Integrating larval connectivity into the marine conservation decision-making process across spatial scales

Larval dispersal connectivity is typically integrated into spatial conservation decisions at regional or national scales, but implementing agencies struggle with translating these methods to local scales. We used larval dispersal connectivity at regional (hundreds of kilometers) and local (tens of kilometers) scales to aid in design of networks of no-take reserves in Southeast Sulawesi, Indonesia. We used Marxan with Connectivity informed by biophysical larval dispersal models and remotely sensed coral reef habitat data to design marine reserve networks for 4 commercially important reef species across the region. We complemented regional spatial prioritization with decision trees that combined network-based connectivity metrics and habitat quality to design reserve boundaries locally. Decision trees were used in consensus-based workshops with stakeholders to qualitatively assess site desirability, and Marxan was used to identify areas for subsequent network expansion. Priority areas for protection and expected benefits differed among species, with little overlap in reserve network solutions. Because reef quality varied considerably across reefs, we suggest reef degradation must inform the interpretation of larval dispersal patterns and the conservation benefits achievable from protecting reefs. Our methods can be readily applied by conservation practitioners, in this region and elsewhere, to integrate connectivity data across multiple spatial scales.     

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.     

Bridging gaps in demographic analysis with phylogenetic imputation

Phylogenetically informed imputation methods have rarely been applied to estimate missing values in demographic data but may be a powerful tool for reconstructing vital rates of survival, maturation, and fecundity for species of conservation concern. Imputed vital rates could be used to parameterize demographic models to explore how populations respond when vital rates are perturbed. We used standardized vital rate estimates for 50 bird species to assess the use of phylogenetic imputation to fill gaps in demographic data. We calculated imputation accuracy for vital rates of focal species excluded from the data set either singly or in combination and with and without phylogeny, body mass, and life-history trait data. We used imputed vital rates to calculate demographic metrics, including generation time, to validate the use of imputation in demographic analyses. Covariance among vital rates and other trait data provided a strong basis to guide imputation of missing vital rates in birds, even in the absence of phylogenetic information. Mean NRMSE for null and phylogenetic models differed by <0.01 except when no vital rates were available or for vital rates with high phylogenetic signal (Pagel's λ > 0.8). In these cases, including body mass and life-history trait data compensated for lack of phylogenetic information: mean normalized root mean square error (NRMSE) for null and phylogenetic models differed by <0.01 for adult survival and <0.04 for maturation rate. Estimates of demographic metrics were sensitive to the accuracy of imputed vital rates. For example, mean error in generation time doubled in response to inaccurate estimates of maturation time. Accurate demographic data and metrics, such as generation time, are needed to inform conservation planning processes, for example through International Union for Conservation of Nature Red List assessments and population viability analysis. Imputed vital rates could be useful in this context but, as for any estimated model parameters, awareness of the sensitivities of demographic model outputs to the imputed vital rates is essential.     

Incorporating putatively neutral and adaptive genomic data into marine conservation planning

The availability of genomic data for an increasing number of species makes it possible to incorporate evolutionary processes into conservation plans. Recent studies show how genetic data can inform spatial conservation prioritization (SCP), but they focus on metrics of diversity and distinctness derived primarily from neutral genetic data sets. Identifying adaptive genetic markers can provide important information regarding the capacity for populations to adapt to environmental change. Yet, the effect of including metrics based on adaptive genomic data into SCP in comparison to more widely used neutral genetic metrics has not been explored. We used existing genomic data on a commercially exploited species, the giant California sea cucumber (Parastichopus californicus), to perform SCP for the coastal region of British Columbia (BC), Canada. Using a RAD-seq data set for 717 P. californicus individuals across 24 sampling locations, we identified putatively adaptive (i.e., candidate) single nucleotide polymorphisms (SNPs) based on genotype–environment associations with seafloor temperature. We calculated various metrics for both neutral and candidate SNPs and compared SCP outcomes with independent metrics and combinations of metrics. Priority areas varied depending on whether neutral or candidate SNPs were used and on the specific metric used. For example, targeting sites with a high frequency of warm-temperature-associated alleles to support persistence under future warming prioritized areas in the southern coastal region. In contrast, targeting sites with high expected heterozygosity at candidate loci to support persistence under future environmental uncertainty prioritized areas in the north. When combining metrics, all scenarios generated intermediate solutions, protecting sites that span latitudinal and thermal gradients. Our results demonstrate that distinguishing between neutral and adaptive markers can affect conservation solutions and emphasize the importance of defining objectives when choosing among various genomic metrics for SCP.     

