites within a given climate shows a strong sensitivity to temperature, at least, this suggests that the processes determining canopy tree recruitment on new sites also vary strongly with climate.     

Comparing environmental influences on coral bleaching across and within species using clustered binomial regression

Differential susceptibility among reef-building coral species can lead to community shifts and loss of diversity as a result of temperature-induced mass bleaching events. We evaluate environmental influences on coral colony bleaching over an 8-year period in the Florida Keys, USA. Clustered binomial regression is used to develop models incorporating taxon-specific responses to the environment in order to identify conditions and species for which bleaching is likely to be severe. By building three separate models incorporating environment, community composition, and taxon-specific responses to environment, we show observed prevalence of bleaching reflects an interaction between community composition and local environmental conditions. Environmental variables, including elevated sea temperature, solar radiation, and reef depth, explained 90% and 78% of variability in colony bleaching across space and time, respectively. The effects of environmental variables were only partially explained (33% of variability) by corresponding differences in community composition. Taxon-specific models indicated individual coral species responded differently to local environmental conditions and had different sensitivities to temperature-induced bleaching. For many coral species, but not all, bleaching was exacerbated by high solar radiation. A 25% reduction in the probability of bleaching in shallow locations for one species may reflect an ability to acclimatize to local conditions. Overall, model results indicate predictions of coral bleaching require knowledge of not just the environmental conditions or community composition, but the responses of individual species to the environment. Model development provides a useful tool for coral reef management by quantifying the influence of the local environment on individual species bleaching sensitivities, identifying susceptible species, and predicting the likelihood of mass bleaching events with changing environmental conditions.     

Morphological analysis of growth forms of branching marine sessile organisms along environmental gradients

In this paper a series of growth forms of the sponge Haliclona oculata, the hydrozoan Millepora alcicornis and the scleractinian coral Pocillopora damicornis are morphologically analysed. The growth forms of these species were collected along a gradient of the amount of water movement. In this analysis it is demonstrated that, although these species are from very different taxonomical groups, the degree of compactness of the growth forms shows a similar trend as a response to the exposure to water movement. In all three species the growth forms gradually change from thin-branching to more compact shapes, as evaluated by measurements of various morphological characteristics. Other morphological measurements, in particular the average distance between branch tips and neighbouring branches (“branch spacing”) show a more species-specific pattern. Species in which fusion of branches is almost never observed, as for example P. damicornis, are characterized by a relatively low standard deviation of branch spacing. Species in which anastomosis frequently occurs (H. oculata and M. alcicornis) are characterized by a relatively high standard deviation in branch spacing. The final aim of this research approach is to use the morphological data acquired here in combination with morphological simulation models to gain a better understanding of the growth and form of these organisms and the impact of the physical environment (hydrodynamics and availability of light required for photosynthesis). Received: 8 July 1998 / Accepted: 9 February 1999     

Drivers of euphausiid species abundance and numerical abundance in the Atlantic Ocean

Mid-ocean ridges are common features of the world’s oceans but there is a lack of understanding as to how their presence affects overlying pelagic biota. The Mid-Atlantic Ridge (MAR) is a dominant feature of the Atlantic Ocean. Here, we examined data on euphausiid distribution and abundance arising from several international research programmes and from the continuous plankton recorder. We used a generalized additive model (GAM) framework to explore spatial patterns of variability in euphausiid distribution on, and at either side of, the MAR from 60°N to 55°S in conjunction with variability in a suite of biological, physical and environmental parameters. Euphausiid species abundance peaked in mid-latitudes and was significantly higher on the ridge than in adjacent waters, but the ridge did not influence numerical abundance significantly. Sea surface temperature (SST) was the most important single factor influencing both euphausiid numerical abundance and species abundance. Increases in sea surface height variance, a proxy for mixing, increased the numerical abundance of euphausiids. GAM predictions of variability in species abundance as a function of SST and depth of the mixed layer were consistent with present theories, which suggest that pelagic niche availability is related to the thermal structure of the near surface water: more deeply-mixed water contained higher euphausiid biodiversity. In addition to exposing present distributional patterns, the GAM framework enables responses to potential future and past environmental variability including temperature change to be explored.     

Multi-model analysis of tree competition along environmental gradients in southern New England forests.

