Eastern Meadowlark Conserving Wildlife and Their Habitats Through a Targeted Habitat Conservation Approach

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Nebraska’s Targeted Conservation Initiative Eastern Meadowlark Conserving Wildlife and their Habitats through a Targeted Habitat Conservation Approach

Habitat Management: Traditionally Speaking think outside of the proverbial “box,” or rather, the Managing habitat for species is a fundamental compo- boundary — often arbitrarily defined — that contains nent in wildlife conservation and often plays a critical our management area. Using land cover data, we can role in maintaining, or even increasing, species’ popula- identify specific cover types (e.g., tallgrass prairie, tions. Traditionally, conservation practitioners utilized deciduous woodland, wetlands, etc.) that surround species-habitat relationships identified in previous survey locations or management areas and use them to explore relationships to species presence and/or abun- research to guide management decisions. For example, if dance. The proportion of land cover in the surrounding research determined that high forb diversity, vegetative litter, and grass height were positively related with the landscape can be measured within varying distances by presence of a grassland bird species, we may, as conser- using a Geographic Information System (GIS), and may vation practitioners, attempt to manage or modify be used to identify the area affecting a species response, grassland habitat structure accordingly to meet the or even the strength of the relationship to a given land- species’ requirements. Although these decisions are cover type. These relationships may be integrated into a based on published scientific literature, we too often lose Species Distribution Model (SDM) using GIS, which sight of the fact that many ecological processes simulta- neously act across various spatial and temporal scales. In Species Distribution Models the previous example, the identified species-habitat relationships likely occur at a local spatial scale (i.e., the field level or territory level), which may or may not hold Species Distribution Models (SDMs) are applications of ecological niche theory that are useful in predicting the likelihood of a true in a different landscape context (e.g., in an area species occurring, based on species’ relationships to landscape, containing high densities of woody cover rather than topographic, and climate variables. As ecological systems and grassland). As geospatial and remote sensing techniques their respective populations continue to face new threats from have improved significantly, so has our knowledge of climate change, habitat loss, and biological invasions, SDMs how the context and composition of the landscape can provide a solid foundation that facilitates the ability of dramatically affect species occurrence and abundance. A policymakers, conservation planners, and practitioners to make informed predictions regarding when and where to implement failure to account for landscape constraints on species conservation strategies. In addition, SDMs allow extrapolation of populations may reduce the likelihood of achieving the relatively limited field samples from finite study areas to the desired conservation goals, and thus reduces the efficacy entire potential range of a species. Once a predictive distribution of our conservation efforts. is produced, the SDM can be applied to a number of applications in the conservation field. For instance, SDMs can be used to Thinking Outside the “Box” predict changes in species distributions resulting from climate Although local habitat composition and structure are change, identify how species respond to changes in habitat connectivity, forecast biological invasions, detect biological unquestionably important in increasing the likelihood of hotspots, discover new species’ ranges, and predict species species occurrence or even abundance, we must begin to responses to changes in land use.

Nebraska’s Targeted Conservation Initiative Eastern Meadowlark produces a spatially explicit model capable of identify- developed and tested a candidate set of global models ing suitable locations for local management efforts (i.e., with land cover variables measured within seven spatial our conservation “box”) throughout a geographic scales (31, 124, 497, 1118, 1987, 4472, and 7949 acres). extent. We used a model selection approach (AICc) to identify the statistical model that best supported our data. The Eastern Meadowlark The Eastern Meadowlark’s range is distributed through- Results indicated that Eastern Meadowlarks responded out eastern Nebraska, along the Central Platte River and positively to the available grassland cover in the the northern edge of the state. The Eastern Meadowlark surrounding landscape (within 31 acres; Fig. 1). The predominantly nests in prairies, open pastures and likelihood of Eastern Meadowlark occurrence decreased hayfields, but also nests in a variety of other habitats as anthropogenic development and woody cover including roadsides, cropland borders, and other open increased in the surrounding landscape (Fig. 1). These grassy areas. In regions where both Western and results agree with previous studies suggesting that Eastern Meadowlarks occur, Eastern Mead- Eastern Meadowlarks prefer landscapes containing owlarks tend to more often inhabit poorly drained grassland and lowland areas. The Eastern Meadowlark is considered a regular breeder in Nebraska, but the species has a limited distribution in the state. The Eastern Meadowlark is not federally listed or considered an At-Risk Species by the state. However, by managing for Eastern Meadow- larks, managers may be able to provide additional habitat for various other species that respond to similar cover types. Breeding Bird Survey Data Analysis In order to assess landscape effects on Eastern Meadowlark populations, we used the Breeding Bird Survey (BBS) data collected in Nebraska from 2005 through 2011. We modeled the effects of various climate factors (e.g., 30-year average precipitation), land Fig. 1. Eastern Meadowlark probability of occurrence increases at a survey cover (e.g., percent grassland within a location (Breeding Bird Survey stop) as the percentage of grassland (blue line) specified area), and survey-specific variables increases in the landscape (within 31 acres). An increasing amount of develop- (e.g., Stop ID) on species presence-absence, ment (black line) and woodland (red line) in the surrounding matrix tends to decrease the Eastern Meadowlark’s probability of occurrence. using mixed-effects regression models. We