Predicting landscape-scale biodiversity recovery by natural tropical forest regrowth

Natural forest regrowth is a cost-effective, nature-based solution for biodiversity recovery, yet different socioenvironmental factors can lead to variable outcomes. A critical knowledge gap in forest restoration planning is how to predict where natural forest regrowth is likely to lead to high levels of biodiversity recovery, which is an indicator of conservation value and the potential provisioning of diverse ecosystem services. We sought to predict and map landscape-scale recovery of species richness and total abundance of vertebrates, invertebrates, and plants in tropical and subtropical second-growth forests to inform spatial restoration planning. First, we conducted a global meta-analysis to quantify the extent to which recovery of species richness and total abundance in second-growth forests deviated from biodiversity values in reference old-growth forests in the same landscape. Second, we employed a machine-learning algorithm and a comprehensive set of socioenvironmental factors to spatially predict landscape-scale deviation and map it. Models explained on average 34% of observed variance in recovery (range 9–51%). Landscape-scale biodiversity recovery in second-growth forests was spatially predicted based on socioenvironmental landscape factors (human demography, land use and cover, anthropogenic and natural disturbance, ecosystem productivity, and topography and soil chemistry); was significantly higher for species richness than for total abundance for vertebrates (median range-adjusted predicted deviation 0.09 vs. 0.34) and invertebrates (0.2 vs. 0.35) but not for plants (which showed a similar recovery for both metrics [0.24 vs. 0.25]); and was positively correlated for total abundance of plant and vertebrate species (Pearson r = 0.45, p = 0.001). Our approach can help identify tropical and subtropical forest landscapes with high potential for biodiversity recovery through natural forest regrowth.     

Using individual-based movement information to identify spatial conservation priorities for mobile species

The optimal design of reserve networks and fisheries closures depends on species occurrence information and knowledge of how anthropogenic impacts interact with the species concerned. However, challenges in surveying mobile and cryptic species over adequate spatial and temporal scales can mask the importance of particular habitats, leading to uncertainty about which areas to protect to optimize conservation efforts. We investigated how telemetry-derived locations can help guide the scale and timing of fisheries closures with the aim of reducing threatened species bycatch. Forty juvenile speartooth sharks (Glyphis glyphis) were monitored over 22 months with implanted acoustic transmitters and an array of hydrophone receivers. Using the decision-support tool Marxan, we formulated a permanent fisheries closure that prioritized areas used more frequently by tagged sharks and considered areas perceived as having high value to fisheries. To explore how the size of the permanent closure compared with an alternative set of time-area closures (i.e., where different areas were closed to fishing at different times of year), we used a cluster analysis to group months that had similar arrangements of selected planning units (informed by shark movements during that month) into 2 time-area closures. Sharks were consistent in their timing and direction of migratory movements, but the number of tagged sharks made a big difference in the placement of the permanent closure; 30 individuals were needed to capture behavioral heterogeneity. The dry-season (May–January) and wet-season (February–April) time-area closures opened 20% and 25% more planning units to fishing, respectively, compared with the permanent closure with boundaries fixed in space and time. Our results show that telemetry has the potential to inform and improve spatial management of mobile species and that the temporal component of tracking data can be incorporated into prioritizations to reduce possible impacts of spatial closures on established fisheries.     

