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Although trait information has been widely used to explore underlying mechanisms of forest community structure, most studies have focused on local patterns of phylogenetic or functional alpha diversity. Investigations of functional beta diversity, on the other hand, have not been conducted at local scales in a spatially explicit way. In this study, we provide a powerful methodology based on recent advances in spatial point pattern analysis using fully mapped data of large and small trees in two large temperate forest plots. This approach allowed us to assess the relative importance of different ecological processes and mechanisms for explaining patterns of local phylogenetic and functional beta diversity. For both forests and size classes, we found a clear hierarchy of scales: habitat filtering accounted for patterns of phylogenetic and functional beta diversity at larger distances (150-250 m), dispersal limitation accounted for the observed decline in beta diversity at distances below 150 m, and species interactions explained small departures from functional and phylogenetic beta diversity at the immediate plant-neighborhood scale (below 20 m). Thus, both habitat filtering and dispersal limitation influenced the observed patterns in phylogenetic and functional beta diversity at local scales. This result contrasts with a previous study from the same forests, where dispersal limitation alone approximated the observed species beta diversity for distances up to 250 m. In addition, species interactions were relatively unimportant for predicting phylogenetic and functional beta diversity. Our analysis suggests that phylogenetic and functional beta diversity can provide insights into the mechanisms of local community assembly that are missed by studies focusing exclusively on species beta diversity.

Countless wetlands have been lost and degraded globally, making amphibians the most threatened vertebrate class. However, despite facing extensive threats and stressors, coastal wetlands of the Laurentian Great Lakes of North America (lakes Superior, Michigan, Huron, Erie, and Ontario) still support sizable populations of frogs (order Anura, including toads). We used data from the Great Lakes Coastal Wetland Monitoring Program to quantify the first‐ever annual occurrence probabilities and trends (2011–2023) of eight marsh‐breeding frog species, or groups of species, at 1550 point count locations in 747 coastal wetlands throughout the Great Lakes, and to assess 11 potential drivers of occurrence. Sampled wetlands were marshes greater than 4 ha in area with a permanent or periodic surface‐water connection to an adjacent Great Lake or their connecting river systems. Across our study area, green frog (Lithobates clamitans) occurrence increased by 8% per year, whereas chorus frog (Pseudacris maculata, Pseudacris triseriata) occurrence decreased by 14% per year. We found more positive or stable trends in occurrence among lakes and species (85%) than negative trends (15%). Occurrence of all species was negatively associated with one or two indicators of poor water quality: specific conductance, ammonium nitrogen, nitrate nitrogen, and urban and agricultural land cover in the surrounding watershed (median area: 12 km2). Occurrence of multiple species was positively associated with high lake levels and surrounding wetland (<250 m) and forest (<2.5 km) land cover and negatively associated with surrounding road density (<2.5 km). Even though occurrence of most species was increasing or stable and was relatively high (>50%), all will likely benefit from conservation actions because 50%–90% of Great Lakes coastal wetlands have been lost and converted to anthropogenic land uses, leaving frog populations at a fraction of their former, original sizes. Therefore, extra precaution is critical to help ensure their growth and persistence. Improving water quality, increasing natural forest and wetland land cover within 2.5 km, and reducing roads within 2.5 km of Great Lakes coastal wetlands will help conserve these important indicator species in this globally recognized but imperiled ecosystem.

Species often exhibit regionally specific habitat associations, so habitat association models developed in one region might not be accurate or even appropriate for other regions. Three programs to survey wetland‐breeding birds covering (respectively) Great Lakes coastal wetlands, inland Great Lakes wetlands, and the Prairie Pothole Region offer an opportunity to test whether regionally specific models of habitat use by wetland‐obligate breeding birds are transferrable across regions. We first developed independent, regional population density models for four species of wetland‐obligate birds: Pied‐billed Grebe (Podilymbus podiceps), Virginia Rail (Rallus limicola), Sora (Porzana carolina), and American Bittern (Botaurus lentiginosus). We then used adjusted pseudo‐R2 values to compare the amount of variation explained by each model when applied to data collected in each of the three regions. Although certain habitat characteristics, such as emergent vegetation and wetland area, were consistently important across regions, models for each species differed by region—both in variables selected for inclusion and often in the directionality of relationships for common variables—indicating that habitat associations for these species are regionally specific. When we applied a model developed in one region to data collected in another region, we found that explanatory power was reduced in most (71%) models. Therefore, we suggest that ecological analyses should emphasize regionally specific habitat association models whenever possible. Nonetheless, models created from inland Great Lakes wetland data had higher median explanatory power when applied to other regions, and the amount of explanatory power lost by other transferred models was relatively small. Thus, while regionally specific habitat association models are preferable, in the absence of reliable regional data, habitat association models developed in one region may be applied to another region, but the results need to be cautiously interpreted. Additionally, we found that median explanatory power was higher when local‐scale habitat characteristics were included in the models, indicating that regionally specific models should ideally be based on a combination of local‐ and landscape‐scale habitat characteristics. Conservation practitioners can leverage such regionally specific models and associated monitoring data to help prioritize areas for management activities that contribute to regional conservation efforts.

