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ABSTRACT Lead (Pb) exposure in free‐flying bald eagles (Haliaeetus leucocephalus) is an important conservation concern. One of the challenges to characterizing the magnitude of Pb exposure in free‐flying bald eagles is obtaining samples. Although blood samples are the most commonly used biomarker to quantify Pb exposure in living animals, the potential for negative impacts resulting from handling bald eagles make blood sampling less than ideal in a large‐scale field study. We partnered with wildlife rehabilitators, who simultaneously collected blood and excrement samples from bald eagles admitted for rehabilitation in Iowa, USA, 2012 and 2013, to determine whether excrement could provide information comparable to blood about Pb exposure. We used linear regression to examine the relationship between excrement and blood Pb levels from 45 bald eagles admitted for rehabilitation and found that excrement Pb levels were statistically significantly related to blood Pb levels (P

The monarch butterfly (Danaus plexippus) is the focus of large-scale habitat restoration efforts because of recent population declines. From 2006-2017 we monitored monarchs at >400 sites throughout Iowa to link site occupancy and colonization/extinction dynamics to the presence of milkweed, site-specific habitat metrics, and landscape context at differing spatial scales. We used a robust design occupancy model in Program MARK and a hierarchical model selection approach to estimate site occupancy, extinction and colonization probabilities, and detection probability. Occupancy models revealed that monarchs responded differently to landscape features, environmental conditions, and local habitat conditions for site occupancy, extinction, and colonization probabilities. For site occupancy, the mean patch size of grassland at the 1-km spatial scale had a positive effect (βGrassPS1K = 0.94, SE = 0.54) while the percent of the landscape in woodland at the 200-m spatial scale had a negative effect (βWoodPL200 = −1.68, SE = 0.34). For extinction, there were additive effects of the percent of the landscape in woodland at the 100-m spatial scale (βWoodPLAND100 = 2.70, SE = 0.63), the interspersion of grassland at the 1-km spatial scale (βGrassIJI1K = −2.30, SE = 0.63), and litter depth (βLitter = 0.46, SE = 0.13). Finally, there were negative effects of the percent of the landscape in woodland at the 200-m spatial scale (βWoodPLAND200 = −4.67, SE = 1.37) and the interspersion of grassland at the 100-m spatial scale (βGrassPS1K = −2.02, SE = 0.70) on colonization probability. Detection probability was affected by the additive effects of canopy cover and monarch density; no other detection model was competitive. In the top model there was a positive effect of monarch density (βDensity = 0.28, SE = 0.05) and a negative effect of canopy cover (βCanopy = −0.18, SE = 0.03) on detection probability. In Iowa, monarchs are widespread on conservation lands where they avoid sites with lots of canopy cover. Colonization and extinction processes are influenced by an interplay of landscape attributes across multiple spatial scales and site habitat attributes. Our study provides the first comprehensive insight into monarch use of conservation lands in Iowa, and predicted responses to important covariates may be useful for future conservation efforts.

The Iowa Multiple Species Inventory and Monitoring (MSIM) Program includes a protocol for monitoring butterfly density on conservation lands using transects. Most data are collected from sites chosen randomly; additional sites are chosen non-randomly for other reasons. We analyzed a 12-year dataset for monarchs to address how density (per 50 m2 transect section) responded to site selection (random vs. non-random), latitude, and measures of the amount of milkweed and canopy cover on survey transects. Between 2006 and 2017, we conducted 2,328 surveys on 420 sites and detected a total of 2,757 adult monarchs. Monarch densities peaked in 2010 for random sites and 2012 for non-random sites, but densities were lowest in 2013 for both site types. The density of monarchs at non-random transects (0.047, 95% CI = 0.031, 0.062) was higher than that at random transects (0.029, 95% CI = 0.019, 0.044) and the temporal trends of density for random and non-random sites were significantly different. Monarch density was positively correlated with UTM northing, suggesting that monarch density increases from south to north in Iowa. The percent of plots containing milkweed was positively correlated with monarch density whereas percent tree canopy cover was negatively correlated with monarch density. Our results show that non-random transects had more monarchs, which may be a concern when interpreting findings from some citizen science efforts that used non-probabilistic sampling designs. Collectively, the MSIM program data provide a comprehensive assessment of monarch densities statewide as well as the first empirically-derived density estimates for monarchs on the breeding grounds and may prove helpful when refining future monitoring efforts.