Need for multiscale planning for conservation of urban bats

For over a century there have been continual efforts to incorporate nature into urban planning. These efforts (i.e., urban reconciliation) aim to manage and create habitats that support biodiversity within cities. Given that species select habitat at different spatial scales, understanding the scale at which urban species respond to their environment is critical to the success of urban reconciliation efforts. We assessed species–habitat relationships for common bat species at 50‐m, 500‐m, and 1 km spatial scales in the Chicago (U.S.A.) metropolitan area and predicted bat activity across the greater Chicago region. Habitat characteristics across all measured scales were important predictors of silver‐haired bat (Lasionycteris noctivagans) and eastern red bat (Lasiurus borealis) activity, and big brown bat (Eptesicus fuscus) activity was significantly lower at urban sites relative to rural sites. Open vegetation had a negative effect on silver‐haired bat activity at the 50‐m scale but a positive effect at the 500‐m scale, indicating potential shifts in the relative importance of some habitat characteristics at different scales. These results demonstrate that localized effects may be constrained by broader spatial patterns. Our findings highlight the importance of considering scale in urban reconciliation efforts and our landscape predictions provide information that can help prioritize urban conservation work.     

Bridging information domains to improve ecological understanding of biological invasions in a marine ecosystem

We devised a practical method for integrating information on 2 marine invasive species using 3 different approaches: standardized ecological monitoring, online-reporting databases, and surveys of anglers and crabbers. Focusing on 2 recently introduced species with different characteristics, the Asian shore crab (Hemigrapsus sanguineus) and Chinese mitten crab (Eriocheir sinensis), in the Hudson-Raritan watershed of New York and New Jersey, we used sensitivity analyses to explore the relative contribution of each information source to knowledge of species abundance and distribution. All 3 information sources contributed something unique to understanding abundance and distribution of the introduced crabs. Online and survey data on Asian shore crabs significantly affected predictions of abundance, whereas monitoring data did not. When survey data were omitted, abundance estimates were unchanged over time, but when they were included, the model predicted an increased abundance in 2012. All 3 data sets for the Asian shore crab significantly affected estimates of species coverage; surveys had the biggest influence, increasing range size by 4097.25 km². For the catadromous Chinese mitten crab, ecological monitoring data collected in freshwater shortly after the original sighting significantly shaped model estimates for abundance and documented the establishment phase of the mitten crab in an area outside the spatial scope of the surveyed resource users. However, the survey data significantly enlarged mitten crab range-size estimates by 6498.01 km². By demonstrating that data integration produced an image of the invasion process that would not have emerged had we used any 1 method individually, model results provide evidence for the advantages of an interdisciplinary approach.     

Complex and nonlinear climate-driven changes in freshwater insect communities over 42 years

The ongoing biodiversity crisis becomes evident in the widely observed decline in abundance and diversity of species, profound changes in community structure, and shifts in species’ phenology. Insects are among the most affected groups, with documented decreases in abundance up to 76% in the last 25–30 years in some terrestrial ecosystems. Identifying the underlying drivers is a major obstacle as most ecosystems are affected by multiple stressors simultaneously and in situ measurements of environmental variables are often missing. In our study, we investigated a headwater stream belonging to the most common stream type in Germany located in a nature reserve with no major anthropogenic impacts except climate change. We used the most comprehensive quantitative long-term data set on aquatic insects available, which includes weekly measurements of species-level insect abundance, daily water temperature and stream discharge as well as measurements of additional physicochemical variables for a 42-year period (1969–2010). Overall, water temperature increased by 1.88 °C and discharge patterns changed significantly. These changes were accompanied by an 81.6% decline in insect abundance, but an increase in richness (+8.5%), Shannon diversity (+22.7%), evenness (+22.4%), and interannual turnover (+34%). Moreover, the community's trophic structure and phenology changed: the duration of emergence increased by 15.2 days, whereas the peak of emergence moved 13.4 days earlier. Additionally, we observed short-term fluctuations (<5 years) in almost all metrics as well as complex and nonlinear responses of the community toward climate change that would have been missed by simply using snapshot data or shorter time series. Our results indicate that climate change has already altered biotic communities severely even in protected areas, where no other interacting stressors (pollution, habitat fragmentation, etc.) are present. This is a striking example of the scientific value of comprehensive long-term data in capturing the complex responses of communities toward climate change.     