Robust predictions of competitive interactions among canopy trees and variation in tree growth along environmental gradients represent key challenges for the management of mixed-species, uneven-aged forests. We analyzed the effects of competition on tree growth along environmental gradients for eight of the most common tree species in southern New England and southeastern New York using forest inventory and analysis (FIA) data, information theoretic decision criteria, and multi-model inference to evaluate models. The suite of models estimated growth of individual trees as a species-specific function of average potential diameter growth, tree diameter at breast height, local environmental conditions, and crowding by neighboring trees. We used ordination based on the relative basal area of species to generate a measure of site conditions in each plot. Two ordination axes were consistent with variation in species abundance along moisture and fertility gradients. Estimated potential growth varied along at least one of these axes for six of the eight species; peak relative abundance of less shade-tolerant species was in all cases displaced away from sites where they showed maximum potential growth. Our crowding functions estimate the strength of competitive effects of neighbors; only one species showed support for the hypothesis that all species of competitors have equivalent effects on growth. The relative weight of evidence (Akaike weights) for the best models varied from a low of 0.207 for Fraxinus americana to 0.747 for Quercus rubra. In such cases, model averaging provides a more robust platform for prediction than that based solely on the best model. We show that predictions based on the selected best models dramatically overestimated differences between species relative to predictions based on the averaged set of models.     

Conserving the abundance of nonthreatened species

Human modification of the environment is driving declines in population size and distributional extent of much of the world's biota. These declines extend to many of the most abundant and widespread species, for which proportionally small declines can result in the loss of vast numbers of individuals, biomass, and interactions. These losses could have major localized effects on ecological and cultural processes and services without elevating a species’ global extinction risk. Although most conservation effort is directed at species threatened with extinction in the very near term, the value of retaining abundance regardless of global extinction risk is justifiable based on many biodiversity or ecosystem service metrics, including cultural services, at scales from local to global. The challenges of identifying conservation priorities for widespread and abundant species include quantifying the effects of species’ abundance on services and understanding how these effects are realized as populations decline. Negative effects of population declines may be disconnected from the threat processes driving declines because of species movements and environment flows (e.g., hydrology). Conservation prioritization for these species shares greater similarity with invasive species risk assessments than extinction risk assessments because of the importance of local context and per capita effects of abundance on other species. Because conservation priorities usually focus on preventing the extinction of threatened species, the rationale and objectives for incorporating declines of nonthreatened species must be clearly articulated, going beyond extinction risk to encompass the range of likely harmful effects (e.g., secondary extinctions, loss of ecosystem services) if declines persist or are not reversed. Research should focus on characterizing the effects of local declines in species that are not threatened globally across a range of ecosystem services and quantifying the spatial distribution of these effects through the distribution of abundance. The case for conserving abundance in nonthreatened species can be made most powerfully when the costs of losing this abundance are better understood.     

Patterns of sponge biodiversity and abundance across different biogeographic regions

Few studies have compared the underlying nature or structure of marine communities and assemblages across broad spatial scales, despite the importance of such comparisons in understanding global scale responses to environmental change and biodiversity conservation. The aim of this study was to examine the consistency of relationships between sponge abundance and richness on the undersides of boulders (to control for multiple confounding factors) in relation to space availability (boulder size) in three widely separated biogeographic regions. Sponges followed typical species-area (SA) relationships irrespective of site or ocean and we consistently found no decrease in sponge richness at larger boulder sizes. We also found reliable underlying density–area (DA) relationships, with larger boulders supporting more sponge patches at all sites. Although the general SA and DA relationships were similar between oceans and sites, the exact nature of these relationships in terms of the actual species present per unit area, total number of species present or density differed between sites. There were no consistent differences between SA and DA relationships at each locality, suggesting that although disturbance (particularly wave action) regimes may play an important role in controlling sponge biodiversity and abundance, its effects are manifested differently at local-scales. Even though boulders have received a considerable amount of research effort over the past three decades, this is the first study to examine the consistency of DA and SA relationships between ocean basins, finding similar relationships.     