Numerous studies have shown reduced performance in plants that are surrounded by neighbours of the same species 1 , 2 , a phenomenon known as conspecific negative density dependence (CNDD) 3 . A long-held ecological hypothesis posits that CNDD is more pronounced in tropical than in temperate forests 4 , 5 , which increases community stabilization, species coexistence and the diversity of local tree species 6 , 7 . Previous analyses supporting such a latitudinal gradient in CNDD 8 , 9 have suffered from methodological limitations related to the use of static data 10 – 12 . Here we present a comprehensive assessment of latitudinal CNDD patterns using dynamic mortality data to estimate species-site-specific CNDD across 23 sites. Averaged across species, we found that stabilizing CNDD was present at all except one site, but that average stabilizing CNDD was not stronger toward the tropics. However, in tropical tree communities, rare and intermediate abundant species experienced stronger stabilizing CNDD than did common species. This pattern was absent in temperate forests, which suggests that CNDD influences species abundances more strongly in tropical forests than it does in temperate ones 13 . We also found that interspecific variation in CNDD, which might attenuate its stabilizing effect on species diversity 14 , 15 , was high but not significantly different across latitudes. Although the consequences of these patterns for latitudinal diversity gradients are difficult to evaluate, we speculate that a more effective regulation of population abundances could translate into greater stabilization of tropical tree communities and thus contribute to the high local diversity of tropical forests. An analysis of tree survival data from forest sites worldwide shows that in the tropics, rare tree species experience stronger stabilizing density dependence than common species, wheras no correlation of stabilizing density dependence and abundance exists in the temperate zone.

Since European settlement, over 50 % of coastal wetlands have been lost in the Laurentian Great Lakes basin, causing growing concern and increased monitoring by government agencies. For over a decade, monitoring efforts have focused on the development of regional and organism-specific measures. To facilitate collaboration and information sharing between public, private, and government agencies throughout the Great Lakes basin, we developed standardized methods and indicators used for assessing wetland condition. Using an ecosystem approach and a stratified random site selection process, birds, anurans, fish, macroinvertebrates, vegetation, and physico-chemical conditions were sampled in coastal wetlands of all five Great Lakes including sites from the United States and Canada. Our primary objective was to implement a standardized basin-wide coastal wetland monitoring program that would be a powerful tool to inform decision-makers on coastal wetland conservation and restoration priorities throughout the Great Lakes basin.

Ecology cannot yet fully explain why so many tree species coexist in natural communities such as tropical forests. A major difficulty is linking individual-level processes to community dynamics. We propose a combination of tree spatial data, spatial statistics and dynamical theory to reveal the relationship between spatial patterns and population-level interaction coefficients and their consequences for multispecies dynamics and coexistence. Here we show that the emerging population-level interaction coefficients have, for a broad range of circumstances, a simpler structure than their individual-level counterparts, which allows for an analytical treatment of equilibrium and stability conditions. Mechanisms such as animal seed dispersal, which result in clustering of recruits that is decoupled from parent locations, lead to a rare-species advantage and coexistence of otherwise neutral competitors. Linking spatial statistics with theories of community dynamics offers new avenues for explaining species coexistence and calls for rethinking community ecology through a spatial lens. Tree spatial data, spatial statistics and dynamical theory reveal the relationship between spatial patterns and population-level interaction coefficients and their consequences for multispecies dynamics and coexistence.

ContextResource movements across ecosystem boundaries are important determinants of the diversity and abundance of organisms in the donor and recipient ecosystem. However the effects of cross-ecosystem movements of materials at broader spatial extents than a typical field study are not well understood.ObjectivesWe tested the hypotheses that (1) variation in abundance of 57 forest songbird species within four foraging guilds is explained by modeled emergent aquatic insect biomass inputs from adjacent lakes and streams and (2) the degree of association varies across foraging guilds and species within guilds. We also sought to determine the importance of emergent aquatic insects while accounting for variation in local forest cover and edge.MethodsWe spatially modeled the degree to which distribution and abundance of songbirds in different foraging guilds was explained by modeled emergent aquatic insect biomass. We used multilevel models to simultaneously estimate the responses of species in four different insectivorous guilds. Bird abundance was summarized from point counts conducted over 24 years at 317 points.ResultsAerial insectivores were more abundant in areas with high estimated emergent insect biomass inputs to land (regression coefficient 0.30, P < 0.05) but the overall abundance of gleaners, bark-probers, and ground-foragers was not explained by estimated emergent insect abundance. The coursing aerial insectivores had the strongest association with emergent insects followed by willow flycatcher, olive-sided flycatcher, and alder flycatcher.ConclusionsModeling cross-ecosystem movements of materials at broad spatial extents can effectively characterize the importance of this ecological process for aerial insectivorous songbirds.

