Forecasting species distributions : correlation does not equal causation

This research was funded by the U.S. Department of the Interior Northeast Climate Adaptation Science Center, which is managed by the U.S. Geological Survey National Climate Adaptation Science Center. Additional funding was provided by T-2- 3R grants for Nongame Species Monitoring and Management through the New Hampshire Fish and Game Department and E-1- 25 grants for Investigations and Population Recovery through the Vermont Fish and Wildlife Department.Aim Identifying the mechanisms influencing species' distributions is critical for accurate climate change forecasts. However, current approaches are limited by correlative models that cannot distinguish between direct and indirect effects. Location New Hampshire and Vermont, USA. Methods Using causal and correlational models and new theory on range limits, we compared current (2014?2019) and future (2080s) distributions of ecologically important mammalian carnivores and competitors along range limits in the northeastern US under two global climate models (GCMs) and a high-emission scenario (RCP8.5) of projected snow and forest biomass change. Results Our hypothesis that causal models of climate-mediated competition would result in different distribution predictions than correlational models, both in the current and future periods, was well-supported by our results; however, these patterns were prominent only for species pairs that exhibited strong interactions. The causal model predicted the current distribution of Canada lynx (Lynx canadensis) more accurately, likely because it incorporated the influence of competitive interactions mediated by snow with the closely related bobcat (Lynx rufus). Both modeling frameworks predicted an overall decline in lynx occurrence in the central high-elevation regions and increased occurrence in the northeastern region in the 2080s due to changes in land use that provided optimal habitat. However, these losses and gains were less substantial in the causal model due to the inclusion of an indirect buffering effect of snow on lynx. Main conclusions Our comparative analysis indicates that a causal framework, steeped in ecological theory, can be used to generate spatially explicit predictions of species distributions. This approach can be used to disentangle correlated predictors that have previously hampered understanding of range limits and species' response to climate change.Publisher PDFPeer reviewe

Daily Patterns of River Herring (\u3cem\u3eAlosa\u3c/em\u3e spp.) Spawning Migrations: Environmental Drivers and Variation among Coastal Streams in Massachusetts

The timing of life history events in many plants and animals depends on the seasonal fluctuations of specific environmental conditions. Climate change is altering environmental regimes and disrupting natural cycles and patterns across communities. Anadromous fishes that migrate between marine and freshwater habitats to spawn are particularly sensitive to shifting environmental conditions and thus are vulnerable to the effects of climate change. However, for many anadromous fish species the specific environmental mechanisms driving migration and spawning patterns are not well understood. In this study, we investigated the upstream spawning migrations of river herring Alosa spp. in 12 coastal Massachusetts streams. By analyzing long-term data sets (8–28 years) of daily fish counts, we determined the local influence of environmental factors on daily migration patterns and compared seasonal run dynamics and environmental regimes among streams. Our results suggest that water temperature was the most consistent predictor of both daily river herring presence–absence and abundance during migration. We found inconsistent effects of streamflow and lunar phase, likely due to the anthropogenic manipulation of flow and connectivity in different systems. Geographic patterns in run dynamics and thermal regimes suggest that the more northerly runs in this region are relatively vulnerable to climate change due to migration occurring later in the spring season, at warmer water temperatures that approach thermal maxima, and during a narrower temporal window compared to southern runs. The phenology of river herring and their reliance on seasonal temperature patterns indicate that populations of these species may benefit from management practices that reduce within-stream anthropogenic water temperature manipulations and maintain coolwater thermal refugia

A call to action for climate change research on Caribbean dry forests

The final publication is available at Springer via https://doi.org/10.1007/s10113-018-1334-6Tropical dry forest (TDF) is globally one of the most threatened forest types. In the insular Caribbean, limited land area and high population pressure have resulted in the loss of over 60% of TDF, yet local people’s reliance on these systems for ecosystem services is high. Given the sensitivity of TDF to shifts in precipitation regimes and the vulnerability of the Caribbean to climate change, this study examined what is currently known about the impacts of climate change on TDF in the region. A systematic review (n = 89) revealed that only two studies addressed the ecological response of TDF to climate change. Compared to the rapidly increasing knowledge of the effects of climate change on other Caribbean systems and on TDF in the wider neotropics, this paucity is alarming given the value of these forests. We stress the need for long-term monitoring of climate change responses of these critical ecosystems, including phenological and hotspot analyses as priorities

Dynamical downscaling of historical climate over CORDEX Central America domain with a regionally coupled atmosphere–ocean model

