Tingyi’s Geob479 blog

A review letter to “Evaluation of Spatial Elasticity of Landscape in Typical

Grassland Nature reserve by GIS”

–reviewed by Tingyi Liu

Original Paper access: http://www.j-csam.org/jcsam/ch/reader/create_pdf.aspx?file_no=20190623&flag=1&journal_id=jcsam

The purpose of this research, which is introduced by the authors at the beginning
of the paper is to understand the effect of grassland vegetation restoration and evaluate
grassland spatial elasticity, then further to help formulate a grassland vegetation
restoration plan and optimizing protection function areas. The scientists took Xilin Gole
League Grassland Nation Nature Reserve as their study object. They proceeded this
research with the using ArcGIS, Fragstas, Erdas imagine Microsoft Excel and analyze
the spatial elasticity of landscape by using a conceptual landscape spatial elasticity
model established by them.
Before analysis, the scientists obtained resource data including maps such as
grassland landscape types map, vegetation map etc., DEM, Landsat8 OLI data, and
weather record data such as average temperature and precipitation etc.
First, they produced six maps to illustrate the spatial distribution pattern of different
influential factors of the research areas-landscape types, the sensitivity of soil and water
loss, the sensitivity of climate’s humidity change, sensitivity of land
desertification(based on NDVI), sensitivity of flood disasters and human disturbance
intensity.
These six nicely made maps were nice and clear, and these can really help readers to
obtain the information they need for understanding this paper well and fast. The authors

did not include details about how they defined or calculated the sensitivities and
intensities in this paragraph along with the maps, but in the following two sections they
introduced how they determine or calculated (with formula) the sensitivities by four
landscape indices (Cohesion, IJI, FRAC_MN and LPI) and then used these four
sensitivity index to deduce landscape stability(LSS)
The conceptual landscape spatial elasticity model(LSR, Dimensionless quantity, 0~100)
used in the following step was established from three factors: landscape pattern stability
( LPS) ,landscape ecological sensitivity (LES) and human disturbance (0~100). The
LSR formula also included landscape resilience constant and a coefficient of

disturbance. The formula is: .
The scientists divided the research area into five kinds of landscape types and three
kinds of functional area: core area, buffer area around the core areas and the
experimental area which takes the rest area in this nature reserve. The scientists
compared the LSS and the key indicators for LSS of each type of grassland landscape.
Also, they graded the value of LSR into five groups from extremely insensitivity to
extremely sensitive. The author used maps, bar graphs and tables to illustrate the
ecological sensitivity distribution and the ratio of each area of different conservation
types.
Finally, the authors conclude that the core area has relatively high landscape
stability according to the LSS analysis and the percentage of area with high stability.
But both the LSS of single conservation type areas and the overall grassland area are
still at a low level compared to the theoretical optimal value. This negative point the

authors mentioned gives the research paper more potential in practical use. As for
ecological sensitivity, the author summarized the distribution of a more sensitive area
and concluded the reason for the great variety of sensitivity among different function
areas sue to both human and natural influence. I would suggest them to spread this
cause a little bit more, such as what specific activities and natural events or characters
are affecting this index, because they also include different types of human disturbance
as details in the recent analysis. As the more than 70% area in this reserve has medium
and low spatial elasticity, and the elasticity decrease with the strict level pf production
from core area to experimental area, the author only gives a short discussion about their
suggestions, which is only about the different percentage of areas that need different
amount of extra protection work.
In conclusion, the delivery, especially the structure and figures used in this paper, is in
good quality. The methodology or data analysis part of this research is at a high level.
The indicators the scientists used are properly chosen and processed, and just some
details are not very well described such as some term included in formulas are
introduced too simply. The major limitation of this paper is its conclusion and
discussion part. The conclusion section of this paper is more like a shorter summary of
their results and a lack of further discussion about the guiding role of grassland
conservation work. I hope they could provide some suggestions on how these
researches can help to improve assess, planning and optimize the grassland reserve as
they mention as purpose in the abstract. The title used “typical grassland”, but this
paper is more like a case study without describing how this case has universal guiding

value on more kinds of grassland. I would think this paper should include a simple
introduction to the similarity and differences of Xilin Gole Grassland reserve to other
types of grassland and involve comparisons during proceeding analysis. Thus, I would
like to give this paper a grade of 8 out of 10.

Reference

Zhao, F., Yu, Q., Yue, D., Yang, X., Su, K., & Qu, Z. (2019). Feoli, E., & Zuccarello, V.
(2019). Spatial pattern of ecological processes: the role of similarity in GIS applications
for landscape analysis. Spatial Analytical Perspectives on GIS. Transactions of the
Chinese Society for Agricultural Machinery, 209–217.
(赵方博, 岳德鹏, 杨晓潇, 于强, 苏凯, & 屈志强. (2019). 典型草原自然保护地
景观空间弹性 GIS 评价. 农业机械学报, (6), 23.)

Feoli, E., & Zuccarello, V. (2019). Spatial pattern of ecological processes: the role of
similarity in GIS applications for landscape analysis. Spatial Analytical Perspectives on
GIS, 175–186. doi: 10.1201/9780203739051-13

Gotham, K. F., & Campanella, R. (2011). Coupled vulnerability and resilience: The
dynamics of cross-scale interactions in post-Katrina New Orleans. Ecology and Society,
16(3).