00454nas a2200133 4500008004100000245005700041210005700098100001500155700001700170700001800187700001700205700001700222856008100239 2019 eng d00aRestoring grassland in the context of climate change0 aRestoring grassland in the context of climate change1 aBaer, S.G.1 aGibson, D.J.1 aJohnson, L.C.1 aGibson, D.J.1 aNewman, J.A. uhttp://lter.konza.ksu.edu/content/restoring-grassland-context-climate-change01657nas a2200181 4500008004100000245010600041210006900147300001100216490000600227520099300233653002501226653002001251653001801271100001901289700002101308700001701329856012901346 1998 eng d00aPermutation of two-term local quadrat variance analysis: general concepts for interpretation of peaks0 aPermutation of twoterm local quadrat variance analysis general c a41 -440 v93 aMany ecological studies use Two-Term Local Quadrat Variance Analysis (TTLQV) and its derivatives for spatial pattern analysis. Currently, rules for determining variance peak significance are arbitrary. Variance peaks found at block size 1 and at > 50 % of the transect length are the only peaks whose use is explicitly prohibited. Although the use of variance peaks found at block sizes > 10 % of the transect length have also been warned against, many researchers interpret them regardless. We show in this paper that variance peaks derived from TTLQV are subject to additional ‘rules of thumb’. Through the use of randomization and permutation analyses on real and simulated data of species abundance in contiguous plots along a single transect, we show that variance peaks found at block sizes 1, 2 and 3 occur frequently by chance and thus likely do not indicate biologically meaningful patterns. The use of multiple replicate transects decreases the probability of Type II error.10aPermutation analysis10aSpatial pattern10aVariance peak1 aCampbell, J.E.1 aFranklin, D.J.G.1 aNewman, J.A. uhttp://lter.konza.ksu.edu/content/permutation-two-term-local-quadrat-variance-analysis-general-concepts-interpretation-peaks