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Key Concepts: Good, Better, Best

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A brief overview of how the rankings of Good, Better, and Best are used throughout this Handbook to lay out different options for inventorying, management, and monitoring.

Assessing the ecological integrity of sites before and after management activity is essential to understanding management outcomes, probing if and to what degree outcomes meet expectations, and drilling down into the details in order to improve understanding and management over time. One model is the multi-metric, multi-level inventory and assessment methodology of the Natural Heritage Network and NatureServe (Faber-Langendoen et al. 2019), called Ecological Integrity Assessment (EIA). The following method, based on NatureServe’s EIA, provides a generalized concept of how to determine the ecological quality of a site. This method can be modified based financial constraints and level of available knowledge. While the “Best” category can be considered the gold standard, any of the three options can provide valuable insights into ecosystem health and sustainability.

The approaches below include both qualitative indicators (evaluated subjectively in clearly defined categories, e.g., “high,” “moderate,” “low,” and “none,” referring to conditions such as infestation by invasives, tree advance regeneration, survival of plantings) and quantitative indicators (measured or estimated numerically, e.g., percent cover of key plant species functional groups in sampling quadrats; numbers of nesting pairs of grassland-obligate bird species; acres of newly planted forest trees). An efficient set of indicators strikes a balance between providing essential information on the direction and magnitude of the response of an ecosystem to various management actions and stressors, and keeping the costs of collecting the information within reasonable limits.

Good—Assessments are basic overviews of context and condition, often based on landscape-level metrics derived from aerial imagery and qualitative site observations. Natural cover and condition (e.g., distance to roads) are quantified in GIS (geographical information systems). Often this can be done using a Landscape Condition Model (LCM) (Pennsylvania Natural Heritage Program 2016) to determine a basic condition score from remotely sensed data.  

Better—Assessments involve a greater amount of field observation to determine the condition of the site and the use of standardized protocols to obtain and analyze data. “Better” methods are more rigorous than “Good,” but are still qualitative or only semi-quantitative (e.g., timed-meander plant species survey) approaches to determine specific types of habitat or plant community and address their management needs. Data analyses employ widely accepted tools to indicate condition, such as state and regional floristic quality assessments (FQA) (Chamberlain and Ingram 2012) or wetland indicators to quantify habitat type and condition. 

Best—These methods represent the most intensive evaluation of a site’s quality. “Best” methods are rigorous, quantitative approaches to collect detailed data, often with a clear sampling design intended to monitor trends in condition over time. “Best” metrics are quantitatively assessed and statistically evaluated to ensure that they address key goals in decision-making. “Best” methods are usually focused on species-level assessments of communities to determine the condition of a site. For example, the Vegetation Index of Biotic Integrity (VIBI) (Mack 2001) is a highly rigorous assessment protocol that uses plant species as quality indicators and to set management performance measures (Faber-Langendoen et al. 2019).

Assessment metrics are monitored at regular intervals to analyze trends in ecosystem condition over time, from the first (baseline) assessment through all successive assessments. Following Natural Heritage Program methodology, metrics can be divided into three categories—size, landscape context, and condition (Faber-Langendoen et al. 2019). 

Size refers to the total assessment area size or to the sizes of habitat patches within a site. However, bigger does not always equate to better. The relevant measure of habitat size depends on the needs of particular species; for instance, forest-interior and grassland-interior birds are sensitive not only to habitat size but also shape. For them the size that matters is of the part that is more than 100 meters from an edge, which can be very different between two areas of identical total size—much larger in one that is circular (in which interior habitat occupies the largest possible percentage) compared with one that is narrow or with a meandering edge (in which interior habitat is a much smaller percentage or even zero).

Landscape context refers to the neighborhood in which a site is situated. For example, is the assessment area surrounded by forest, farm fields, roads, or residential, commercial or industrial development? Does it have a contiguous natural buffer between it and roads or developed areas?  

Condition metrics, also called ecological indicators, include measures of the presence or abundance of desired vegetation and invasive vegetation, condition of the native vegetation itself (e.g., intactness of each forest structural layer), and intensities of human-caused stressors. Indicators may be qualitative or quantitative.


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Chamberlain, S. and H. Ingram. 2012. Developing coefficients of conservatism to advance floristic quality assessment in the Mid-Atlantic region. Journal of the Torrey Botanical Society 139:416-427. (doi.org/10.3159/TORREY-D-12-00007.1)

Faber-Langendoen, D., J. Lemly, W. Nichols, J. Rocchio, K. Walz, and R. Smyth. 2019. Development and evaluation of NatureServe’s multi-metric ecological integrity assessment method for wetland ecosystems. Ecological Indicators 104:764-775. (natureserve.org/sites/default/files/publications/files/Faber-Langendoen etal_2019_NatureServe EIA method for wetland ecosystems_EcoInd.pdf, as of 2024)

Tracey, C. et al. 2018. A Landscape Condition Model (LCM) for Pennsylvania. NatureServe (researchgate.net/publication/324569897_A_Landscape_Condition_Model_LCM_for_Pennsylvania, as of 2024).