Herbivory in the gammarid amphipod Aora typica: relationships between consumption rates, performance and abundance across ten seaweed species

This paper reveals a substantial capacity for herbivory of seaweeds in the gammarid amphipod Aora typica, adults eating seven of ten taxonomically and morphologically diverse seaweed species offered to them in a no-choice assay. The green algae Ulva spathulata and Enteromorpha intestinalis were consumed at the highest rates in both no-choice (2.3–2.5 mg blotted weight individual⁻¹ day⁻¹) and multiple-choice assays (0.5–1.3 mg blotted weight individual⁻¹ day⁻¹). Adult A. typica collected from two different species of brown seaweeds had very similar feeding preferences to each other. Juvenile A. typica grew to reproductive maturity on the green algae E. intestinalis and U. spathulata, and the brown algae Carpophyllum maschalocarpum and Ecklonia radiata. In common with previous studies on members of other amphipod families, survivorship of juvenile amphipods was positively correlated with feeding preferences of adults across seaweed species (r ²=0.43, P=0.04). However, densities of A. typica on seaweeds in the field (excluding the intertidal E. intestinalis and U. spathulata) were not significantly correlated with feeding preferences of adults (r ²=0.07, P=0.5) or survivorship of juveniles (r ²=0.17, P=0.31). This suggests that either host seaweeds are not a major dietary component of these amphipods in nature, or that the host’s value as a food source is overridden by other properties such as the degree of shelter it affords from larger consumers. This study provides the first demonstration that a member of the cosmopolitan amphipod family Aoridae is capable of consuming a diverse range of seaweeds.     

Use of ecoacoustics to determine biodiversity patterns across ecological gradients

The variety of local animal sounds characterizes a landscape. We used ecoacoustics to noninvasively assess the species richness of various biotopes typical of an ecofriendly forest plantation with diverse ecological gradients and both nonnative and indigenous vegetation. The reference area was an adjacent large World Heritage Site protected area (PA). All sites were in a global biodiversity hotspot. Our results showed how taxa segregated into various biotopes. We identified 65 singing species, including birds, frogs, crickets, and katydids. Large, natural, protected grassland sites in the PA had the highest mean acoustic diversity (14.1 species/site). Areas covered in nonnative timber or grass species were devoid of acoustic species. Sites grazed by native and domestic megaherbivores were fairly rich (5.1) in acoustic species but none were unique to this habitat type, where acoustic diversity was greater than in intensively managed grassland sites (0.04). Natural vegetation patches inside the plantation mosaic supported high mean acoustic diversity (indigenous forests 7.6, grasslands 8.0, wetlands 9.1), which increased as plant heterogeneity and patch size increased. Indigenous forest patches within the plantation mosaic contained a highly characteristic acoustic species assemblage, emphasizing their complementary contribution to local biodiversity. Overall, acoustic signals determined spatial biodiversity patterns and can be a useful tool for guiding conservation.     

Facilitation across stress gradients: the importance of local adaptation

While there is some information on genetic variation in response to competition in plants, we know nothing about intraspecific variation in facilitation. Previous studies suggest that facilitation should increase fitness in stressful environments. However, whether a plant experiences an environment as stressful may depend on prior adaptive responses to stressors at a site. Local adaptation to stress at a site may reduce the likelihood of facilitation. Seeds of Plantago erecta from stressful (serpentine soil) and non-stressful (non-serpentine soil) edaphic environments were reciprocally planted into these two soil types. Although competition did not differ significantly among seed sources, there was evidence for a local adaptation effect on facilitation. Non-serpentine seeds planted into serpentine soil exhibited greater individual plant biomass at higher densities. The interaction between population source and growth environment indicates a role for evolutionary processes such as local adaptation in the expression of facilitation in plants.     

Assessing the shelf life of cost‐efficient conservation plans for species at risk across gradients of agricultural land use

High costs of land in agricultural regions warrant spatial prioritization approaches to conservation that explicitly consider land prices to produce protected‐area networks that accomplish targets efficiently. However, land‐use changes in such regions and delays between plan design and implementation may render optimized plans obsolete before implementation occurs. To measure the shelf life of cost‐efficient conservation plans, we simulated a land‐acquisition and restoration initiative aimed at conserving species at risk in Canada's farmlands. We accounted for observed changes in land‐acquisition costs and in agricultural intensity based on censuses of agriculture taken from 1986 to 2011. For each year of data, we mapped costs and areas of conservation priority designated using Marxan. We compared plans to test for changes through time in the arrangement of high‐priority sites and in the total cost of each plan. For acquisition costs, we measured the savings from accounting for prices during site selection. Land‐acquisition costs and land‐use intensity generally rose over time independent of inflation (24–78%), although rates of change were heterogeneous through space and decreased in some areas. Accounting for spatial variation in land price lowered the cost of conservation plans by 1.73–13.9%, decreased the range of costs by 19–82%, and created unique solutions from which to choose. Despite the rise in plan costs over time, the high conservation priority of particular areas remained consistent. Delaying conservation in these critical areas may compromise what optimized conservation plans can achieve. In the case of Canadian farmland, rapid conservation action is cost‐effective, even with moderate levels of uncertainty in how to implement restoration goals.     