Effects of crowding due to habitat loss on species assemblage patterns

Terrestrial animals are negatively affected by habitat loss, which is assessed on a landscape scale, whereas secondary effects of habitat loss, such as crowding, are usually disregarded. Such impacts are inherently hard to address and poorly understood, and there is a growing concern that they could have dire consequences. We sampled birds throughout a deforestation process to assess crowding stress in an adjacent habitat remnant in the southern Brazilian Atlantic Forest. Crowding is expected of highly mobile taxa, especially given the microhabitat heterogeneity of Neotropical forests, and we hypothesized that the arrival of new individuals or species in refuges shifts assemblage patterns. We used point counts to obtain bird abundances in a before-after-control-impact design sampling of a deforestation event. Temporal changes in taxonomic and functional diversity were examined with metrics used to assess alpha and beta diversity, turnover of taxonomic and functional similarity, and taxonomic and functional composition. Over time increased abundance of some species altered the Simpson index and affected the abundance-distribution of traits in the habitat remnant. Taxonomic composition and functional composition changed in the remnant, and thus bird assemblages changed over time. Taxonomic and functional metrics indicated that fugitives affected resident assemblages in refuges, and effects endured >2 years after the deforestation processes had ceased. Dissimilarity of taxonomic composition between pre- and postdeforestation assemblages increased, whereas functional composition reverted to preimpact conditions. We found that ecological disruptions resulted from crowding and escalated into disruptions of species’ assemblages and potentially compromising ecosystem functioning. It is important to consider crowding effects of highly mobile taxa during impact assessments, especially in large-scale infrastructure projects that may affect larger areas than is assumed.     

Spatial heterogeneity in distribution and ecology of Western Palearctic birds

Species vary in abundance and heterogeneity of spatial distribution, and the ecological and evolutionary consequences of such variability are poorly known. Evolutionary adaptation to heterogeneously distributed resources may arise from local adaptation with individuals of such locally adapted populations rarely dispersing long distances and hence having small populations and small overall ranges. We quantified mean population density and spatial heterogeneity in population density of 197 bird species across 12 similarly sized regions in the Western Palearctic. Variance in population density among regions differed significantly from a Poisson distribution, suggesting that random processes cannot explain the observed patterns. National estimates of means and variances in population density were positively correlated with continental estimates, suggesting that means and variances were maintained across spatial scales. We used Morisita's index of population abundance as an estimate of heterogeneity in distribution among regions to test a number of predictions. Heterogeneously distributed passerine bird species as reflected by Morisita's index had small populations, low population densities, and small breeding ranges. Their breeding populations had been consistently maintained at low levels for considerable periods of time, because the degree of genetic variation in a subsample of non-passerines and passerines was significantly negatively related to heterogeneity in distribution. Heterogeneously distributed passerine species were not more often habitat specialists than homogeneously distributed species. Furthermore, heterogeneously distributed passerine species had high annual adult survival rates but did not differ in annual fecundity from homogeneously distributed species. Heterogeneously distributed passerine species rarely colonized urban habitats. Finally, homogeneously distributed bird species were hosts to a greater diversity of blood parasite species than heterogeneously distributed species. In conclusion, small breeding ranges, population sizes, and population densities of heterogeneously distributed passerine bird species, combined with their low degree of genetic variability, and their inability to colonize urban areas may render such species particularly susceptible to human-influenced global climatic changes.     

Intertidal assemblages on artificial and natural habitats in marinas on the north-west coast of Italy