Nebraska’s Targeted Conservation Initiative Eastern Meadowlark grassland habitat, particularly tallgrass prairie. Other Meadowlarks throughout the state. In addition, the variables, such as long-term average precipitation and resulting SDM can be used in conjunction with more the amount of spring precipitation, significantly influ- complex decision support tools that are designed to enced occurrence and distribution of Eastern Meadow- assist in conservation planning. These tools may be larks in Nebraska (see full report at rwbjv.org). focused only on a single species, or alternatively, they The land cover and climatic relationships identified from can incorporate multiple SDMs into a single decision the best-fitting statistical model for Eastern Meadowlark support tool to help facilitate community ecological were integrated into a SDM using GIS (Fig. 2). The planning. Furthermore, SDMs can be used in scenario SDM can be used by conservation practitioners and planning exercises, allowing conservation practitioners planners to help identify and target suitable regions in to predict species response to changes in land use or the state where local habitat management can provide climate over a predicted period of time. the greatest benefit to the species. These ‘hotspots,’ or red areas in the SDM, indicate the top 10 percent of the range of predicted probability of occurrence values in the state. Just as a thunderstorm would appear on radar, these color schemes provide a visual means of identify- ing the predicted occurrence and distribution of Eastern

Fig. 2. The Eastern Meadowlark probability of occurrence species distribution model for Nebraska.

Nebraska’s Targeted Conservation Initiative Eastern Meadowlark So Why Go the Extra Mile? expert opinion and discretion, SDMs are valued decision SDMs are powerful conservation planning tools that can support tools that can assist conservation practitioners in be useful in targeting management efforts throughout the meeting their population objectives. Such conservation state. In combination with additional spatial data, such as tools can help agencies and organizations become more the USDA Farm Service Agency’s Common Land Unit efficient in managing for species, and therefore become dataset (CLU), we can pinpoint specific tracts of land more cost-effective with limited conservation resources. best suited for habitat management. But why go the extra mile, when research has previously identified relationships between species and the surrounding land cover or habitat type? The answer to this question is that we must begin to understand and address how the relationships interact if we hope to predict probability of occurrence. For example, an area containing short to moderate grass height, high forb diversity, and moderate levels of litter may appear to be optimal breeding habitat for a grassland bird species, yet the surrounding landscape is densely covered with forests and the climate conditions are sub-optimal. In this example, it may be nearly impossible for managers to remove enough trees to achieve a species response (e.g., Fig. 3). To elaborate further, when forming predictions of species occurrence, the relationships all interact, so that even when a positive relationship exists between a specific cover type and Fig.3. The conceptual model describes possible management strat- species abundance, it may be inhibited by one or more of egies for grassland birds, based on land cover and a species distri- the additional land cover or climate relationships bution model. Although grassland birds tend to respond positively identified in the model. By considering these interacting to grass in the surrounding landscape, interactions between one or more types of habitat often exist (i.e., grassland birds also tend to relationships prior to prescribed habitat management, respond negatively to woody cover). Managing habitat for priority managers can target landscapes best suited for the species in areas containing high proportions of grass in the land- species and may even determine possible strategies scape may not be as beneficial to the species when woody cover based on the SDM (e.g., Fig. 3). In combination with also exists in the surrounding area.

Funding for this project was received from the Great Plains Landscape Conservation Cooperative (grant # F11AP00021) and was admin- istered by the Nebraska Game and Parks Commission. The models and results presented in this document are based on spatial modeling efforts conducted by the Rainwater Basin Joint Venture, Grand Island, NE, U.S.A. For more information, visit rwbjv.org and read the original report: Conservation of Avian Resources through Species Distribution Models and Strategic Habitat Conservation.