Spatial variance in abundance and occupancy of corals across broad geographic scales

Species assemblages vary in structure due to a wide variety of processes operating at ecological and much broader biogeographical scales. Cross-scale studies of assemblage structure are necessary to fully understand this variability. Here, we evaluate the abundance and occupancy patterns of hierarchically sampled coral assemblages in three habitats (reef flat, crest, and slope) and five regions (Indonesia, Papua New Guinea, the Solomon Islands, American Samoa, and the Society Islands) across the west-central Pacific Ocean. Specifically, we compare two alternative models that unify spatial variance and occupancy via the negative binomial distribution. The first assumes a power-law scaling between the mean and variance of abundance; the second assumes a quadratic variance-mean relationship and a constant abundance-invariant aggregation parameter. Surprisingly, the well-established power-law model performs worse than the model assuming abundance-invariant aggregation, for both variance-mean and occupancy-abundance relationships. We also find strong evidence for regional and habitat variation in these relationships and in the levels of aggregation estimated by the abundance-invariant aggregation model. Among habitats, corals on reef flats exhibited lower occupancy and higher levels of aggregation compared to reef crests and slopes. Among regions, low occupancy and high aggregation were most pronounced across all habitats in American Samoa. These patterns may be related to habitat and regional differences in disturbance and recovery processes. Our results suggest that the spatial scaling of abundance and occupancy is sensitive to processes operating among these habitats and at regional scales. However, the consistency of these relationships across species within assemblages suggests that a theoretical unification of spatial variance and occupancy patterns is indeed possible.     

Maximum entropy modeling of species geographic distributions

The availability of detailed environmental data, together with inexpensive and powerful computers, has fueled a rapid increase in predictive modeling of species environmental requirements and geographic distributions. For some species, detailed presence/absence occurrence data are available, allowing the use of a variety of standard statistical techniques. However, absence data are not available for most species. In this paper, we introduce the use of the maximum entropy method (Maxent) for modeling species geographic distributions with presence-only data. Maxent is a general-purpose machine learning method with a simple and precise mathematical formulation, and it has a number of aspects that make it well-suited for species distribution modeling. In order to investigate the efficacy of the method, here we perform a continental-scale case study using two Neotropical mammals: a lowland species of sloth, Bradypus variegatus, and a small montane murid rodent, Microryzomys minutus. We compared Maxent predictions with those of a commonly used presence-only modeling method, the Genetic Algorithm for Rule-Set Prediction (GARP). We made predictions on 10 random subsets of the occurrence records for both species, and then used the remaining localities for testing. Both algorithms provided reasonable estimates of the species’ range, far superior to the shaded outline maps available in field guides. All models were significantly better than random in both binomial tests of omission and receiver operating characteristic (ROC) analyses. The area under the ROC curve (AUC) was almost always higher for Maxent, indicating better discrimination of suitable versus unsuitable areas for the species. The Maxent modeling approach can be used in its present form for many applications with presence-only datasets, and merits further research and development.     

The environmental effects of trade within and across sectors

This paper presents a model that combines within and across sector channels through which trade affects our environment by embedding heterogeneous firms and fixed costs into a two-sector framework with an endogenous response to environmental policy. In contrast to existing literature that tends to examine these channels separately, the combined framework developed here shows how cross-sector comparative advantage and within-sector responses to trade and environmental policy or factor endowments interact to affect our environment through three channels: changes in output, cross-sector market share, and emissions intensity. In contrast to a single-sector model with neutral productivity, consideration of two sectors allows for trade liberalization to affect the allocation of inputs in each sector and thereby affect total pollution output. The additional consideration of heterogeneous firm responses to falling trade costs will generate endogenous increases in productivity that increase output, reduce aggregate emissions intensity, and moderate the cross-sector resource adjustment, relative to a representative-firm model. Simulation results show how the combined framework can replicate existing empirical outcomes, and provide concise ceteris paribus insights regarding the potential role of trade and environmental policy changes and factor expansion in driving observed outcomes and their contribution to each of the three channels.