The Integrated Monarch Monitoring Program: From Design to Implementation

Steep declines in North American monarch butterfly (Danaus plexippus) populations have prompted continent-wide conservation efforts. While monarch monitoring efforts have existed for years, we lack a comprehensive approach to monitoring population vital rates integrated with habitat quality to inform adaptive management and effective conservation strategies. Building a geographically and ecologically representative dataset of monarchs and their habitat will improve these efforts. These data will help track long-term changes in the distribution and abundance of monarchs and their habitats, refine population and habitat models, and illuminate how conservation activities affect monarchs and their habitats. The Monarch Conservation Science Partnership developed the Integrated Monarch Monitoring Program (IMMP) to profile breeding habitats and their use by monarchs in North America. A spatially balanced random sampling framework guides site selection, while also allowing opportunistic inclusion of sites chosen by participants, such as conservation areas. The IMMP weaves new protocols together with those from existing monitoring programs to improve data compatibility for assessing milkweed (Asclepias spp.) density, nectar resources, monarch reproduction and survival, and adult monarch habitat use. Participants may select a protocol subset according to interests or local monitoring objectives, thereby maximizing contributions. Conservation partners, including public and private land managers, academic researchers, and citizen scientists contribute data to a national dataset available for analyses at multiple scales. We describe the program and its development, implementation elements that make the program robust and feasible, participation to date, and how IMMP data can advance research and conservation for monarchs, pollinators, and their habitats

Using landscape habitat associations to prioritize areas of conservation action for terrestrial birds.

Predicting species distributions has long been a valuable tool to plan and focus efforts for biodiversity conservation, particularly because such an approach allows researchers and managers to evaluate species distribution changes in response to various threats. Utilizing data from a long-term monitoring program and land cover data sets, we modeled the probability of occupancy and colonization for 38 bird Species of Greatest Conservation Need (SGCN) in the robust design occupancy modeling framework, and used results from the best models to predict occupancy and colonization on the Iowa landscape. Bird surveys were conducted at 292 properties from April to October, 2006-2014. We calculated landscape habitat characteristics at multiple spatial scales surrounding each of our surveyed properties to be used in our models and then used kriging in ArcGIS to create predictive maps of species distributions. We validated models with data from 2013 using the area under the receiver operating characteristic curve (AUC). Probability of occupancy ranged from 0.001 (SE 0.70). The most important predictor for occupancy of grassland birds was percentage of the landscape in grassland habitat, and the most important predictor for woodland birds was percentage of the landscape in woodland habitat. This emphasizes the need for managers to restore specific habitats on the landscape. In an era during which funding continues to decrease for conservation agencies, our approach aids in determining where to focus limited resources to best conserve bird species of conservation concern

List of species, their respective guild, and estimates (standard error; SE) for occupancy (Psi), colonization (Gamma), and detection (p) probabilities, and area under the receiver operating characteristic curve (AUC).

<p>List of species, their respective guild, and estimates (standard error; SE) for occupancy (Psi), colonization (Gamma), and detection (p) probabilities, and area under the receiver operating characteristic curve (AUC).</p

Predicted probability of occupancy and colonization for three bird Species of Greatest Conservation Need (SGCN) in Iowa using the covariates on Psi and Gamma from the best model for each species.

<p>Maps display values for one grassland species (Bobolink [<i>Dolichonyx oryzivorus</i>]), one woodland species (Acadian Flycatcher [<i>Empidonax virescens</i>]), and one scrub-shrub species (Bell’s Vireo [<i>Vireo bellii</i>]), all of which had predicted models considered useful (AUC > 0.70). (a) Predicted probability of occupancy for Bobolink, (b) Predicted probability of occupancy for Acadian Flycatcher, (c) Predicted probability of occupancy for Bell’s Vireo, (d) Predicted probability of colonization for Bobolink, (e) Predicted probability of colonization for Acadian Flycatcher, (f) Predicted probability of colonization for Bell’s Vireo.</p

Predicted probability of occupancy and colonization for three range-restricted bird Species of Greatest Conservation Need (SGCN) in Iowa using the covariates on Psi and Gamma from the best model for each species.

<p>Predictive models for all species displayed were considered useful (AUC > 0.70). (a) Predicted probability of occupancy for Northern Bobwhite (<i>Colinus virginianus</i>), (b) Predicted probability of occupancy for Red-shouldered Hawk (<i>Buteo lineatus</i>), (c) Predicted probability of occupancy for Kentucky Warbler (<i>Geothlypis formosa</i>), (d) Predicted probability of colonization for Northern Bobwhite, (e) Predicted probability of colonization for Red-shouldered Hawk, (f) Predicted probability of colonization for Kentucky Warbler.</p