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3.3.2 Terrestrial Habitat Fragmentation


Goal: C. Protect and enhance landscape and habitats structure and processes to benefit ecosystem and watershed functions

Objective: 2. Protect and enhance terrestrial (native upland) habitat connectivity both within the watershed and into adjacent watersheds

WAF Attribute: Landscape Condition

What is it?

This indicator is a measure of landscape fragmentation using a metric known as effective mesh size.  Effective mesh size is based on the probability that two points chosen randomly in a region will be connected, and that barriers like roads, railroads, or urban development do not separate the points (Jaeger 2000, Moser 2007, Girvetz et al., 2008). A high effective mesh size value indicates low fragmentation of the landscape. Fragmentation, or its corollary connectivity, was recently calculated for the whole of California (Girvetz et al., 2008).

Why is it Important?

Landscape fragmentation is a process by which larger areas become smaller, more numerous and isolated by physical or other barriers. Structural changes in ecosystems, such as fragmentation in vegetative cover, causes functional changes in hydrological, geochemical, and geomorpological processes. At the landscape scale, fragmentation (and its corollary connectivity) for individual taxa may be the most important of physiographic properties, because it is a measure of intactness, which along with habitat type and forage availability describes what individual taxa and biodiversity need across daily to evolutionary timeframes. Landscape fragmentation results in further changes in other structures (e.g., aquatic habitat) and processes, leading to an unraveling of complex systems and loss of resiliency. Species existing in a fragmenting landscape will have different responses to the process. Some will be less able to adapt to the changes leading to a reduction in the probability of survival over time. Ultimately, fragmentation can result in a reduction of biodiversity, a measure of the health of an ecosystem. All landscapes have some degree of natural fragmentation, however a landscape with fewer anthropogenic sources of fragmentation is regarded as healthier and an objective for environmental protection.

Intactness and habitat quality and the connectivity that they help to confer, are closely related to the ecological state of particular landscapes. A place that has undergone a large change in cover (e.g., from grazing or crop irrigation) may attain a different resilient state than the original, natural state. One commonly-proposed adaptation strategy is improving structural connectivity under different climate change scenarios to increase the likelihood that species ranges can change adaptively over time (Carroll et al., 2009). Providing for biodiversity conservation under climate change and land-use pressure includes protecting connectivity as a landscape attribute to facilitate individual species and community migration.

What is the target or desired condition?

Natural fragmentation of habitats is an expected characteristic of Sierra Nevada landscapes and is desirable. Fragmentation by roads and other infrastructure and activities is not. Fragmentation affects different species and natural processes differently, meaning that there is no single value of fragmentation that has broad ecological meaning. A target condition (score of 100) was set at the largest measured effective mesh size in any Feather River subwatershed (South Yuba). All other subwatersheds were compared to that value and scores expressed as proportions.

What can influence or stress condition?

The most direct cause of habitat fragmentation is land-use actions by people. These include housing development, roads & highways, canals, logging, surface mining, agriculture, and recreation. The combination of infrastructure and use of the infrastructure causes the overall disturbance to habitats and landscapes. The decision-making that leads to fragmentation is spread among many private and public bodies and many social and economic benefits are derived from past and current fragmenting structures and activities.

What did we find out/How are we doing?

The largest average effective mesh size value for the subwatersheds was 221 sq. km, for the South Yuba, which had a score of 100 (Table 1, Figure 1). The lowest score of 2 was for the Lower Bear subwatershed, corresponding to an effective mesh size of 4.9 sq km. The average score for all planning watersheds (~10,000 acre creek drainages) in the landscape was 10.1 indicating that the effective mesh size for most of the landscape is low compared to the maximum observed.