Following the progressive expansion of human populations, the number of artificial habitats is increasing in shallow waters of urbanised coastal areas. The comparison of assemblages between natural and artificial habitats is necessary to determine whether there is real loss and fragmentation of natural habitats. This study investigates the changes in intertidal assemblages caused by marinas for tourists, along exposed rocky shores on the north-west coast of Italy. Marinas, being made of transplanted boulders and by internal wave-sheltered seawalls, introduce different types of artificial habitats in a relatively small area. Intertidal assemblages on breakwaters, seawalls and adjacent rocky shores were compared at three locations, thousands of metres apart. To assess the generality of patterns through time, natural and artificial habitats were sampled at three different times, over a period of about 2 years. Data were analysed by means of multivariate and univariate analyses to test the hypotheses that assemblages and abundances of single taxa differed among habitats, consistently among locations and times of sampling. Furthermore, the variability of assemblages at the scales of tens of centimetres and metres was compared among habitats. Assemblages on seawalls were largely distinct from those on rocky shores or breakwaters. Seawalls, which supported a smaller number of species than breakwaters and rocky shores, were dominated by encrusting algae and lacked common species such as Rissoella verrucosa and Patella rustica. The abundance of main-space occupiers did not differ between breakwaters and rocky shores, but there were differences in variability of assemblages at both the spatial scales investigated. This study provides evidence for differences between intertidal assemblages supported by artificial habitats at marinas and those on adjacent rocky shores. Differences in habitat-structure (and/or wave-exposure in the case of seawalls) could explain the occurrence of distinct intertidal assemblages. Despite the nature and magnitude of these differences, varied according to the type of artificial habitat considered, neither breakwaters nor seawalls could be considered surrogates of rocky shores.Communicated by R. Cattaneo-Vietti, Genova     

Multispecies genetic objectives in spatial conservation planning

Growing threats to biodiversity and global alteration of habitats and species distributions make it increasingly necessary to consider evolutionary patterns in conservation decision making. Yet, there is no clear‐cut guidance on how genetic features can be incorporated into conservation‐planning processes, despite multiple molecular markers and several genetic metrics for each marker type to choose from. Genetic patterns differ between species, but the potential tradeoffs among genetic objectives for multiple species in conservation planning are currently understudied. We compared spatial conservation prioritizations derived from 2 metrics of genetic diversity (nucleotide and haplotype diversity) and 2 metrics of genetic isolation (private haplotypes and local genetic differentiation) in mitochondrial DNA of 5 marine species. We compared outcomes of conservation plans based only on habitat representation with plans based on genetic data and habitat representation. Fewer priority areas were selected for conservation plans based solely on habitat representation than on plans that included habitat and genetic data. All 4 genetic metrics selected approximately similar conservation‐priority areas, which is likely a result of prioritizing genetic patterns across a genetically diverse array of species. Largely, our results suggest that multispecies genetic conservation objectives are vital to creating protected‐area networks that appropriately preserve community‐level evolutionary patterns.     

Bird‐community responses to habitat creation in a long‐term,large‐scale natural experiment

Ecosystem function and resilience are compromised when habitats become fragmented due to land‐use change. This has led to national and international conservation strategies aimed at restoring habitat extent and improving functional connectivity (i.e., maintaining dispersal processes). However, biodiversity responses to landscape‐scale habitat creation and the relative importance of spatial and temporal scales are poorly understood, and there is disagreement over which conservation strategies should be prioritized. We used 160 years of historic post‐agricultural woodland creation as a natural experiment to evaluate biodiversity responses to habitat creation in a landscape context. Birds were surveyed in 101 secondary, broadleaf woodlands aged 10–160 years with ≥80% canopy cover and in landscapes with 0‐17% broadleaf woodland cover within 3000 m. We used piecewise structural equation modeling to examine the direct and indirect relationships between bird abundance and diversity, ecological continuity, patch characteristics, and landscape structure and quantified the relative conservation value of local and landscape scales for bird communities. Ecological continuity indirectly affected overall bird abundance and species richness through its effects on stand structure, but had a weaker influence (effect size near 0) on the abundance and diversity of species most closely associated with woodland habitats. This was probably because woodlands were rapidly colonized by woodland generalists in ≤10 years (minimum patch age) but were on average too young (median 50 years) to be colonized by woodland specialists. Local patch characteristics were relatively more important than landscape characteristics for bird communities. Based on our results, biodiversity responses to habitat creation depended on local‐ and landscape‐scale factors that interacted across time and space. We suggest that there is a need for further studies that focus on habitat creation in a landscape context and that knowledge gained from studies of habitat fragmentation and loss should be used to inform habitat creation with caution because the outcomes are not necessarily reciprocal.     

