Topographic and vegetation drivers of thermal heterogeneity along the boreal-grassland transition zone in western Canada: Implications for climate change refugia.

Climate change refugia are areas that are relatively buffered from contemporary climate change and may be important safe havens for wildlife and plants under anthropogenic climate change. Topographic variation is an important driver of thermal heterogeneity, but it is limited in relatively flat landscapes, such as the boreal plain and prairie regions of western Canada. Topographic variation within this region is mostly restricted to river valleys and hill systems, and their effects on local climates are not well documented. We sought to quantify thermal heterogeneity as a function of topography and vegetation cover within major valleys and hill systems across the boreal-grassland transition zone. Using iButton data loggers, we monitored local temperature at four hills and 12 river valley systems that comprised a wide range of habitats and ecosystems in Alberta, Canada (N = 240), between 2014 and 2020. We then modeled monthly temperature by season as a function of topography and different vegetation cover types using general linear mixed effect models. Summer maximum temperatures (T max) varied nearly 6°C across the elevation gradient sampled. Local summer mean (T mean) and maximum (T max) temperatures on steep, north-facing slopes (i.e., low levels of potential solar radiation) were up to 0.70°C and 2.90°C cooler than highly exposed areas, respectively. T max in incised valleys was between 0.26 and 0.28°C cooler than other landforms, whereas areas with greater terrain roughness experienced maximum temperatures that were up to 1.62°C cooler. We also found that forest cover buffered temperatures locally, with coniferous and mixedwood forests decreasing summer T mean from 0.23 to 0.72°C and increasing winter T min by up to 2°C, relative to non-forested areas. Spatial predictions of temperatures from iButton data loggers were similar to a gridded climate product (ClimateNA), but the difference between them increased with potential solar radiation, vegetation cover, and terrain roughness. Species that can track their climate niche may be able to compensate for regional climate warming through local migrations to cooler microsites. Topographic and vegetation characteristics that are related to cooler local climates should be considered in the evaluation of future climate change impacts and to identify potential refugia from climate change.

Climate-change refugia: biodiversity in the slow lane.

Climate-change adaptation focuses on conducting and translating research to minimize the dire impacts of anthropogenic climate change, including threats to biodiversity and human welfare. One adaptation strategy is to focus conservation on climate-change refugia (that is, areas relatively buffered from contemporary climate change over time that enable persistence of valued physical, ecological, and sociocultural resources). In this Special Issue, recent methodological and conceptual advances in refugia science will be highlighted. Advances in this emerging subdiscipline are improving scientific understanding and conservation in the face of climate change by considering scale and ecosystem dynamics, and looking beyond climate exposure to sensitivity and adaptive capacity. We propose considering refugia in the context of a multifaceted, long-term, network-based approach, as temporal and spatial gradients of ecological persistence that can act as "slow lanes" rather than areas of stasis. After years of discussion confined primarily to the scientific literature, researchers and resource managers are now working together to put refugia conservation into practice.

Phylogeography of a migratory songbird across its Canadian breeding range: Implications for conservation units.

The objectives of this study were to describe and evaluate potential drivers of genetic structure in Canadian breeding populations of the Ovenbird, Seiurus aurocapilla. We performed genetic analyses on feather samples of individuals from six study sites using nuclear microsatellites. We also assessed species identity and population genetic structure of quill mites (Acariformes, Syringophilidae). For male Ovenbirds breeding in three study sites, we collected light-level geolocator data to document migratory paths and identify the wintering grounds. We also generated paleohindcast projections from bioclimatic models of Ovenbird distribution to identify potential refugia during the last glacial maximum (LGM, 21,000 years before present) as a factor explaining population genetic structure. Birds breeding in the Cypress Hills (Alberta/Saskatchewan) may be considered a distinct genetic unit, but there was no evidence for genetic differentiation among any other populations. We found relatively strong migratory connectivity in both western and eastern populations, but some evidence of mixing among populations on the wintering grounds. There was also little genetic variation among syringophilid mites from the different Ovenbird populations. These results are consistent with paleohindcast distribution predictions derived from two different global climate models indicating a continuous single LGM refugium, with the possibility of two refugia. Our results suggest that Ovenbird populations breeding in boreal and hemiboreal regions are panmictic, whereas the population breeding in Cypress Hills should be considered a distinct management unit.

Scale-dependent complementarity of climatic velocity and environmental diversity for identifying priority areas for conservation under climate change.

