Salish Sea Stream Discharge Diagram

Major rivers of the Salish Sea and average stream discharge (cubic meters per second). Data are based on annual averages from 1981 to 2010. Figure 2.3 in th

Salish Sea Bioregion Reference Map

Map of the Salish Sea, major waterways, and surrounding watersheds, which when combined form a distinct transboundary bioregion. Figure 1.1 in th

Three Centuries of Synchronous Forest Defoliator Outbreaks in Western North America

Insect outbreaks often occur synchronously across large spatial scales, but the long-term temporal stability of the phenomenon and the mechanisms behind it are not well understood. In this study, I use a widespread lepidopteran defoliator native to western North America--the western spruce budworm--as a case study to explore patterns of and potential causes for synchronous population fluctuations. Analyses of synchrony are typically severely limited by the short historical records available for many species. To overcome this limitation, I compiled multi-century dendrochronological reconstructions of western spruce budworm outbreaks from across much of the species\u27 range. This allowed me to analyze synchrony at a sub-continental spatial scale over the last three centuries. I found statistically significant synchrony among regional outbreak records up to 2,000 km apart and identified numerous outbreak periods that occurred synchronously across much of the species\u27 range. I quantified spatial and temporal associations between climate and synchronous outbreak periods using paleoclimate reconstructions. The spatial patterns of outbreak histories and climate records were remarkably similar, with higher similarity in outbreak histories apparent between regions with more similar climate conditions. Synchronous outbreaks typically occurred during periods of average or above average moisture availability preceded by periods of low moisture availability. My results suggest that climatic variability has played a key role in synchronizing western spruce budworm population fluctuations in disjunct forests across western North America for at least the last three centuries. Widespread synchrony appears to be a natural part of this species\u27 population dynamics, though synchronous outbreaks have occurred more frequently during the 20th century than during prior centuries. This study uses a novel combination of statistical methods and dendrochronological data to provide analyses of this species\u27 population dynamics with an unprecedented combination of spatial extent and temporal depth

Salish Sea Population Density

Human population density in the Salish Sea. People per square kilometer mapped for each census block. Data from 2010 in the US and 2011 in Canada. Figure 3.1 in th

Salish Sea Jurisdictions

US Counties, Canadian Regional Districts, and major cities in the Salish Sea Bioregion. Figure 1.3 in th

Salish Sea Circulation Diagram

. Direction and relative magnitude (line width) of net water flow in the Salish Sea. Deep water flows represent primarily marine waters entering the Salish Sea from the Pacific Ocean. Intermediate depth and surface flows represent a mix of marine waters and freshwater from rivers in the Salish Sea. Actual circulation patterns are highly complex and seasonally variable, this diagram shows a simplified model of net exchanges. Labels indicate percent of the total water exchange that moves in and out of the Salish Sea through the Strait of Juan de Fuca in the south and through the northern boundary of the Strait of Georgia. Figure 2.6 in th

Salish Sea Land Cover

Land cover in the Salish Sea bioregion. Land cover categories modeled using 30x30 meter resolution gridded satellite data from 2015. Figure 3.2 in th

Marine Basins

Subbasins and bathymetry of the Salish Sea. Basins are delineated based on water depth and circulation. Shallower areas associated with underwater sills separate many of the basins, creating distinct oceanography. Figure 2.5 in th

Why Georeferencing Matters: Introducing a Practical Protocol to Prepare Species Occurrence Records for Spatial Analysis

Species Distribution Models (SDMs) are widely used to understand environmental controls on species’ ranges and to forecast species range shifts in response to climatic changes. The quality of input data is crucial determinant of the model’s accuracy. While museum records can be useful sources of presence data for many species, they do not always include accurate geographic coordinates. Therefore, actual locations must be verified through the process of georeferencing. We present a practical, standardized manual georeferencing method (the Spatial Analysis Georeferencing Accuracy (SAGA) protocol) to classify the spatial resolution of museum records specifically for building improved SDMs. We used the high-elevation plant Saxifraga austromontana Wiegand (Saxifragaceae) as a case study to test the effect of using this protocol when developing an SDM. In MAXENT, we generated and compared SDMs using a comprehensive occurrence dataset that had undergone three different levels of georeferencing: (1) trained using all publicly available herbarium records of the species, minus outliers (2) trained using herbarium records claimed to be previously georeferenced, and (3) trained using herbarium records that we have manually georeferenced to a ≤ 1-km resolution using the SAGA protocol. Model predictions of suitable habitat for S. austromontana differed greatly depending on georeferencing level. The SDMs fitted with presence locations georeferenced using SAGA outperformed all others. Differences among models were exacerbated for future distribution predictions. Under rapid climate change, accurately forecasting the response of species becomes increasingly important. Failure to georeference location data and cull inaccurate samples leads to erroneous model output, limiting the utility of spatial analyses. We present a simple, standardized georeferencing method to be adopted by curators, ecologists, and modelers to improve the geographic accuracy of museum records and SDM predictions