Sensitivity of population viability to spatial and nonspatial parameters using GRIP.

Metapopulation dynamics are influenced by spatial parameters including the amount and arrangement of suitable habitat, yet these parameters may be uncertain when deciding how to manage species or their habitats. Sensitivity analyses of population viability analysis (PVA) models can help measure relative parameter influences on predictions, identify research priorities for reducing uncertainty, and evaluate management strategies. Few spatial PVAs, however, include sensitivity analyses of both spatial and nonspatial parameters, perhaps because computationally efficient tools for such analyses are lacking or inaccessible. We developed GRIP, a program to facilitate sensitivity analysis of spatial and nonspatial input parameters for PVAs created in RAMAS Metapop, a widely applied software program. GRIP creates random sets of input files by varying parameters specified in the PVA model including vital rates and their correlations among populations, the number and configuration of populations, dispersal rates, dispersal survival, initial population abundances, carrying capacities, and the probability, intensity, and spatial extent of catastrophes, while drawing on specified parameter distributions. We evaluated GRIP's performance as a tool for sensitivity analysis of spatial PVAs and explored the consequences of varying spatial input parameters for predictions of a published PVA model of the sand lizard (Lacerta agilis). We used GRIP output to generate standardized regression coefficients (SRCs) and nonparametric correlation coefficients as indices of the relative sensitivity of predicted conservation status to input parameters. GRIP performed well; with a single analysis we were able to rank the relative influence of input parameters identified as influential by the PVA's original author, S. A. Berglind, who used three separate forms of sensitivity analysis. Our analysis, however, also underscored the value of exploring the relative influence of spatial parameters on PVA predictions; both SRCs and correlation coefficients indicated that the most influential parameters in the sand lizard model were spatial in nature. We provide annotated code so that GRIP may be modified to reflect particular species biology, customized for more complex spatial PVA models, upgraded to incorporate features added in newer versions of RAMAS Metapop, used as a template to develop similar programs, or used as it is for computationally efficient sensitivity analyses in support of conservation planning.     

Multi-scale marine biodiversity patterns inferred efficiently from habitat image processing

Cost-effective proxies of biodiversity and species abundance, applicable across a range of spatial scales, are needed for setting conservation priorities and planning action. We outline a rapid, efficient, and low-cost measure of spectral signal from digital habitat images that, being an effective proxy for habitat complexity, correlates with species diversity and requires little image processing or interpretation. We validated this method for coral reefs of the Great Barrier Reef (GBR), Australia, across a range of spatial scales (1 m to 10 km), using digital photographs of benthic communities at the transect scale and high-resolution Landsat satellite images at the reef scale. We calculated an index of image-derived spatial heterogeneity, the mean information gain (MIG), for each scale and related it to univariate (species richness and total abundance summed across species) and multivariate (species abundance matrix) measures of fish community structure, using two techniques that account for the hierarchical structure of the data: hierarchical (mixed-effect) linear models and distance-based partial redundancy analysis. Over the length and breadth of the GBR, MIG alone explained up to 29% of deviance in fish species richness, 33% in total fish abundance, and 25% in fish community structure at multiple scales, thus demonstrating the possibility of easily and rapidly exploiting spatial information contained in digital images to complement existing methods for inferring diversity and abundance patterns among fish communities. Thus, the spectral signal of unprocessed remotely sensed images provides an efficient and low-cost way to optimize the design of surveys used in conservation planning. In data-sparse situations, this simple approach also offers a viable method for rapid assessment of potential local biodiversity, particularly where there is little local capacity in terms of skills or resources for mounting in-depth biodiversity surveys.     