As most regions of the earth transition to altered climatic conditions, new methods are needed to identify refugia and other areas whose conservation would facilitate persistence of biodiversity under climate change. We compared several common approaches to conservation planning focused on climate resilience over a broad range of ecological settings across North America and evaluated how commonalities in the priority areas identified by different methods varied with regional context and spatial scale. Our results indicate that priority areas based on different environmental diversity metrics differed substantially from each other and from priorities based on spatiotemporal metrics such as climatic velocity. Refugia identified by diversity or velocity metrics were not strongly associated with the current protected area system, suggesting the need for additional conservation measures including protection of refugia. Despite the inherent uncertainties in predicting future climate, we found that variation among climatic velocities derived from different general circulation models and emissions pathways was less than the variation among the suite of environmental diversity metrics. To address uncertainty created by this variation, planners can combine priorities identified by alternative metrics at a single resolution and downweight areas of high variation between metrics. Alternately, coarse-resolution velocity metrics can be combined with fine-resolution diversity metrics in order to leverage the respective strengths of the two groups of metrics as tools for identification of potential macro- and microrefugia that in combination maximize both transient and long-term resilience to climate change. Planners should compare and integrate approaches that span a range of model complexity and spatial scale to match the range of ecological and physical processes influencing persistence of biodiversity and identify a conservation network resilient to threats operating at multiple scales.

Modeling tidal marsh distribution with sea-level rise: evaluating the role of vegetation, sediment, and upland habitat in marsh resiliency.

Tidal marshes maintain elevation relative to sea level through accumulation of mineral and organic matter, yet this dynamic accumulation feedback mechanism has not been modeled widely in the context of accelerated sea-level rise. Uncertainties exist about tidal marsh resiliency to accelerated sea-level rise, reduced sediment supply, reduced plant productivity under increased inundation, and limited upland habitat for marsh migration. We examined marsh resiliency under these uncertainties using the Marsh Equilibrium Model, a mechanistic, elevation-based soil cohort model, using a rich data set of plant productivity and physical properties from sites across the estuarine salinity gradient. Four tidal marshes were chosen along this gradient: two islands and two with adjacent uplands. Varying century sea-level rise (52, 100, 165, 180 cm) and suspended sediment concentrations (100%, 50%, and 25% of current concentrations), we simulated marsh accretion across vegetated elevations for 100 years, applying the results to high spatial resolution digital elevation models to quantify potential changes in marsh distributions. At low rates of sea-level rise and mid-high sediment concentrations, all marshes maintained vegetated elevations indicative of mid/high marsh habitat. With century sea-level rise at 100 and 165 cm, marshes shifted to low marsh elevations; mid/high marsh elevations were found only in former uplands. At the highest century sea-level rise and lowest sediment concentrations, the island marshes became dominated by mudflat elevations. Under the same sediment concentrations, low salinity brackish marshes containing highly productive vegetation had slower elevation loss compared to more saline sites with lower productivity. A similar trend was documented when comparing against a marsh accretion model that did not model vegetation feedbacks. Elevation predictions using the Marsh Equilibrium Model highlight the importance of including vegetation responses to sea-level rise. These results also emphasize the importance of adjacent uplands for long-term marsh survival and incorporating such areas in conservation planning efforts.

Separating the effects of environment and space on tree species distribution: from population to community.

Quantifying the relative contributions of environmental conditions and spatial factors to species distribution can help improve our understanding of the processes that drive diversity patterns. In this study, based on tree inventory, topography and soil data from a 20-ha stem-mapped permanent forest plot in Guangdong Province, China, we evaluated the influence of different ecological processes at different spatial scales using canonical redundancy analysis (RDA) at the community level and multiple linear regression at the species level. At the community level, the proportion of explained variation in species distribution increased with grid-cell sizes, primarily due to a monotonic increase in the explanatory power of environmental variables. At the species level, neither environmental nor spatial factors were important determinants of overstory species' distributions at small cell sizes. However, purely spatial variables explained most of the variation in the distributions of understory species at fine and intermediate cell sizes. Midstory species showed patterns that were intermediate between those of overstory and understory species. At the 20-m cell size, the influence of spatial factors was stronger for more dispersal-limited species, suggesting that much of the spatial structuring in this community can be explained by dispersal limitation. Comparing environmental factors, soil variables had higher explanatory power than did topography for species distribution. However, both topographic and edaphic variables were highly spatial structured. Our results suggested that dispersal limitation has an important influence on fine-intermediate scale (from several to tens of meters) species distribution, while environmental variability facilitates species distribution at intermediate (from ten to tens of meters) and broad (from tens to hundreds of meters) scales.

Evaluating tidal marsh sustainability in the face of sea-level rise: a hybrid modeling approach applied to San Francisco Bay.