Distributions of pond-breeding amphibians may be influenced by habitat factors at different spatial scales. We used anuran calling surveys to investigate the association between 5 anuran species and habitat variables measured within 100, 500, 1000, and 3000 m of sampling points at 63 coastal wetlands along the US shores of Lake Michigan and Lake Huron. Stepwise logistic regression was used to create predictive models for each species at each spatial scale. Our results confirm the view that habitat variables at multiple scales influence frog distributions, but the strength of predictive models was significantly affected by the spatial scale at which habitat variables were derived. Remotely sensed habitat variables within a 3000 m radius were among the most effective predictors of occurrence for American toad (Bufo americanus), eastern gray treefrog (Hyla versicolor), spring peeper (Pseudacris crucifer), and green frog (Rana clamitans melanota). The western chorus frog (Pseudacris triseriata) was predicted most effectively by variables derived within a 500 m radius. For the most part, these anurans exhibited species-specific responses to habitat variables; however the suite of landscape-scale variables associated with urban land use appeared in all species’ regression models. Associations with landscape-scale variables coupled with well-documented habitat needs at local breeding sites suggest that conservation and assessment of frogs and toads in coastal wetlands should consider the influence of habitat variables at multiple spatial scales.

Traditionally, ecosystem monitoring, conservation, and restoration have been conducted in a piecemeal manner at the local scale without regional landscape context. However, scientifically driven conservation and restoration decisions benefit greatly when they are based on regionally determined benchmarks and goals. Unfortunately, required data sets rarely exist for regionally important ecosystems. Because of early recognition of the extreme ecological importance of Laurentian Great Lakes coastal wetlands, and the extensive degradation that had already occurred, significant investments in coastal wetland research, protection, and restoration have been made in recent decades and continue today. Continued and refined assessment of wetland condition and trends, and the evaluation of restoration practices are all essential to ensuring the success of these investments. To provide wetland managers and decision makers throughout the Laurentian Great Lakes basin with the optimal tools and data needed to make scientifically-based decisions, our regional team of Great Lakes wetland scientists developed standardized methods and indicators used for assessing wetland condition. From a landscape perspective, at the Laurentian Great Lakes ecosystem scale, we established a stratified random-site-selection process to monitor birds, anurans, fish, macroinvertebrates, vegetation, and physicochemical conditions of coastal wetlands in the US and Canada. Monitoring of approximately 200 wetlands per year began in 2011 as the Great Lakes Coastal Wetland Monitoring Program. In this paper, we describe the development, delivery, and expected results of this ongoing international, multi-disciplinary, multi-stakeholder, landscape-scale monitoring program as a case example of successful application of landscape conservation design.

Aim The relationship between the proportion of sites occupied by a species and the area of a site [occupancy–area relationship (OAR)] offers key information for biodiversity management and has long fascinated ecologists. We quantified the variation in OAR for 3,157 woody species in 17 forest plots worldwide and tested the relative importance of environment and species traits for explaining this variation and evaluated overall model predictive ability. Location Global. Time period Early 21st century. Major taxa studied Woody plants. Methods We used mixed‐effect regression to examine the observed shape of the OAR (its “slope”) against species‐specific and plot‐wide predictors: coarse‐grain occupancy, tree size, plot species richness, energy availability and topographic complexity. Results We found large variation in OAR slopes, and the variation was strongest among species within plots. The OAR slopes showed a latitudinal trend and were steeper near the equator. As predicted, coarse‐grain occupancy and tree size negatively affected OAR slopes, whereas species richness had a positive effect and explained most of the variance between plots. Although hypothesized directionalities were broadly confirmed, traits and environment had relatively limited overall predictive power. Main conclusions These results document the variation of the OAR for 3,157 species at near‐global extent. We found a latitudinal gradient in OAR slopes and confirmed key hypothesized predictors. But at this global extent and over the large set of species analysed, the remaining unexplained variation in OAR slopes was substantial. Nevertheless, this large‐scale empirical analysis of the OAR offers an initial step towards a more general use of OARs for the fine‐scale prediction of species distributions and abundance.