How decisions about fitting species distribution models affect conservation outcomes

Species distribution models (SDMs) are increasingly used in conservation and land-use planning as inputs to describe biodiversity patterns. These models can be built in different ways, and decisions about data preparation, selection of predictor variables, model fitting, and evaluation all alter the resulting predictions. Commonly, the true distribution of species is unknown and independent data to verify which SDM variant to choose are lacking. Such model uncertainty is of concern to planners. We analyzed how 11 routine decisions about model complexity, predictors, bias treatment, and setting thresholds for predicted values altered conservation priority patterns across 25 species. Models were created with MaxEnt and run through Zonation to determine the priority rank of sites. Although all SDM variants performed well (area under the curve >0.7), they produced spatially different predictions for species and different conservation priority solutions. Priorities were most strongly altered by decisions to not address bias or to apply binary thresholds to predicted values; on average 40% and 35%, respectively, of all grid cells received an opposite priority ranking. Forcing high model complexity altered conservation solutions less than forcing simplicity (14% and 24% of cells with opposite rank values, respectively). Use of fewer species records to build models or choosing alternative bias treatments had intermediate effects (25% and 23%, respectively). Depending on modeling choices, priority areas overlapped as little as 10–20% with the baseline solution, affecting top and bottom priorities differently. Our results demonstrate the extent of model-based uncertainty and quantify the relative impacts of SDM building decisions. When it is uncertain what the best SDM approach and conservation plan is, solving uncertainty or considering alterative options is most important for those decisions that change plans the most.     

Life history traits predict relative abundance in an assemblage of forest caterpillars

Species in a given trophic level occur in vastly unequal abundance, a pattern commonly documented but poorly explained for most taxa. Theoretical predictions of species density such as those arising from the metabolic theory of ecology hold well at large spatial and temporal scales but are not supported in many communities sampled at a relatively small scale. At these scales ecological factors may be more important than the inherent limits to energy use set by allometric scaling of mass. These factors include the amount of resources available, and the ability of individuals to convert these resources successfully into population growth. While previous studies have demonstrated the limits of macroecological theory in explaining local abundance, few studies have tested alternative generalized mechanisms determining abundance at the community scale. Using an assemblage of forest moth species found co-occurring as caterpillars on a single host plant species, we tested whether species abundance on that plant could be explained by mass allometry, intrinsic population growth, diet breadth, or some combination of these traits. We parameterized life history traits of the caterpillars in association with the host plant in both field and laboratory settings, so that the population growth estimate was specific to the plant on which abundance was measured. Using a generalized least-squares regression method incorporating phylogenetic relatedness, we found no relationship between abundance and mass but found that abundance was best explained by both intrinsic population growth rate and diet breadth. Species population growth potential was most affected by survivorship and larval development time on the host plant. Metabolic constraints may determine upper limits to local abundance levels for species, but local community abundance is strongly predicted by the potential for population increase and the resources available to that species in the environment.     

Mapping shifts in spatial synchrony in grassland birds to inform conservation planning

Spatial synchrony, defined as the correlated fluctuations in abundance of spatially separated populations, can be caused by regional fluctuations in natural and anthropogenic environmental population drivers. Investigations into the geography of synchrony can provide useful insight to inform conservation planning efforts by revealing regions of common population drivers and metapopulation extinction vulnerability. We examined the geography of spatial synchrony and decadal changes in these patterns for grassland birds in the United States and Canada, which are experiencing widespread and persistent population declines. We used Bayesian hierarchical models and over 50 years of abundance data from the North American Breeding Bird Survey to generate population indices within a 2° latitude by 2° longitude grid. We computed and mapped mean local spatial synchrony for each cell (mean detrended correlation of the index among neighboring cells), along with associated uncertainty, for 19 species in 2, 26-year periods, 1968–1993 and 1994–2019. Grassland birds were predicted to increase in spatial synchrony where agricultural intensification, climate change, or interactions between the 2 increased. We found no evidence of an overall increase in synchrony among grassland bird species. However, based on the geography of these changes, there was considerable spatial heterogeneity within species. Averaging across species, we identified clusters of increasing spatial synchrony in the Prairie Pothole and Shortgrass Prairie regions and a region of decreasing spatial synchrony in the eastern United States. Our approach has the potential to inform continental-scale conservation planning by adding an additional layer of relevant information to species status assessments and spatial prioritization of policy and management actions. Our work adds to a growing literature suggesting that global change may result in shifting patterns of spatial synchrony in population dynamics across taxa with broad implications for biodiversity conservation.