The climate in Mexico and Central America is influenced by the Pacific and the Atlantic oceanic basins and atmospheric conditions over continental North and South America. These factors and important ocean–atmosphere coupled processes make the region’s climate a great challenge for global and regional climate modeling. We explore the benefits that coupled regional climate models may introduce in the representation of the regional climate with a set of coupled and uncoupled simulations forced by reanalysis and global model data. Uncoupled simulations tend to stay close to the large-scale patterns of the driving fields, particularly over the ocean, while over land they are modified by the regional atmospheric model physics and the improved orography representation. The regional coupled model adds to the reanalysis forcing the air–sea interaction, which is also better resolved than in the global model. Simulated fields are modified over the ocean, improving the representation of the key regional structures such as the Intertropical Convergence Zone and the Caribbean Low Level Jet. Higher resolution leads to improvements over land and in regions of intense air–sea interaction, e.g., off the coast of California. The coupled downscaling improves the representation of the Mid Summer Drought and the meridional rainfall distribution in southernmost Central America. Over the regions of humid climate, the coupling corrects the wet bias of the uncoupled runs and alleviates the dry bias of the driving model, yielding a rainfall seasonal cycle similar to that in the reanalysis-driven experiments.Universidad de Costa Rca/[805-B7-507]/UCR/Costa RicaCRYOPERU/[144-2015]//PerúUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI

Large-scale climatic phenomena drive fluctuations in macroinvertebrate assemblages in lowland tropical streams, Costa Rica: The importance of ENSO events in determining long-term (15y) patterns

Understanding how environmental variables influence the distribution and density of organisms over relatively long temporal scales is a central question in ecology given increased climatic variability (e.g., precipitation, ENSO events). The primary goal of our study was to evaluate long-term (15y time span) patterns of climate, as well as environmental parameters in two Neotropical streams in lowland Costa Rica, to assess potential effects on aquatic macroinvertebrates. We also examined the relative effects of an 8y whole-stream P-enrichment experiment on macroinvertebrate assemblages against the backdrop of this long-term study. Climate, environmental variables and macroinvertebrate samples were measured monthly for 7y and then quarterly for an additional 8y in each stream. Temporal patterns in climatic and environmental variables showed high variability over time, without clear inter-annual or intra-annual patterns. Macroinvertebrate richness and abundance decreased with increasing discharge and was positively related to the number of days since the last high discharge event. Findings show that fluctuations in stream physicochemistry and macroinvertebrate assemblage structure are ultimately the result of large-scale climatic phenomena, such as ENSO events, while the 8y P-enrichment did not appear to affect macroinvertebrates. Our study demonstrates that Neotropical lowland streams are highly dynamic and not as stable as is commonly presumed, with high intra- and inter-annual variability in environmental parameters that change the structure and composition of freshwater macroinvertebrate assemblages.This study was financed by National Science Foundation (DEB 1122389) to Catherine M. Pringle. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Ciencias del Mar y Limnología (CIMAR

Consequences of Global Warming of 1.5 °C and 2 °C for Regional Temperature and Precipitation Changes in the Contiguous United States

<div><p>The differential warming of land and ocean leads to many continental regions in the Northern Hemisphere warming at rates higher than the global mean temperature. Adaptation and conservation efforts will, therefore, benefit from understanding regional consequences of limiting the global mean temperature increase to well below 2°C above pre-industrial levels, a limit agreed upon at the United Nations Climate Summit in Paris in December 2015. Here, we analyze climate model simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to determine the timing and magnitude of regional temperature and precipitation changes across the contiguous United States (US) for global warming of 1.5 and 2°C and highlight consensus and uncertainties in model projections and their implications for making decisions. The regional warming rates differ considerably across the contiguous US, but all regions are projected to reach 2°C about 10-20 years before the global mean temperature. Although there is uncertainty in the timing of exactly when the 1.5 and 2°C thresholds will be crossed regionally, over 80% of the models project at least 2°C warming by 2050 for all regions for the high emissions scenario. This threshold-based approach also highlights regional variations in the rate of warming across the US. The fastest warming region in the contiguous US is the Northeast, which is projected to warm by 3°C when global warming reaches 2°C. The signal-to-noise ratio calculations indicate that the regional warming estimates remain outside the envelope of uncertainty throughout the twenty-first century, making them potentially useful to planners. The regional precipitation projections for global warming of 1.5°C and 2°C are uncertain, but the eastern US is projected to experience wetter winters and the Great Plains and the Northwest US are projected to experience drier summers in the future. The impact of different scenarios on regional precipitation projections is negligible throughout the twenty-first century compared to uncertainties associated with internal variability and model diversity.</p></div