BACKGROUND: Tidal marshes will be threatened by increasing rates of sea-level rise (SLR) over the next century. Managers seek guidance on whether existing and restored marshes will be resilient under a range of potential future conditions, and on prioritizing marsh restoration and conservation activities. METHODOLOGY: Building upon established models, we developed a hybrid approach that involves a mechanistic treatment of marsh accretion dynamics and incorporates spatial variation at a scale relevant for conservation and restoration decision-making. We applied this model to San Francisco Bay, using best-available elevation data and estimates of sediment supply and organic matter accumulation developed for 15 Bay subregions. Accretion models were run over 100 years for 70 combinations of starting elevation, mineral sediment, organic matter, and SLR assumptions. Results were applied spatially to evaluate eight Bay-wide climate change scenarios. PRINCIPAL FINDINGS: Model results indicated that under a high rate of SLR (1.65 m/century), short-term restoration of diked subtidal baylands to mid marsh elevations (-0.2 m MHHW) could be achieved over the next century with sediment concentrations greater than 200 mg/L. However, suspended sediment concentrations greater than 300 mg/L would be required for 100-year mid marsh sustainability (i.e., no elevation loss). Organic matter accumulation had minimal impacts on this threshold. Bay-wide projections of marsh habitat area varied substantially, depending primarily on SLR and sediment assumptions. Across all scenarios, however, the model projected a shift in the mix of intertidal habitats, with a loss of high marsh and gains in low marsh and mudflats. CONCLUSIONS/SIGNIFICANCE: Results suggest a bleak prognosis for long-term natural tidal marsh sustainability under a high-SLR scenario. To minimize marsh loss, we recommend conserving adjacent uplands for marsh migration, redistributing dredged sediment to raise elevations, and concentrating restoration efforts in sediment-rich areas. To assist land managers, we developed a web-based decision support tool (www.prbo.org/sfbayslr).

Where the wild things are: predicting hotspots of seabird aggregations in the California Current System.

Marine protected areas (MPAs) provide an important tool for conservation of marine ecosystems. To be most effective, these areas should be strategically located in a manner that supports ecosystem function. To inform marine spatial planning and support strategic establishment of MPAs within the California Current System, we identified areas predicted to support multispecies aggregations of seabirds ("hotspots"). We developed habitat-association models for 16 species using information from at-sea observations collected over an 11-year period (1997-2008), bathymetric data, and remotely sensed oceanographic data for an area from north of Vancouver Island, Canada, to the USA/Mexico border and seaward 600 km from the coast. This approach enabled us to predict distribution and abundance of seabirds even in areas of few or no surveys. We developed single-species predictive models using a machine-learning algorithm: bagged decision trees. Single-species predictions were then combined to identify potential hotspots of seabird aggregation, using three criteria: (1) overall abundance among species, (2) importance of specific areas ("core areas") to individual species, and (3) predicted persistence of hotspots across years. Model predictions were applied to the entire California Current for four seasons (represented by February, May, July, and October) in each of 11 years. Overall, bathymetric variables were often important predictive variables, whereas oceanographic variables derived from remotely sensed data were generally less important. Predicted hotspots often aligned with currently protected areas (e.g., National Marine Sanctuaries), but we also identified potential hotspots in Northern California/Southern Oregon (from Cape Mendocino to Heceta Bank), Southern California (adjacent to the Channel Islands), and adjacent to Vancouver Island, British Columbia, that are not currently included in protected areas. Prioritization and identification of multispecies hotspots will depend on which group of species is of highest management priority. Modeling hotspots at a broad spatial scale can contribute to MPA site selection, particularly if complemented by fine-scale information for focal areas.

Niches, models, and climate change: assessing the assumptions and uncertainties.

As the rate and magnitude of climate change accelerate, understanding the consequences becomes increasingly important. Species distribution models (SDMs) based on current ecological niche constraints are used to project future species distributions. These models contain assumptions that add to the uncertainty in model projections stemming from the structure of the models, the algorithms used to translate niche associations into distributional probabilities, the quality and quantity of data, and mismatches between the scales of modeling and data. We illustrate the application of SDMs using two climate models and two distributional algorithms, together with information on distributional shifts in vegetation types, to project fine-scale future distributions of 60 California landbird species. Most species are projected to decrease in distribution by 2070. Changes in total species richness vary over the state, with large losses of species in some "hotspots" of vulnerability. Differences in distributional shifts among species will change species co-occurrences, creating spatial variation in similarities between current and future assemblages. We use these analyses to consider how assumptions can be addressed and uncertainties reduced. SDMs can provide a useful way to incorporate future conditions into conservation and management practices and decisions, but the uncertainties of model projections must be balanced with the risks of taking the wrong actions or the costs of inaction. Doing this will require that the sources and magnitudes of uncertainty are documented, and that conservationists and resource managers be willing to act despite the uncertainties. The alternative, of ignoring the future, is not an option.

Re-shuffling of species with climate disruption: a no-analog future for California birds?

By facilitating independent shifts in species' distributions, climate disruption may result in the rapid development of novel species assemblages that challenge the capacity of species to co-exist and adapt. We used a multivariate approach borrowed from paleoecology to quantify the potential change in California terrestrial breeding bird communities based on current and future species-distribution models for 60 focal species. Projections of future no-analog communities based on two climate models and two species-distribution-model algorithms indicate that by 2070 over half of California could be occupied by novel assemblages of bird species, implying the potential for dramatic community reshuffling and altered patterns of species interactions. The expected percentage of no-analog bird communities was dependent on the community scale examined, but consistent geographic patterns indicated several locations that are particularly likely to host novel bird communities in the future. These no-analog areas did not always coincide with areas of greatest projected species turnover. Efforts to conserve and manage biodiversity could be substantially improved by considering not just future changes in the distribution of individual species, but including the potential for unprecedented changes in community composition and unanticipated consequences of novel species assemblages.