Table 1. Report Card for Habitat Fragmentation

Goal Measurable Objective Subwatershed Score
C. Protect and enhance landscape and habitats structure and processes to benefit ecosystem and watershed functions 2. Protect and enhance terrestrial (native upland) habitat connectivity both within the watershed and into adjacent watersheds NFF 81
MFF 44
LF 5
NY 54
MY 27
SY 100
DC 5
LY 11
UB 14
LB 2

Figure 1. Distribution of subwatershed landscape and habitat fragmentation scores

Temporal and spatial resolution

Effective mesh size was previously calculated for the whole of California by Girvetz et al. (2008). The finest-resolution values were available for planning watersheds, which are creek drainages with sizes around 10,000 acres. This calculation has only been done once for the state using roads and other barriers (e.g., urban areas), so temporal resolution is limited to this most recent calculation.

How sure are we about our findings (Things to keep in mind)

The effective mesh size metric is one estimator of fragmentation. It treats all barriers as identical in their prevention of wildlife movement and inhibiting other ecological flows, though it is more likely that barriers are relatively permeable, rather than absolutely impermeable. There are other fragmentation metrics in the literature relating to the size, shape, and distribution of “patches”, which are the pieces of habitat surrounded by roads or other habitats. The measurement itself is very accurate at the planning and subwatershed scale, though there was considerable variation in effective mesh sizes among planning watersheds (Table 2). Overall, this metric provides a good general indication of fragmentation condition, especially in a relative sense within a region or river basin.

Additional Information

Data sources

Effective mesh size data were those described in Girvetz et al. (2008) and were obtained directly from the authors.


Effective mesh size (expressed in sq. km) values for individual planning watersheds were aggregated to the subwatershed using area weighted averaging.

The effective mesh size value for each subwatershed was compared to the maximum observed effective mesh size value among all subwatersheds (South Yuba). The following equation was used to generate a score for each subwatershed relative to the maximum observed EMS value: Score = EMSsw / max(EMSsw), where EMSsw is the area weighted EMS value calculated for the subwatershed and max (EMSsw) is the maximum EMS value observed in a subwatershed. The score ranges from 0 (low) to 100 (high).

Table 2 — Basic statistics for effective mesh size for subwatersheds. “95% C.I. refers to 95% confidence intervals around the mean. “PW” refers to planning watersheds and “SW” refers to subwatersheds.

Subwatershed Name PW in SW (count) Minimum EMS (sqkm) Maximum EMS (sqkm) Mean EMS (sqkm) 95% C.I. Score
Deer Creek 8 1.581 36.045 10.304 8.7 4.6
East Branch North Fork Feather 75 5.377 318.431 51.981 6.5 23
Lower Bear 10 2.778 11.429 4.911 1.6 2.2
Lower Feather 19 1.767 204.927 9.852 21.5 4.5
Lower Yuba 14 7.463 89.939 25.050 13.1 11
Middle Fork Feather 98 9.050 438.637 97.160 22.9 44
Middle Yuba 20 7.286 156.699 60.835 18.5 27
North Fork Feather 86 2.188 730.727 179.089 36.6 81
North Yuba 34 24.091 275.046 120.255 26.9 54
South Yuba 25 4.932 537.050 221.597 76.2 100
Upper Bear 21 1.317 115.992 32.009 14.1 14


Carroll, C., J.R. Dunk, and A. Moilanen. 2009. "Optimizing resiliency of reserve networks to climate change: multispecies conservation planning in the Pacific Northwest, USA." Global Change Biology, doi: 10.1111/j.1365-2486.2009.01965.x.

Girvetz E.H., Thorne J.H., Berry A.M., Jaeger J.A.G. 2008. "Integration of landscape fragmentation analysis into regional planning: a statewide multi-scale case study from California, USA." Landscape and Urban Planning 86:205–218

Jaeger, J. A. G. 2000. “Landscape division, splitting index, and effective mesh size: new measures of landscape fragmentation.” Landscape Ecology 15(2): 115-130.

Moser, B., J. Jaeger, et al. (2007). “Modification of the effective mesh size for measuring landscape fragmentation to solve the boundary problem.” Landscape Ecology 22(3): 447-459.